Proceedings of Fourth International Conference on Computing, Communications, and Cyber-Security: IC4S 2022 9819914787, 9789819914784
This book features selected research papers presented at the Fourth International Conference on Computing, Communication
249 80 30MB
English Pages 919 [920] Year 2023
Preface
Contents
Editors and Contributors
Communication and Network Technologies
Design and Implementation of an IoT-Based Indoor Hydroponics Farm with Automated Climate and Light Control
1 Introduction
2 Literature Review
3 System Design Methodology
3.1 System Architecture
3.2 IoT System Decision Flow
3.3 User Interface Mobile Application
4 Results
5 Conclusion
References
Drone Ecosystem: Architecture for Configuring and Securing UAVs
1 Introduction
2 UAV Ecosystem Infrastructure
3 Communication Architecture-Stage One
3.1 UAV or Drones
3.2 Light-Weight Cryptographic Function
3.3 Ad Hoc Network
4 Communication Architecture-Stage Two
4.1 5G Cellular Network
4.2 5G Cellular Tower
4.3 Network Slicing
5 Communication Architecture-Stage Three
5.1 Ground Station
5.2 Sub-ground Station
5.3 HTTP-3/QUIC Messaging Protocol
5.4 Zero-Round Trip Time (Zero/0-RTT)
5.5 Cloud, Cloud-Based Storage, and WAi
6 Security: Types of Attacks
6.1 Cyberattack Vectors
6.2 Physical Threat to Drones
7 Conclusion and Future Scope
References
An Improved Neural Network-Based Routing Algorithm for Mobile Ad Hoc Networks
1 Introduction
2 Related Work
3 Proposed Method
3.1 Path Finding Mechanism
3.2 Management of Event
3.3 Evaluation of the QoS Parameters
4 Results and Discussion
5 Conclusion
References
Energy Harvesting in Fifth-Generation Wireless Network: Upcoming Challenges and Future Directions
1 Introduction
2 Background and Motivation
3 Trends in Energy Harvesting
4 Challenges
5 Future Directions
6 Conclusion
References
Develop a Quantum Based Time Scheduling Algorithm for Digital Microfluidic Biochips
1 Introduction
2 Problem Description
2.1 Motivation
2.2 Problem Formulation
3 Proposed Algorithm
4 Experimental Result
5 Conclusion
References
Revolution in Agriculture with the Aid of Internet of Things
1 Introduction
2 Review of Literature
3 Benefits of IoT in Agriculture
4 Role of IoT in Agriculture
5 Proposed Systems
6 Conclusion
References
Supercontinuum Generation in Dispersion-Tailored Tetrachloroethylene Filled Photonic Crystal Fibers
1 Introduction
2 Theoretical Model of Tetrachloroethylene PCF
3 Dispersion Properties of the Proposed Fiber
4 SCG in Optimized Structures
5 Conclusion
References
Early Detection of Covid-19 Using Wearable Sensors’ Data Enabled by Semantic Web Technologies
1 Introduction
1.1 Motivation
1.2 Objective
1.3 Contribution
2 Literature Survey
2.1 IoT and Covid-19
2.2 SWT and SWoT
2.3 Related Works-Early Detection of Covid-19
3 Methodology
4 Evaluation
4.1 Method and Metrics
4.2 Results
4.3 Discussion
5 Conclusion and Future Scope
References
Cell Outage Detection in 5G Self-organizing Networks Based on FDA-HMM
1 Introduction
2 FDA Feature Extraction Method
3 Hidden Markov Models
4 HMM Training and Detection
4.1 Training Stage
4.2 Detection Stage
5 Simulation Results
5.1 FDA-HMM Performance at Different pp and upper LL
5.2 FDA-HMM Performance Comparison with Other Detectors
6 Conclusion
References
IoT-Based Scalable Framework for Pollution Aware Route Recommendation
1 Introduction
2 Background
3 Air Quality Standards
4 Proposed Architecture
4.1 Air Pollution Tracking
4.2 Traffic Re-routing
5 Process Methodology
6 Experimental Setup
6.1 Ingest
6.2 Collect
6.3 Process
6.4 Store
6.5 Visualize
6.6 Route Recommendation
6.7 User Interface
6.8 Result Analysis
7 Interface
8 Conclusion and Future Directions
References
Drone: A Systematic Review of UAV Technologies
1 Introduction
1.1 About the Drone and Its History
2 Contextual and Associated Work
2.1 Literature Review
2.2 Challenges in the Field of UAVs
2.3 Applications of Drones
2.4 Advantages and Disadvantages of Drones
2.5 Simulator Tools
3 Future Work and Conclusions
References
Reconfigurable Intelligent Surface-Enabled Energy-Efficient Cooperative Spectrum Sensing
1 Introduction
2 System Model
3 Energy Efficiency of RIS-Based CSS
4 Results and Discussion
5 Conclusion and Future Scope
References
Resource Sharing in Back Haul Satellite-Based NOMA Network
1 Introduction
2 System Model
2.1 Selection a User for a BS
2.2 Access to Satellite
3 Results and Simulation
4 Conclusion
References
Advanced Computing Technologies
A Review on Various Deepfakes’ Detection Methods
1 Introduction
2 Deepfakes’ Generation
3 Generative Adversarial Networks (GANs)
4 Types of Deepfakes
5 Literature Survey
6 Conclusion
References
Proposed Framework for Implementation of Biometrics in Banking KYC
1 Introduction
2 Literature Review
3 Biometric Security
3.1 Biometric Implementation in Banking
4 Retinal Biometric Recognition
4.1 What Is Retinal Biometric Recognition
4.2 Working of Retinal Biometric Recognition
4.3 Application of Iris Recognition
5 Threats and Attacks on Banking
6 Proposed Methodology
6.1 Components of the Adaptive Framework
6.2 Adaptive Operational Framework
7 Strengths of Proposed Methodology
7.1 Design Objectives of KYC Framework
8 Conclusion and Future Scope
References
Paddy Pro: A MobileNetV3-Based App to Identify Paddy Leaf Diseases
1 Introduction
2 Literature Survey
3 Proposed System
3.1 System Architecture
4 Classification Models
4.1 Convolutional Neural Networks (CNN)
4.2 MobileNetV3
4.3 Transfer Learning
4.4 Mobile App Development
5 Experimental Results
5.1 Performance Analysis
6 Conclusion
References
Cryptanalysis of RSEAP2 Authentication Protocol Based on RFID for Vehicular Cloud Computing
1 Introduction
1.1 RFID Communication System Security Standards for IoT
2 Literature Review
2.1 Definition of the Problem
2.2 The Purpose and Signicance of Our Work
3 Definitions and Mathematical Preliminaries
3.1 Background of ECC
4 RSEAP2-Protocol
5 Security Analysis of RSEAP2
5.1 Inappropriate Extraction of Keys
5.2 Inefficient Mutual Authentication Attack
5.3 Inefficient Session Key Establishment Attack
5.4 Attack on Denial of Service
5.5 Availability Issues
6 Performance Analysis
7 Concluding Remarks
References
A Survey on Code-Mixed Sentiment Analysis Based on Hinglish Dataset
1 Introduction
2 Related Research
3 Datasets
4 Challenges and Issues
5 Conclusion
References
An Alternative to PHP for the Development of Web Applications: Java Server Pages Engine
1 Introduction
2 Concept Statement
2.1 JSP: The Basis and High-Speed Setting
2.2 Shell for Java Server Pages
3 The Perspectives of Using Java Server Pages
4 Conclusions
References
Novel Load Balancing Technique for Microservice-Based Fog Healthcare Environment
1 Introduction
1.1 Motivation and Novelty
1.2 Load Balancing in Fog Computing
2 Load Balancing Technique for Microservice-Based Fog Healthcare Environment
2.1 Workflow
2.2 Details of Microservice in Proposed Healthcare System
2.3 Success_factor-Based Load Balancing Algorithm
3 Result and Discussion
3.1 Throughput
3.2 Execution Time
4 Conclusion
References
Self-improved COOT Algorithm for Resource Allocation in Cloud Data Centers
1 Introduction
2 Literature Review
2.1 Related Works
3 Resource Allocation Method in Cloud: An Overview of Proposed Concept
3.1 Suggested Resource Allocation Method
3.2 Cloud Setup
4 Improved K-means-Based Workload Clustering: SUCO-Based Optimal Centroid Identification
4.1 Improved K-means Clustering-Based Workload Clustering
4.2 Defined Threefold Objectives
4.3 Suggested SUCO Model for Resource Allocation and Optimal Centroid Selection
5 Results and Discussion
5.1 Simulation Procedure
5.2 Analysis on Energy Consumption
5.3 Analysis on Execution Time
5.4 Analysis on Resource Utilization
5.5 Convergence Analysis
5.6 Performance Analysis
5.7 Analysis on Computing Time
6 Conclusion
References
XGBoost-Based Prediction and Evaluation Model for Enchanting Subscribers in Industrial Sector
1 Introduction
1.1 Customer Interaction
1.2 Customer Engagement Marketing
1.3 Implementing a Customer Engagement Marketing Strategy
1.4 Customer Interaction Strategies
2 Literature Review
3 Proposed System Model
3.1 Work Flow Classification
4 Simulation Results
5 Conclusion and Future Work
References
CleanO-Renewable Energy-Based Robotic Floor Cleaner
1 Introduction
2 Product Design
2.1 Product Comparison
2.2 Empathize and Ideate Phase
3 Proposed System Model
3.1 Block Diagram
3.2 Architectural Diagram of IoT-Based Floor Cleaner
3.3 Navigation System
4 Proposed Product Prototype
5 Challenges and Research Opportunities
5.1 Networking
5.2 Machine Learning
5.3 Blockchain
5.4 Artificial Intelligence
5.5 Renewable and Reusable Energych23b27
5.6 Future Resources
6 Conclusion
References
Impact of “COVID-19 Pandemic” on Children Online Education: A Review and Bibliometric Analysis
1 Introduction
1.1 Motivation
2 Preliminary Data
2.1 Initial Search Results
2.2 Preliminary Data Analysis
3 Bibliometric Analysis
3.1 Geographical Region Analysis
3.2 Network Analysis
3.3 Statistical Analysis of Publication Citation
4 Conclusion and Discussion
References
Digital-Based Learning in Indian Government’s Higher Education: Initiatives and Insights
1 Introduction
1.1 Role of Digital-Based Learning
1.2 Digital Learning Strategy
1.3 Individualized Learning
1.4 Gamification and Badging
1.5 Mobile Learning (M-Learning)
1.6 Digital Learning Resources and CEC-UGC YouTube Channel
2 Literature Review
3 Electronic Textbook
3.1 e-PGPathshala, e-ShodhSindhu, Shodhganga, and e-GyanKosh
4 Animation and Graphics
4.1 SWAYAM and SWAYAM Prabha
4.2 NDLI
4.3 Spoken Tutorial and Virtual Labs
4.4 FOSSEE
4.5 ShodhShudhhi
4.6 e-Yantra, e-Kalpa, and e-Acharya
4.7 NSDL Database Management Limited Academic Depository (NDMLAD)
4.8 Vidwan
5 Conclusion
References
Autonomous Vehicles Adoption Classification for Future Mobility in UAE Using Machine Learning
1 Introduction
2 Related Literature
3 Methodology
3.1 Data Collection
3.2 Data Preprocessing
3.3 Model Development
4 Model Evaluation and Results
5 Conclusion
References
An Augmented Reality Framework as a Solution to Enhance the Experience of Visiting a Museum
1 Introduction
2 Related Works
3 Proposed Solution Architecture
3.1 System General Overview
3.2 Overall System Architecture
4 Mobile Application
5 Augmented Reality
5.1 AR Systems
5.2 ImmersalAR Versus EasyAR
6 3D Content Acquisition
6.1 3D Eva Scanner
6.2 Photogrammetry
7 Experimental Results
8 Discussion—Augmented Reality Compatibility
9 Conclusions
References
Hybrid Real-Time Implicit Feedback SOM-Based Movie Recommendation Systems
1 Introduction
2 Background and Related Work
3 Hybrid Action-Related System
4 Experiments and Discussions
5 Observations
6 Conclusion
References
Data Analytics and Intelligent Learning
Automatic SMS Spam Filtering for Disaster Response Using Classification Algorithms
1 Introduction
2 Literature Review
3 Methodology
4 Experimental Results
5 Conclusion
References
Lung Cancer Diagnosis Using X-Ray and CT Scan Images Based on Machine Learning Approaches
1 Introduction
2 Literature Review
3 Taxonomic Classification for Diagnosis of Lung Cancer Using Machine Learning
4 Machine Learning-Based Diagnosis of Lung Cancer Using X-Ray and CT Scan
4.1 Acquisition of Image Dataset
4.2 Image Preprocessing
4.3 Lung Segmentation
4.4 Nodule Enhancement
4.5 Nodule Detection
4.6 Feature Extraction
4.7 Machine Learning Algorithms
4.8 Classification
5 Conclusion
References
Hybrid Machine Learning Algorithm for Prediction of Malaria
1 Introduction
2 Related Works
3 Material and Method
3.1 Dataset Analysis
3.2 Parameters Analysis
3.3 Model Architecture
3.4 Model Evaluation
4 Result and Discussion
5 Conclusion
5.1 Feature Work
References
Yoga Pose Estimation Using Machine Learning
1 Introduction
1.1 Human Pose Estimation
1.2 Problem Statement
2 Literature Survey
3 Dataset
3.1 Dataset Acquisition
3.2 Label Hierarchy and Annotation
4 About MediaPipe
5 Methodology
5.1 Processing the Dataset
5.2 Algorithm Design
5.3 Model Description
5.4 Pseudocode
6 Results
6.1 Level 1
6.2 Level 2
6.3 Level 3
7 Conclusion
References
COVID Detection from Chest X-Ray Images Using Deep Learning Model
1 Introduction
1.1 General
1.2 Prediction
1.3 Objective
2 Literature Review
3 Methodology
3.1 Overview
3.2 Working
3.3 X-Ray Classification
3.4 Dataset
3.5 Pre-processing Techniques
3.6 COVID Detection Model
4 Experimental Results
5 Conclusion
References
Impact of Boosting Techniques in AI-Based Credit Card Fraud Detection Classifier
1 Introduction
1.1 Contribution
1.2 Organization
2 Related Work
3 Most Prominent Fraud Detection Use Cases
4 Proposed Research Work
4.1 Dataset
4.2 Execution Flow
4.3 Solution and Challenges
5 Methodology and Concepts
5.1 kNN
5.2 Naive Bayes Classifier
5.3 Decision Tree
5.4 Random Forest
5.5 AdaBoost Classifier
5.6 Multilayer Perceptron
5.7 Boltzmann Machine
6 Execution and Implementation
6.1 Dataset Selection
7 Results and Discussions
8 Conclusion and Future Work
References
Stock Price Prediction for Market Forecasting Using Machine Learning Analysis
1 Introduction
1.1 Research Contribution
2 Forecasting Stock Prices Using Machine and Deep Learning
2.1 Related Works
3 Forecasting in Stock Price Prediction and Time Series Analysis
3.1 Augmented Dickey–Fuller Test
3.2 Kwiatkowski–Phillips–Schmidt–Shin Test
4 Case Study: Time Series Analysis Using LSTM, ARIMA and SARIMAX Models
4.1 Long Short-Term Memory Analysis
4.2 Autoregressive Integrated Moving Average Analysis
4.3 SARIMAX Model
5 Conclusion and Future Works
References
Thyroid Carcinoma Prediction Using ACO and Machine Learning Techniques
1 Introduction
1.1 Thyroid Carcinoma
2 Literature Review
3 Problem Statement
4 Proposed Methodology
5 Implementation of Algorithm
6 Ant Colony Optimization Algorithm-Based Feature Selection
7 Result and Discussion
8 Conclusion
References
Cyclone Intensity Detection and Classification Using a Attention-Based 3D Deep Learning Model
1 Introduction
2 Literature Survey
3 Proposed Methodology: 3D Attention Module
4 Results and Discussion
5 Conclusion
5.1 Future Scope
References
Towards Development of Data Architecture for Learning Analytics Projects Using Data Engineering Approach
1 Introduction
2 Motivation
3 Research Organisation
4 Related Work
5 Unified Architecture for Data Infrastructure
6 Current State of Data Infrastructure Implementation at the University
7 Discussion and Conclusion
References
A Real-Time Road Crash Prediction Model by Hybridizing Multiple Learning Classifiers
1 Introduction
2 Literature Survey
3 Proposed Methodology
4 Results and Discussion
5 Conclusions
References
Machine Learning Assisted Intelligent Reflecting Surface MIMO Communication-Gateway for 6G—A Review
1 Introduction
2 Machine Learning for Wireless Systems with IRS-Assistance
2.1 Deep Learning for Communication Systems Assisted by IRS
2.2 Reinforcement Learning for IRS-Emphasised Communication Systems
2.3 Supervised Learning for Communication Systems Enhanced by IRS
2.4 Unsupervised Learning for Communication Systems Enhanced by IRS
2.5 Federated Learning for Communication Systems Enhanced by the IRS
3 Future Directions for Research in Machine Learning-Based IRS-Aided Wireless Communication
3.1 Optimal Deployment of IRS
3.2 Dynamic Hybrid Beamforming
3.3 Modelling of Constrained Systems
3.4 Channel State Characterisation
3.5 IRS for IoT Network
3.6 Anti-eavesdropping Measures
3.7 Mm Wave Communication
3.8 EDGE Intelligence
4 Conclusion
References
AI-Based Invoice Payment Date Prediction for B2B
1 Introduction
2 Literature Survey
3 Proposed Method
3.1 Logistic Regression
3.2 Decision Tree
3.3 Support Vector Machine (SVM)
3.4 Pre-processing
3.5 Comparison with Various Regression
4 Conclusion
References
Early Fault Detection for Rotating Machinery Onboard Ships Motor Using Fuzzy Logic and K-Means
1 Introduction
2 Literature Survey
2.1 Failures in Motor
2.2 Causes of Failure
3 Methodology Adopted
4 Proposed Work
4.1 Fuzzy Inference System
4.2 Membership Functions
4.3 If-Then Rules
4.4 Evaluation with Fuzzy Inference System
4.5 Dimensionality Reduction for K-Means Clustering
4.6 Optimal Parameter Calculation for K-Means Clustering
4.7 Evaluation with K-Means Clustering
5 Conclusion
References
Intellectual Movie Recommendation System Using Supervised Machine Learning Method
1 Introduction
2 Related Works
3 Proposed Approach
4 Machine Learning Algorithm Used for Recommendation System
5 Performance Assessment
6 Results
7 Conclusion and Future Work
References
A Comparative Study on Different Machine Learning Algorithms for Predictive Analysis of Stock Prices
1 Introduction
1.1 Stock Prediction
1.2 Sentiment Analysis
1.3 Motivation
1.4 Research Contribution
2 Experimental Work
3 Result and Discussion
3.1 Random Forest
3.2 Linear Regression
3.3 Support Vector Machine
4 Conclusion and Future Scope
References
Opinion Mining-Assisted Intelligent Program Selection Employing Fuzzy SWARA Mechanism
1 Introduction
2 Motivation
3 Proposed Methodology
4 Implementation
5 Result and Discussion
6 Conclusion
References
Deraining of Image Using UNet-Based Conditional Generative Adversarial Network
1 Introduction
1.1 Motivation
1.2 Related Works
1.3 Contribution and Organization of Paper
2 Methodology
2.1 Network Architecture
3 Results and Discussion
3.1 Datasets
3.2 Evaluation Metrics
3.3 Comparison with the State-of-the-Art Methods
4 Conclusion and Future Scope
References
Video Indexing and Retrieval Techniques: A Review
1 Introduction
2 Different Approaches of Video Indexing and Retrieval
2.1 Keyframes Features
2.2 Object-Based Features
2.3 Motion-Based Features
3 Analysis of Different Video Indexing and Retrieval Techniques
4 Video Indexing and Retrieval Challenges
5 Applications
6 Conclusion
References
A Robust Deep Learning Techniques for Alzheimer’s Prediction
1 Introduction
2 Literature Survey
3 Proposed Method
3.1 Overview of the Architecture
3.2 Data Pre-processing
3.3 Inception(V3) Network
3.4 Fastai
4 Experiments
5 Conclusion
References
Latest Electrical and Electronics Trends
Steganography Methods for GIF Images: A Review
1 Introduction
2 Categorization of Steganography Methods
2.1 Palette-Based Embedding
2.2 Frame-Based Embedding
3 Related Works
3.1 Palette-Based Method
3.2 Frame-Based Method
4 Evaluation Methods
4.1 Image Quality Assessment
5 Future Directions
6 Conclusion
References
Image Interpolation-Based Steganographic Techniques Under Spatial Domain: A Survey
1 Introduction
1.1 Motivation
2 Literature Review
2.1 Interpolation Techniques
2.2 Interpolation-Based Data Hiding Techniques
3 Comparative Analysis
4 Conclusion
References
A Comparative Review on Image Interpolation-Based Reversible Data Hiding
1 Introduction
2 Various Interpolation Methods
3 Related works
4 Results Analysis and Discussion
5 Conclusion
References
Real-Time Face Mask Detection Using Convolution Neural Network and Computer Vision
1 Introduction
2 Literature Review
2.1 Dataset
3 Proposed System
3.1 Implementing CNN Architecture in the Model
3.2 Data Splitting and CNN Model Training
3.3 Implementation
3.4 Proposed Algorithm
4 Experimental Results and Discussion
4.1 Detection of Face with Mask
4.2 Detection of Face Without Mask
5 Performance Analysis and Evaluation Metrics
6 Conclusion
References
A Video-Based System for Vehicle Tracking Based on Optical Flow and Shi-Tomasi Corner Detection Algorithm
1 Introduction
2 Vehicle Tracking Methods
3 Comparative Analysis
3.1 Object Detection Techniques
3.2 Vehicle Tracking Algorithms
4 Vehicle Tracking Algorithm
5 Implementation
5.1 Result of Pre-processing
5.2 Result of Vehicle Tracking
5.3 Results
6 Conclusion
References
Breast Cancer Classification Using a Novel Image Processing Pipeline and a Two-Stage Deep Learning Segmentation and Classification Approach
1 Introduction
1.1 Research Contribution
1.2 Paper Organization
2 Related Works
3 Proposed Methodology
3.1 About Datasets
3.2 Preprocessing Pipeline
3.3 Models
4 Results and Discussions
5 Conclusion
References
Analysis of Malignant and Non-malignant Lesion Detection Techniques for Human Skin Image
1 Introduction
1.1 Skin Lesion
1.2 Skin Lesion Types
1.3 Lesion Analysis Method
2 Review of Literature
3 Melanoma Diagnosis Techniques
3.1 ABCD-E Rule
3.2 Pattern Analysis
3.3 The 3-Point Checklist
3.4 Texture Assessment
3.5 Menzies Method
3.6 The Seven Point Checklist
4 Discussion
5 Conclusion and Future Scope
References
Implementation of Multi-input (MI) KY Boost Converter for Hybrid Renewable Energy System
1 Introduction
1.1 Review on Controllers
1.2 Survey on Controllers for Hybrid the Renewable Energy
2 Proposed System
2.1 Scope
2.2 Objective
2.3 Stability Analysis of Multi-input (MI) KY Boost Converters
3 PV/Wind Power System
3.1 Solar Energy System
3.2 Wind System
4 Design of Fuzzy-Based MPPT PV Panel and Wind System Control
5 Energy Management Using PV/Wind Power System
5.1 Battery Storage System
5.2 Energy Management
5.3 Intelligent Controller
6 Simulation Results
7 Results from Homer Software
8 Conclusion
References
Security and Privacy Issues
A Prevention Technique-Based Framework for Securing Healthcare Data
1 Introduction
1.1 Categories of Healthcare Data
1.2 Defining Blockchain
2 Literature Review
3 Healthcare Data-Related Vulnerabilities
4 Data Threats in Health Care
5 Prevention Techniques for Healthcare Data
6 Proposed Framework
6.1 Components of the Adaptive Framework
6.2 Adaptive Operational Framework
7 Strengths of Proposed Framework
8 Conclusion and Future Scope
References
An Enhanced Encryption Scheme for Cloud Security
1 Introduction
1.1 Introduction to Cloud Computing
2 Problem Statement and Proposed Method
2.1 Problem Formulation
3 Result Analysis
3.1 Parameters for Analyzing Performance
4 Conclusion
5 Future Scope
References
A Lightweight Authentication Scheme and Security Key Establishment for Internet of Medical Things
1 Introduction
1.1 Motivation and Problem Statement
1.2 Objectives
1.3 Organization of the Paper
2 Related Work
3 System Architecture
3.1 Protocol
4 Evaluations and Security Analysis
4.1 Performance and Comparative Analysis
5 Conclusions and Future Directions
References
Performance of Machine Learning Models on Crime Data
1 Introduction
1.1 Research Contribution
1.2 Organization of Paper
2 Background
3 Materials and Methodology
3.1 Dataset
3.2 Data Provenance
3.3 Libraries Applied
3.4 Data Preprocessing
3.5 Exploratory Data Analysis
3.6 Feature Scaling
3.7 Applied Machine Learning Models
3.8 Evaluation Parameters
4 Results
5 Conclusion
References
Improved Complexity in Localization of Copy-Move Forgery Using DWT
1 Introduction
2 Literature Review
3 Motivation
3.1 Discrete Wavelet Transform on Image
3.2 GLRLM Wavelet Texture Features
4 Proposed Method
5 Implementation
5.1 Dataset Description
5.2 Image Conversion to Gray Scale
5.3 Wavelet Transform
5.4 Dividing Sub-image LL into Overlapping Blocks
5.5 Wavelet GLRLM Feature Extraction from Image Blocks
5.6 Finding Similar Blocks
5.7 Final Result Processing
6 Performance Evaluation
7 Results
7.1 Jpeg Compression
7.2 Blurring
8 Comparison
9 Conclusion
References
Non-Fungible Tokens’ Marketplace: A Secured Blockchain-Based Decentralized Framework for Online Auction
1 Introduction
2 Literature Survey
3 Secured NFT Marketplace-Embedded Blockchain
4 Methodology Proposed with Non-Fungible Token
4.1 Auction Mechanism
5 Implementation
5.1 Minting NFT Smart Contract Functionality
6 Conclusion
References
Untangling Explainable AI in Applicative Domains: Taxonomy, Tools, and Open Challenges
1 Introduction
1.1 Contributions and Layout
2 Related Work
3 Explainable AI—Scope, Inputs, and Techniques
3.1 XAI—The Basic Preliminaries
3.2 Techniques of Explainable AI
3.3 Tools and Frameworks
4 XAI in Applicative Verticals: A Solution Taxonomy
4.1 Industry
4.2 IoT Monitoring
4.3 Health Care
4.4 Software
5 Open Issues and Future Directions
6 Conclusion and Future Works
References
AutoBots: A Botnet Intrusion Detection Scheme Using Deep Autoencoders
1 Introduction
1.1 Contributions and Layout
2 Related Work
3 AutoBots: The Proposed Botnet Detection Method
3.1 Training Process
3.2 Consistent Checking for Anomaly Detection
4 AutoBots: Performance Evaluation
4.1 Experimental Setup
4.2 Botnet Deployed
4.3 Attacks Analysis
4.4 Results and Discussion
5 Conclusions
References
Study on Fuel Cell Vehicle Braking System Selection and Simulation
1 Introduction
2 Historical Background of Fuel Cell
3 Structural Design in Fuel Cell Electric Vehicle
4 Key Component of Fuel Cell Electric Vehicle
4.1 Battery Pack Selection
4.2 Choice of Fuel Cell
4.3 Traction Motor’s Choice
5 Block Diagram of Vehicle on MATLAB/Simulink
6 Anti-lock Braking System
7 Components of ABS
8 Working of ABS
9 Regenerative Braking System
10 Conclusion
References
Deepfakes: A New Era of Misinformation
1 Introduction
1.1 Need and Importance
1.2 Deepfake’s Origins
1.3 Impact on the World
1.4 Why Aren’t They Illegal yet?
2 Process of Creating Deepfakes
2.1 Neural Networks
3 Approach
3.1 Step-by-Step Process
4 Results and Discussion
4.1 Spotting Deepfakes
5 Conclusion
References
Graph Neural Network-Based Anomaly Detection in Blockchain Network
1 Introduction
2 Related Work
3 Proposed Methodology
3.1 Graph-Based Techniques
3.2 Experimental Dataset
3.3 Background of Anomaly Detection
3.4 Graphic Neural Network
3.5 Proposed Method for Anomaly Detection
3.6 Classification
4 Experimental Analysis
5 Conclusion
References
Author Index
Recommend Papers
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- Sudeep Tanwar
- Slawomir T. Wierzchon
- Pradeep Kumar Singh
- Maria Ganzha
- Gregory Epiphaniou
- Similar Topics
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Lecture Notes in Networks and Systems 664
Sudeep Tanwar · Slawomir T. Wierzchon · Pradeep Kumar Singh · Maria Ganzha · Gregory Epiphaniou Editors
Proceedings of Fourth International Conference on Computing, Communications, and Cyber-Security IC4S 2022
Lecture Notes in Networks and Systems Volume 664
Series Editor Janusz Kacprzyk, Systems Research Institute, Polish Academy of Sciences, Warsaw, Poland Advisory Editors Fernando Gomide, Department of Computer Engineering and Automation—DCA, School of Electrical and Computer Engineering—FEEC, University of Campinas—UNICAMP, São Paulo, Brazil Okyay Kaynak, Department of Electrical and Electronic Engineering, Bogazici University, Istanbul, Türkiye Derong Liu, Department of Electrical and Computer Engineering, University of Illinois at Chicago, Chicago, USA Institute of Automation, Chinese Academy of Sciences, Beijing, China Witold Pedrycz, Department of Electrical and Computer Engineering, University of Alberta, Alberta, Canada Systems Research Institute, Polish Academy of Sciences, Warsaw, Poland Marios M. Polycarpou, Department of Electrical and Computer Engineering, KIOS Research Center for Intelligent Systems and Networks, University of Cyprus, Nicosia, Cyprus Imre J. Rudas, Óbuda University, Budapest, Hungary Jun Wang, Department of Computer Science, City University of Hong Kong, Kowloon, Hong Kong
The series “Lecture Notes in Networks and Systems” publishes the latest developments in Networks and Systems—quickly, informally and with high quality. Original research reported in proceedings and post-proceedings represents the core of LNNS. Volumes published in LNNS embrace all aspects and subfields of, as well as new challenges in, Networks and Systems. The series contains proceedings and edited volumes in systems and networks, spanning the areas of Cyber-Physical Systems, Autonomous Systems, Sensor Networks, Control Systems, Energy Systems, Automotive Systems, Biological Systems, Vehicular Networking and Connected Vehicles, Aerospace Systems, Automation, Manufacturing, Smart Grids, Nonlinear Systems, Power Systems, Robotics, Social Systems, Economic Systems and other. Of particular value to both the contributors and the readership are the short publication timeframe and the world-wide distribution and exposure which enable both a wide and rapid dissemination of research output. The series covers the theory, applications, and perspectives on the state of the art and future developments relevant to systems and networks, decision making, control, complex processes and related areas, as embedded in the fields of interdisciplinary and applied sciences, engineering, computer science, physics, economics, social, and life sciences, as well as the paradigms and methodologies behind them. Indexed by SCOPUS, INSPEC, WTI Frankfurt eG, zbMATH, SCImago. All books published in the series are submitted for consideration in Web of Science. For proposals from Asia please contact Aninda Bose ([email protected]).
Sudeep Tanwar · Slawomir T. Wierzchon · Pradeep Kumar Singh · Maria Ganzha · Gregory Epiphaniou Editors
Proceedings of Fourth International Conference on Computing, Communications, and Cyber-Security IC4S 2022
Editors Sudeep Tanwar Department of Computer Engineering, Institute of Technology Nirma University Ahmedabad, Gujarat, India Pradeep Kumar Singh Department of Computer Science and Engineering KIET Group of Institutions Ghaziabad, India
Slawomir T. Wierzchon Institute of Computer Science Polish Academy of Sciences Warsaw, Poland Maria Ganzha Faculty of Mathematics and Informatics Warsaw University of Technology Warsaw, Poland
Gregory Epiphaniou Department of Security Engineering University of Warwick Coventry, UK
ISSN 2367-3370 ISSN 2367-3389 (electronic) Lecture Notes in Networks and Systems ISBN 978-981-99-1478-4 ISBN 978-981-99-1479-1 (eBook) https://doi.org/10.1007/978-981-99-1479-1 © The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2023 This work is subject to copyright. All rights are solely and exclusively licensed by the Publisher, whether the whole or part of the material is concerned, specifically the rights of translation, reprinting, reuse of illustrations, recitation, broadcasting, reproduction on microfilms or in any other physical way, and transmission or information storage and retrieval, electronic adaptation, computer software, or by similar or dissimilar methodology now known or hereafter developed. The use of general descriptive names, registered names, trademarks, service marks, etc. in this publication does not imply, even in the absence of a specific statement, that such names are exempt from the relevant protective laws and regulations and therefore free for general use. The publisher, the authors, and the editors are safe to assume that the advice and information in this book are believed to be true and accurate at the date of publication. Neither the publisher nor the authors or the editors give a warranty, expressed or implied, with respect to the material contained herein or for any errors or omissions that may have been made. The publisher remains neutral with regard to jurisdictional claims in published maps and institutional affiliations. This Springer imprint is published by the registered company Springer Nature Singapore Pte Ltd. The registered company address is: 152 Beach Road, #21-01/04 Gateway East, Singapore 189721, Singapore
Preface
The 4th International Conference on Computing, Communications, and CyberSecurity (IC4S-2022) held on 16–17 December 2022 at Krishna Engineering College (KEC), Ghaziabad, India. Scholars, researchers, and professionals from academia and industry can meet and discuss developments and share ideas at the annual International Conference on Computing, Communication, and Cyber-Security (IC4S). Participants will have the rare chance to share their research results, engage in fruitful discussion, and learn from the experiences and insights of peers from all around the world. The primary goal of the IC4S is to host a forum where experts from academia, government, and industry can debate the most recent innovations, trends, and issues in the realms of information technology, communications, and security. Conferenceattendees are able to hear about the most recent findings in the field and make connections with like-minded professionals at the same time. The goal of the conference is to provide guests from a wide variety of backgrounds with a platform to discuss and exchange solutions to common problems. There were five different technical tracks presented at the conference, it includes: (i) communication and networks technologies, (ii) advanced computing technologies, (iii) data analytics and intelligent learning, (iv) latest electrical and electronics trend, and (v) security and privacy issues. The conference was hosted by the Engineering of Krishna Engineering College (KEC), Ghaziabad, India. The welcome address was given by Director, Joint Director of KEC Ghaziabad followed by the address of general chair of the conference. Inaugural speech was delivered by Prof. Sanjeev Kumar, Dean Academics, KEC Ghaziabad, India. Prof. Yashwant Singh, Head CS & IT, Central University of Jammu, India, delivered the opening keynote address, titled “IoVT: Internet of Vulnerable Things:Issues, Challenges and Prospects”. “Deep Learning for Healthcare Management” was the topic of Prof. Mahesh K. Kholekar of IIT Patna’s second keynote address. Professor Anand Nayyar from Duy Tan University in Vietnam spoke on “Autonomous Vehicles: Research Issues, Challenges, and Prospects” as third keynote. Final
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keynote address on “SDN for Intelligent Transportation System: Opportunities and Challenges” was given by Dr. Jitender Bhatia of Nirma University in India. The organizing committee is thankful to anonymous reviewers, TPC members, and session chairs who have extended their technical support at various stages. Our special mention to following members for their tireless support for the event in various roles: Prof. Sara Paiva, Dr. Pljonkin Anton, Prof. Marcello Tivoti, Prof. Wei-Chiang Hong, Prof. Pao Ann Hsuing, Prof. Mahendra Kumar, Dr. Ashutosh Mishra, Dr. Anupam Singh, Dr. Farkhana Muchtar, Dr. Nagesh Kumar, Dr. Hari Mohan Rai, Dr. Sushil Kumar Singh, Dr. Mohd Zuhair, Dr. Pronanya Bhattacharya, Dr. Anand Nayyar, Dr. Rakesh Saini, Dr. Sudhanshu Tyagi, Dr. Jitendra Bhatia, Dr. Yugal Kumar, Dr. Amit Sharma, Dr. Smita Agarwal, Dr. Ashutosh Sharma, Dr. Brahmah Hazela, Dr. Parita Oza, Dr. Rohit Tanwar, Dr. Sachin Kumar, Dr. Vipin Balyan, Dr. Chaman Verma, and Dr. Zoltan Illes. Knowledge University in Erbil, Iraq, Southern Federal University in Russia, WSG University in Bydgoszcz, Poland, and CSRL in India all provided academic support for the conference’s planning and execution. Many professionals from these organizations assisted with the conference’s technical aspects in various capacities, including the call for papers, the review, the compilation of the programme schedule, the technical sessions themselves, and other technical support activities. For their time and effort, the authors of these articles have our deepest gratitude. The technical programme committee’s help throughout the evaluation process is much appreciated by the event’s organizers. We appreciate the hard work that went into hosting this event and running the programmes over the course of two days. The organizers of IC4S-2022 would like to express their gratitude to the session chairs who presided over the many technical sessions and offered insightful feedback to the writers. During the conference’s paper presentation sessions, the session chairs have imparted their technical knowledge to the attendees. The organizing team is grateful to Springer, LNNS Series for their support. Ahmedabad, India Warsaw, Poland Ghaziabad, India Warsaw, Poland Coventry, UK December 2022
Sudeep Tanwar Slawomir T. Wierzchon Pradeep Kumar Singh Maria Ganzha Gregory Epiphaniou
Contents
Communication and Network Technologies Design and Implementation of an IoT-Based Indoor Hydroponics Farm with Automated Climate and Light Control . . . . . . . . . . . . . . . . . . . . Swati Jain and Mandeep Kaur Drone Ecosystem: Architecture for Configuring and Securing UAVs . . . . Harsh Sinha, Nikita Malik, and Menal Dahiya An Improved Neural Network-Based Routing Algorithm for Mobile Ad Hoc Networks . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Nongmeikapam Thoiba Singh, Raman Chadha, Simarjeet Kaur, and Amrita Chaudhary
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Energy Harvesting in Fifth-Generation Wireless Network: Upcoming Challenges and Future Directions . . . . . . . . . . . . . . . . . . . . . . . . . Neeraj Dwivedi, Sachin Kumar, Sudeep Tanwar, and Sudhanshu Tyagi
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Develop a Quantum Based Time Scheduling Algorithm for Digital Microfluidic Biochips . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . N. Nirmala and D. Gracia Nirmala Rani
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Revolution in Agriculture with the Aid of Internet of Things . . . . . . . . . . . Abhishek Tomar, Gaurav Gupta, Kritika Rana, and Surbhi Bhatia Supercontinuum Generation in Dispersion-Tailored Tetrachloroethylene Filled Photonic Crystal Fibers . . . . . . . . . . . . . . . . . . . Sandeep Vyas, Girraj Sharma, Sudarshan Kumar Jain, Rukhsar Zafar, and Anand Nayyar
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Early Detection of Covid-19 Using Wearable Sensors’ Data Enabled by Semantic Web Technologies . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 105 Nikita Malik and Sanjay Kumar Malik
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Cell Outage Detection in 5G Self-organizing Networks Based on FDA-HMM . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 119 Oluwaseyi Paul Babalola and Vipin Balyan IoT-Based Scalable Framework for Pollution Aware Route Recommendation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 131 Jitendra Bhatia, Radha Govani, Parth Kakadia, Yash Modi, Dhrumin Thakkar, Heta Bhayani, Meshwa Patel, Uttam Chauhan, and Abdulatif Alabdulatif Drone: A Systematic Review of UAV Technologies . . . . . . . . . . . . . . . . . . . . 147 Tanvi Gautam and Rahul Johari Reconfigurable Intelligent Surface-Enabled Energy-Efficient Cooperative Spectrum Sensing . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 159 Girraj Sharma, Sudarshan Kumar Jain, Sandeep Vyas, and Anand Nayyar Resource Sharing in Back Haul Satellite-Based NOMA Network . . . . . . . 169 Gunjan Gupta and Robert Van Zyl Advanced Computing Technologies A Review on Various Deepfakes’ Detection Methods . . . . . . . . . . . . . . . . . . 179 Mayank Pandey and Samayveer Singh Proposed Framework for Implementation of Biometrics in Banking KYC . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 193 Ayushi Malik, Shagun Gehlot, and Sonali Vyas Paddy Pro: A MobileNetV3-Based App to Identify Paddy Leaf Diseases . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 203 S. Asvitha, T. Dhivya, H. Dhivyasree, and R. M. Bhavadharini Cryptanalysis of RSEAP2 Authentication Protocol Based on RFID for Vehicular Cloud Computing . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 217 N. V. S. S. Prabhakar, Srinivas Jangirala, and Surendra Talari A Survey on Code-Mixed Sentiment Analysis Based on Hinglish Dataset . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 233 Rekha Baghel An Alternative to PHP for the Development of Web Applications: Java Server Pages Engine . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 243 Ahmed Altameem Novel Load Balancing Technique for Microservice-Based Fog Healthcare Environment . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 253 Swati Malik and Kamali Gupta
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Self-improved COOT Algorithm for Resource Allocation in Cloud Data Centers . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 267 Shubham Singh, Pawan Singh, and Sudeep Tanwar XGBoost-Based Prediction and Evaluation Model for Enchanting Subscribers in Industrial Sector . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 283 S. Pradeep, M. Kishore, G. Oviya, S. Poorani, and R. Anitha CleanO-Renewable Energy-Based Robotic Floor Cleaner . . . . . . . . . . . . . 297 Khushboo Jain, Shreya Shah, Smita Agrawal, Parita Oza, and Sudeep Tanwar Impact of “COVID-19 Pandemic” on Children Online Education: A Review and Bibliometric Analysis . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 313 Rhea Sawant, Shivali Amit Wagle, R. Harikrishnan, and P. Srideviponmalar Digital-Based Learning in Indian Government’s Higher Education: Initiatives and Insights . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 327 P. Srideviponmalar, Shivali Amit Wagle, R. Harikrishnan, and Rhea Sawant Autonomous Vehicles Adoption Classification for Future Mobility in UAE Using Machine Learning . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 343 Bakhit Bin Jarn, Rahat Iqbal, Shadi Atalla, Obada Alhabshneh, and Mohammed Ahmed An Augmented Reality Framework as a Solution to Enhance the Experience of Visiting a Museum . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 355 David Verde, Pedro Miguel Faria, Sara Paiva, and Luís Romero Hybrid Real-Time Implicit Feedback SOM-Based Movie Recommendation Systems . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 371 Saurabh Sharma and Harish Kumar Shakya Data Analytics and Intelligent Learning Automatic SMS Spam Filtering for Disaster Response Using Classification Algorithms . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 391 K. Nitalaksheswara Rao, Shanmuk Srinivas Amiripalli, Venkata Rao Rampay, and M. S. N. V. Jitendra Lung Cancer Diagnosis Using X-Ray and CT Scan Images Based on Machine Learning Approaches . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 399 Sunil Kumar and Harish Kumar Hybrid Machine Learning Algorithm for Prediction of Malaria . . . . . . . . 413 Yusuf Aliyu Adamu and Jaspreet Singh
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Yoga Pose Estimation Using Machine Learning . . . . . . . . . . . . . . . . . . . . . . . 425 Ishika Shah, Greeva Khant, Jitali Patel, Jigna Patel, and Rupal Kapdi COVID Detection from Chest X-Ray Images Using Deep Learning Model . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 443 Parth Nimbadkar, Dhruv Patel, Aayush Panchal, Jai Prakash Verma, and Jigna Patel Impact of Boosting Techniques in AI-Based Credit Card Fraud Detection Classifier . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 461 Misri Parikh, Niket Kothari, Karan Patel, Jai Prakash Verma, and Pronaya Bhattacharya Stock Price Prediction for Market Forecasting Using Machine Learning Analysis . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 477 Vivek Kumar Prasad, Darshan Savaliya, Sakshi Sanghavi, Vatsal Sakariya, Pronaya Bhattacharya, Jai Prakash Verma, Rushabh Shah, and Sudeep Tanwar Thyroid Carcinoma Prediction Using ACO and Machine Learning Techniques . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 493 Shanu Verma, Rashmi Popli, and Harish Kumar Cyclone Intensity Detection and Classification Using a Attention-Based 3D Deep Learning Model . . . . . . . . . . . . . . . . . . . . . . . . . 505 Y. Vahidhabanu, K. Karthick, R. Asokan, and S. Sreeji Towards Development of Data Architecture for Learning Analytics Projects Using Data Engineering Approach . . . . . . . . . . . . . . . . . . . . . . . . . . 517 Valerii Popovych and Martin Drlik A Real-Time Road Crash Prediction Model by Hybridizing Multiple Learning Classifiers . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 531 G. Arun, K. Anuguraju, A. Sangeetha, and K. Babu Machine Learning Assisted Intelligent Reflecting Surface MIMO Communication-Gateway for 6G—A Review . . . . . . . . . . . . . . . . . . . . . . . . . 543 Praveen Srivastava and Shelej Khera AI-Based Invoice Payment Date Prediction for B2B . . . . . . . . . . . . . . . . . . . 555 Mullapudi V. Ramanatha Subrahmanya Kiran, S. Suchitra, K. Arthi, and A. Shobanadevi Early Fault Detection for Rotating Machinery Onboard Ships Motor Using Fuzzy Logic and K-Means . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 567 Vandan Pandya, Smita Agrawal, Swati Jain, and Bharat Jayaswal Intellectual Movie Recommendation System Using Supervised Machine Learning Method . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 581 Priti Kumari and Vandana Dubey
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A Comparative Study on Different Machine Learning Algorithms for Predictive Analysis of Stock Prices . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 589 Aksh Gupta, Namrata Tadanki, Ninad Berry, Ramya Bardae, R. Harikrishnan, and Shivali Amit Wagle Opinion Mining-Assisted Intelligent Program Selection Employing Fuzzy SWARA Mechanism . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 599 Garima Srivastava, Vaishali Singh, and Sachin Kumar Deraining of Image Using UNet-Based Conditional Generative Adversarial Network . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 615 Samprit Bose, Deep R. Chavan, and Maheshkumar H. Kolekar Video Indexing and Retrieval Techniques: A Review . . . . . . . . . . . . . . . . . . 629 R. J. Poovaraghan and P. Prabhavathy A Robust Deep Learning Techniques for Alzheimer’s Prediction . . . . . . . 641 Jayesh Locharla, Haswanth Kolanuvada, Kona Venkata Sai Ashrith, and S. Suchitra Latest Electrical and Electronics Trends Steganography Methods for GIF Images: A Review . . . . . . . . . . . . . . . . . . . 657 Anjali Gupta, Lalit K. Awasthi, and Samayveer Singh Image Interpolation-Based Steganographic Techniques Under Spatial Domain: A Survey . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 671 Riya Punia and Aruna Malik A Comparative Review on Image Interpolation-Based Reversible Data Hiding . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 687 Raju Pratap Sharma and Aruna Malik Real-Time Face Mask Detection Using Convolution Neural Network and Computer Vision . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 701 V. Anusuya, K. Vignesh Saravanan, and V. Vishnu Praba A Video-Based System for Vehicle Tracking Based on Optical Flow and Shi-Tomasi Corner Detection Algorithm . . . . . . . . . . . . . . . . . . . . . . . . . 715 Nikesha Patel and Keyur N. Brahmbhatt Breast Cancer Classification Using a Novel Image Processing Pipeline and a Two-Stage Deep Learning Segmentation and Classification Approach . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 725 Dhruvin Kakadia, Het Shah, Parita Oza, Paawan Sharma, and Samir Patel Analysis of Malignant and Non-malignant Lesion Detection Techniques for Human Skin Image . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 741 Nikhil Singh, Sachin Kumar, and Shriram K. Vasudevan
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Implementation of Multi-input (MI) KY Boost Converter for Hybrid Renewable Energy System . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 757 M. Pushpavalli, R. Harikrishnan, P. Abirami, and P. Sivagami Security and Privacy Issues A Prevention Technique-Based Framework for Securing Healthcare Data . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 777 Harsimran Jit Singh, Shubh Gupta, and Sonali Vyas An Enhanced Encryption Scheme for Cloud Security . . . . . . . . . . . . . . . . . 789 Pratyaksha Ranawat, Mayank Patel, and Ajay Kumar Sharma A Lightweight Authentication Scheme and Security Key Establishment for Internet of Medical Things . . . . . . . . . . . . . . . . . . . . . . . . 797 Gousia Nissar, Riaz A. Khan, Saba Mushtaq, Sajaad A. Lone, and A. H. Moon Performance of Machine Learning Models on Crime Data . . . . . . . . . . . . . 811 Geetika Bhardwaj and R. K. Bawa Improved Complexity in Localization of Copy-Move Forgery Using DWT . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 825 Saba Mushtaq, Riaz A. Khan, Sajaad A. Lone, A. H. Moon, and Maroof Qadri Non-Fungible Tokens’ Marketplace: A Secured Blockchain-Based Decentralized Framework for Online Auction . . . . . . . . . . . . . . . . . . . . . . . . 841 Pooja Khanna, Sachin Kumar, Ritika Gauba, and Aditya Untangling Explainable AI in Applicative Domains: Taxonomy, Tools, and Open Challenges . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 857 Sachi Chaudhary, Pooja Joshi, Pronaya Bhattacharya, Vivek Kumar Prasad, Rushabh Shah, and Sudeep Tanwar AutoBots: A Botnet Intrusion Detection Scheme Using Deep Autoencoders . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 873 Ashwin Verma, Pronaya Bhattacharya, Vivek Kumar Prasad, Rajan Datt, and Sudeep Tanwar Study on Fuel Cell Vehicle Braking System Selection and Simulation . . . 887 Abhinav Bhardwaj, Raguel R. Marak, Babli Singh Gujar, Yash Anil Dandekar, and Harpreet Singh Bedi Deepfakes: A New Era of Misinformation . . . . . . . . . . . . . . . . . . . . . . . . . . . . 897 Rushan Khan, Bramah Hazela, Shikha Singh, and Pallavi Asthana
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Graph Neural Network-Based Anomaly Detection in Blockchain Network . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 909 Amit Sharma, Pradeep Kumar Singh, Elizaveta Podoplelova, Vadim Gavrilenko, Alexey Tselykh, and Alexander Bozhenyuk Author Index . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 927
Editors and Contributors
About the Editors Dr. Sudeep Tanwar is a professor in the Computer Engineering Department at the Institute of Technology of Nirma University, Ahmedabad, India. He received his Ph.D. in 2016 from the Faculty of Engineering and Technology, Mewar University, India, with a specialization in wireless sensor networks. His current interests include routing issues in WSN, integration of sensors in the cloud, computational aspects of smart grids, and blockchain technology. He has authored or co-authored more than 150+ technical research papers published in leading peer-reviewed international journals and international conferences from the IEEE, Elsevier, Springer, and John Wiley and has authored five books. He is a recipient of the Best Research Paper awards from IEEE GLOBECOM-2018 and Springer ICRIC-2019. He is a TPC member and reviewer of many international conferences across the globe. He is an associate editor of the Security and Privacy Journal and is a member of the IAENG, ISTE, and CSTA. He has Google Scholar citations 8405, H-index 52 and i-10 index 140. Prof. Slawomir T. Wierzchon received M.Sc. and Ph.D. degrees in Computer Science from Technical University of Warsaw, Poland. He holds Habilitation (D.Sc.) in Uncertainty Management from Polish Academy of Sciences. In 2003, he received the title of Professor from the President of Poland. Currently, he is a full professor at the Institute of Computer Science of Polish Academy of Sciences. His research interests include computational intelligence, uncertainty management, information retrieval, machine learning, and data mining. He is an author/co-author of over 100 peer-reviewed papers in international journals and international conferences. He published, as author/co-author, 11 monographs from the field of Machine Learning. In the period 2000–2013, he co-organized 13 international conferences on intelligent information systems. Co-authored proceedings from these conferences were published by Springer. He co-edited two volumes of proceedings of the international
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conference on Computer Information Systems and Industrial Management, and he has served as a guest co-editor of three special issues of Information and Control journal. Currently, he is a member of the editorial board for some international journals, as well as member of many program committees for international conferences. He cooperated with medical centers in the area of statistical data analysis and knowledge discovery in databases. For more information, visit his homepage. Dr. Pradeep Kumar Singh is currently working as a professor and head in the Department of Computer Science at KIET Group of Institutions, Ghaziabad, India. He is an associate editor of the IJISMD, [IJISMD is indexed by Scopus and Web of Science], IJAEC, IGI Global USA, SPY, Wiley, and IJISC from Romania. He is recently appointed as a section editor, Discover IoT, Springer Journal. He has published nearly 150 research papers. He has received three sponsored research project grant worth Rs 25 Lakhs. He has edited a total of 16 books from Springer and Elsevier and also edited several special issues for SCI and SCIE Journals from Elsevier and IGI Global. He has Google Scholar citations 1850, H-index 22 and i-10 index 50. Dr. Maria Ganzha is an associate professor in the Faculty of Mathematics and Information Science. She has an M.S. degree and a Ph.D. degree in Mathematics from the Moscow State University, Russia, and a Doctor of Science degree (in Computer Science) from the Polish Academy of Sciences. Maria has published more than 200 research papers, is on editorial boards of 6 journals and a book series, and was invited to program committees of more than 150 conferences. She is also the principal investigator, of the SRIPAS team, in the INTER-IoT project. Here, her team is responsible for use of semantic technologies in the context of interoperability of IoT platforms. She has 1594 Google citations, H-index 19 and i-10 index 58 in her account. Her area of interest includes computational intelligence, distributed systems, agent-based computing, and semantic data processing. Dr. Gregory Epiphaniou currently holds a position as an associate professor of security engineering at the University of Warwick. His role involves bid support, applied research, and publications. Part of his current research activities is formalized around a research group in wireless communications with the main focus on cryptokey generation, exploiting the time-domain physical attributes of V-V channels. He led and contributed to several research projects funded by EPSRC, IUK, and local authorities totaling over £8M. He is also the main inventor of a patented-pending technology on a distributed ledger system (GB2576160A/US200042497A1). He was previously holding a position as a reader in Cybersecurity and acted as deputy director of the Wolverhampton Cybersecurity Research Institute (WCRI). He has taught in many universities both nationally and internationally in a variety of areas related to proactive network defense with over 120 international publications in journals and conference proceedings and author in several books and chapters. He holds several industry certifications in Information Security and worked with several government agencies, including the UK MoD, in cybersecurity-related projects. He currently
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holds a subject matter expert panel position at the Chartered Institute for Securities and Investments. He acts as a technical committee member for several scientific conferences in information and network security. He serves as a key member in the development of WS5 for the formation of the UK Cybersecurity Council.
Contributors P. Abirami B. S. Abdur Rahman Crescent Institute of Science and Technology, Chennai, India Yusuf Aliyu Adamu Department of Computer Science and Engineering, GD Goenka University, Sohna, India Aditya Amity University Uttar Pradesh, Lucknow, India Smita Agrawal Department of Computer Science and Engineering, Nirma University, Ahmedabad, India Mohammed Ahmed Coventry University, Coventry, UK Abdulatif Alabdulatif Department of Computer Science, College of Computer, Qassim University, Buraydah, Saudi Arabia Obada Alhabshneh Mutah University, Mutah, Jordan Ahmed Altameem King Saud University, Riyadh, Kingdom of Saudi Arabia Shanmuk Srinivas Amiripalli Department of Computer Science and Engineering, GITAM School of Technology, GITAM (Deemed to be University), Visakhapatnam, Andhra Pradesh, India R. Anitha Department of CSE, Sri Venkateswara College of Engineering, Chennai, India K. Anuguraju Department of Computer Science and Engineering, Kongunadu College of Engineering and Technology (Autonomous), Trichy, India V. Anusuya Department of Computer Science and Engineering, Ramco Institute of Technology, Rajapalayam, India K. Arthi Department of Data Science and Business Systems, SRM Institute of Science and Technology, Kattankulathur, Chengalpattu, Tamil Nadu, India G. Arun Department of Computer Science and Engineering, Kongunadu College of Engineering and Technology (Autonomous), Trichy, India Kona Venkata Sai Ashrith Department of Data Science and Business Systems, SRM Institute of Science and Technology, Kattankulathur, Chengalpattu Dist, Tamil Nadu, India
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Editors and Contributors
R. Asokan Department of Electronics and Communication Engineering, Kongunadu College of Engineering and Technology (Autonomous), Trichy, India Pallavi Asthana Department of Electronics and Communication Engineering, Amity School of Engineering and Technology Lucknow, Amity University, Lucknow, Uttar Pradesh, India S. Asvitha Department of CSE, Easwari Engineering College, Chennai, India Shadi Atalla University of Dubai, Dubai, UAE Lalit K. Awasthi Department of Computer Science and Engineering, National Institute of Technology, Srinagar, Uttarakhand, India Oluwaseyi Paul Babalola Department of Electrical, Electronics, and Computer Engineering, Cape Peninsula University of Technology, Bellville, South Africa K. Babu Department of Computer Science and Engineering, Sathyabama Institute of Science and Technology, Chennai, India Rekha Baghel Indira Gandhi Delhi Technical University for Women, New Delhi, India; Ajay Kumar Garg Engineering College, Ghaziabad, Uttar Pradesh, India Vipin Balyan Department of Electrical, Electronics, and Computer Engineering, Cape Peninsula University of Technology, Bellville, South Africa Ramya Bardae Symbiosis Institute of Technology, Pune Campus, Symbiosis International (Deemed University), Pune, India R. K. Bawa Punjabi University, Patiala, Punjab, India Harpreet Singh Bedi School of Electronics and Electrical Engineering, Lovely Professional University, Phagwara, Punjab, India Ninad Berry Symbiosis Institute of Technology, Pune Campus, Symbiosis International (Deemed University), Pune, India Abhinav Bhardwaj School of Electronics and Electrical Engineering, Lovely Professional University, Phagwara, Punjab, India Geetika Bhardwaj Punjabi University, Patiala, Punjab, India Jitendra Bhatia Computer Science and Engineering Department, Institute of Technology, Nirma University, Ahmedabad, Gujarat, India Surbhi Bhatia Department of Information Systems, College of Computer Science and Information Technology, King Faisal University, Al Hofuf, Saudi Arabia Pronaya Bhattacharya Department of Computer Science and Engineering, Institute of Technology, Nirma University, Ahmedabad, Gujarat, India; Department of Computer Science and Engineering, Amity School of Engineering and Technology, Amity University, Kolkata, West Bengal, India
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R. M. Bhavadharini SCOPE, Vellore Institute of Technology, Chennai, India Heta Bhayani Computer Engineering Department, Vishwakarma Government Engineering College, Ahmedabad, India Samprit Bose Indian Institute of Technology Patna, Bihar, India Alexander Bozhenyuk Southern Federal University, Taganrog, Russia Keyur N. Brahmbhatt Birla Vishwakarma Mahavidyalaya, Anand, Gujarat, India Raman Chadha Department of Computer Science and Engineering, Chandigarh University, Mohali, Punjab, India Amrita Chaudhary Department of Computer Science and Engineering, Chandigarh University, Mohali, Punjab, India Sachi Chaudhary Department of Computer Science and Engineering, Institute of Technology, Nirma University, Ahmedabad, Gujarat, India Uttam Chauhan Computer Engineering Department, Vishwakarma Government Engineering College, Ahmedabad, India Deep R. Chavan PDPM-IIITDM, Jabalpur, India Menal Dahiya Department of Computer Science, Maharaja Surajmal Institute, Janakpuri, New Delhi, India Yash Anil Dandekar School of Electronics and Electrical Engineering, Lovely Professional University, Phagwara, Punjab, India Rajan Datt Department of Computer Science and Engineering, Institute of Technology, Nirma University, Ahmedabad, Gujarat, India T. Dhivya Department of CSE, Easwari Engineering College, Chennai, India H. Dhivyasree Department of CSE, Easwari Engineering College, Chennai, India Martin Drlik Constantine the Philosopher University in Nitra, Nitra, Slovakia Vandana Dubey Ashoka Institute of Technology and Management, Varanasi, Uttar Pradesh, India Neeraj Dwivedi Amity University, Lucknow Campus, Lucknow, India Pedro Miguel Faria ADiT-LAB, Instituto Politécnico de Viana do Castelo, Viana do castelo, Portugal Ritika Gauba Zenith Ph.D. Training and Consultancy, Faridabad, Haryana, India Tanvi Gautam SWINGER (Security, Wireless, IoT Network Group of Engineering and Research), USAR (University School of Automation and Robotics), GGS Indraprastha University, Delhi, India; IMS Engineering College, AKTU, Ghaziabad, Uttar Pradesh, India
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Vadim Gavrilenko Institute of Computer Technologies and Informational Security, Southern Federal University, Rostov-on-Don, Russia Shagun Gehlot UPES University, Dehradun, India Radha Govani Computer Engineering Department, Vishwakarma Government Engineering College, Ahmedabad, India D. Gracia Nirmala Rani Department of Electronics and Communication Engineering, Thiagarajar College of Engineering, Madurai, Tamilnadu, India Babli Singh Gujar School of Electronics and Electrical Engineering, Lovely Professional University, Phagwara, Punjab, India Aksh Gupta Symbiosis Institute of Technology, Pune Campus, Symbiosis International (Deemed University), Pune, India Anjali Gupta Department of Computer Science and Engineering, Dr. B R Ambedkar National Institute of Technology, Jalandhar, Punjab, India Gaurav Gupta Yogananda School of Artificial Intelligence, Computers and Data Sciences, Shoolini University, Solan, India Gunjan Gupta Department of Electrical, Electronics and Computer Engineering, French South African Institute of Technology, Cape Peninsula University of Technology, Cape Town, South Africa Kamali Gupta Chitkara University Institute of Engineering and Technology, Chitkara University, Punjab, India Shubh Gupta UPES University, Dehradun, India R. Harikrishnan Symbiosis Institute of Technology, Pune Campus, Symbiosis International (Deemed University), Pune, India Bramah Hazela Department of Computer Science and Engineering, Amity School of Engineering and Technology Lucknow, Amity University, Lucknow, Uttar Pradesh, India Rahat Iqbal University of Dubai, Dubai, UAE Khushboo Jain Department of Computer Science and Engineering, Nirma University, Ahmedabad, India Sudarshan Kumar Jain Department of ECE, Jaipur Engineering College and Research Centre, Jaipur, India Swati Jain Faculty of CSE Department, Institute of Technology, Nirma University, Ahmedabad, India; Department of Computer Science and Engineering, School of Engineering and Technology, Sharda University, Greater Noida, India
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Srinivas Jangirala Jindal Global Business School, O. P. Jindal Global University, Haryana, India Bakhit Bin Jarn University of Dubai, Dubai, UAE Bharat Jayaswal Faculty of CSE Department, Institute of Technology, Nirma University, Ahmedabad, India M. S. N. V. Jitendra Department of Computer Science and Engineering, GITAM School of Technology, GITAM (Deemed to be University), Visakhapatnam, Andhra Pradesh, India Rahul Johari SWINGER (Security, Wireless, IoT Network Group of Engineering and Research), USAR (University School of Automation and Robotics), GGS Indraprastha University, Delhi, India Pooja Joshi Department of Computer Science and Engineering, Institute of Technology, Nirma University, Ahmedabad, Gujarat, India Dhruvin Kakadia Nirma University, Ahmedabad, Gujarat, India Parth Kakadia Computer Engineering Department, Vishwakarma Government Engineering College, Ahmedabad, India Rupal Kapdi Institute of Technology, Nirma University, Ahmedabad, India K. Karthick Department of Computer Science and Engineering, Kongunadu College of Engineering and Technology (Autonomous), Trichy, India Mandeep Kaur Department of Computer Science and Engineering, School of Engineering and Technology, Sharda University, Greater Noida, India Simarjeet Kaur Department of Computer Science and Engineering, Chandigarh University, Mohali, Punjab, India Riaz A. Khan Depaertment of Computer Science and Engineering, Islamic University of Science and Technology, Awantipora Kashmir, India Rushan Khan Department of Computer Science and Engineering, Amity School of Engineering and Technology Lucknow, Amity University, Lucknow, Uttar Pradesh, India Pooja Khanna Amity University Uttar Pradesh, Lucknow, India Greeva Khant Institute of Technology, Nirma University, Ahmedabad, India Shelej Khera School of Electronics and Electrical Engineering, Lovely Professional University, Phagwara, Punjab, India M. Kishore Department of ECE, Sri Venkateswara College of Engineering, Chennai, India
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Haswanth Kolanuvada Department of Data Science and Business Systems, SRM Institute of Science and Technology, Kattankulathur, Chengalpattu Dist, Tamil Nadu, India Maheshkumar H. Kolekar Indian Institute of Technology Patna, Bihar, India Niket Kothari Institute of Technology, Nirma University, Ahmadabad, India Harish Kumar Department of Computer Engineering, J.C. Bose University of Science and Technology, YMCA, Faridabad, India Sachin Kumar Amity University, Lucknow Campus, Lucknow, India Sunil Kumar Department of Computer Engineering, J.C. Bose University of Science and Technology, YMCA, Faridabad, India; Department of Information Technology, School of Engineering and Technology (UIET), CSJM University, Kanpur, India Priti Kumari Ashoka Institute of Technology and Management, Varanasi, Uttar Pradesh, India Jayesh Locharla Department of Data Science and Business Systems, SRM Institute of Science and Technology, Kattankulathur, Chengalpattu Dist, Tamil Nadu, India Sajaad A. Lone Depaertment of Computer Science and Engineering, Islamic University of Science and Technology, Awantipora Kashmir, India Aruna Malik Department of Computer Science and Engineering, Dr. B R Ambedkar National Institute of Technology Jalandhar, Punjab, India Ayushi Malik UPES University, Dehradun, India Nikita Malik USIC&T, GGSIP University, Dwarka, Delhi, India; Department of Computer Science, Maharaja Surajmal Institute, Janakpuri, New Delhi, India Sanjay Kumar Malik USIC&T, GGSIP University, Dwarka, Delhi, India Swati Malik Chitkara University Institute of Engineering and Technology, Chitkara University, Punjab, India Raguel R. Marak School of Electronics and Electrical Engineering, Lovely Professional University, Phagwara, Punjab, India Yash Modi Computer Engineering Department, Vishwakarma Government Engineering College, Ahmedabad, India A. H. Moon Depaertment of Computer Science and Engineering, Islamic University of Science and Technology, Kashmir, India; Department of Computer Science Engineering, IUST, Awantipora Kashmir, India Saba Mushtaq Directorate of IT and SS, University Of Kashmir, Srinagar, Kashmir, India
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Anand Nayyar Graduate School, Faculty of Information Technology, Duy Tan University, Da Nang, Vietnam Parth Nimbadkar CSE Department, Institute of Technology, Nirma University, Ahmedabad, India N. Nirmala Department of Electronics and Communication Engineering, Thiagarajar College of Engineering, Madurai, Tamilnadu, India Gousia Nissar Depaertment of Computer Science and Engineering, Islamic University of Science and Technology, Kashmir, India G. Oviya Department of ECE, Sri Venkateswara College of Engineering, Chennai, India Parita Oza Department of Computer Science and Engineering, Nirma University, Ahmedabad, Gujarat, India Sara Paiva ADiT-LAB, Instituto Politécnico de Viana do Castelo, Viana do castelo, Portugal Aayush Panchal CSE Department, Institute of Technology, Nirma University, Ahmedabad, India Mayank Pandey Department of Computer Science and Engineering, Dr. B. R. Ambedkar National Institute of Technology, Jalandhar, Punjab, India Vandan Pandya Faculty of CSE Department, Institute of Technology, Nirma University, Ahmedabad, India Misri Parikh Institute of Technology, Nirma University, Ahmadabad, India Dhruv Patel CSE Department, Institute of Technology, Nirma University, Ahmedabad, India Jigna Patel CSE Department, Institute of Technology, Nirma University, Ahmedabad, India Jitali Patel Institute of Technology, Nirma University, Ahmedabad, India Karan Patel Institute of Technology, Nirma University, Ahmadabad, India Mayank Patel Geetenjali Institute of Technical Studies, Udaipur, Rajasthan, India Meshwa Patel Computer Engineering Department, Vishwakarma Government Engineering College, Ahmedabad, India Nikesha Patel Gujarat Technological University, Chandkheda, Ahmedabad, India Samir Patel Pandit Deendayal Energy University, Gandhinagar, Gujarat, India Elizaveta Podoplelova Institute of Computer Technologies and Informational Security, Southern Federal University, Rostov-on-Don, Russia
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S. Poorani Department of CSE, Sri Venkateswara College of Engineering, Chennai, India R. J. Poovaraghan School of Computer Science and Engineering, Vellore Institute of Technology, Vellore, Tamil Nadu, India Rashmi Popli J.C. Bose University of Science and Technology, Faridabad, India Valerii Popovych Constantine the Philosopher University in Nitra, Nitra, Slovakia N. V. S. S. Prabhakar Department of Mathematics GIS, GITAM Deemed to be University, Visakhapatnam, Andhra Pradesh, India P. Prabhavathy School of Information Technology and Engg, Vellore Institute of Technology, Vellore, Tamil Nadu, India S. Pradeep Department of ECE, Sri Venkateswara College of Engineering, Chennai, India Vivek Kumar Prasad Department of Computer Science and Engineering, Institute of Technology, Nirma University, Ahmedabad, Gujarat, India Riya Punia Department of Computer Science and Engineering, Dr. B R Ambedkar National Institute of Technology Jalandhar, Punjab, India M. Pushpavalli Sathyabama Institute of Science and Technology, Chennai, India Maroof Qadri Directorate of IT and SS, University Of Kashmir, Srinagar, India Mullapudi V. Ramanatha Subrahmanya Kiran Department of Data Science and Business Systems, SRM Institute of Science and Technology, Kattankulathur, Chengalpattu, Tamil Nadu, India Venkata Rao Rampay Department of Computer Science and Engineering, Wollega University, Nekemte, Ethiopia Kritika Rana Yogananda School of Artificial Intelligence, Computers and Data Sciences, Shoolini University, Solan, India Pratyaksha Ranawat Geetenjali Institute of Technical Studies, Udaipur, Rajasthan, India K. Nitalaksheswara Rao Department of Computer Science and Engineering, GITAM School of Technology, GITAM (Deemed to be University), Visakhapatnam, Andhra Pradesh, India Luís Romero ADiT-LAB, Instituto Politécnico de Viana do Castelo, Viana do castelo, Portugal Vatsal Sakariya Institute of Technology, Nirma University, Ahmedabad, Gujarat, India A. Sangeetha Department of Computer Science and Engineering, Gnanamani College of Technology, Pachal, Namakkal, India
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Sakshi Sanghavi Institute of Technology, Nirma University, Ahmedabad, Gujarat, India Darshan Savaliya Institute of Technology, Nirma University, Ahmedabad, Gujarat, India Rhea Sawant Symbiosis Institute of Technology, Pune Campus, Symbiosis International (Deemed University), Pune, India Het Shah Nirma University, Ahmedabad, Gujarat, India Ishika Shah Institute of Technology, Nirma University, Ahmedabad, India Rushabh Shah Department of Computer Science and Engineering, Institute of Technology, Nirma University, Ahmedabad, Gujarat, India Shreya Shah Department of Computer Science and Engineering, Nirma University, Ahmedabad, India Harish Kumar Shakya Assistant Professor, Department of Computer Science and Engineering, Amity School of Engineering and Technology (ASET), Amity University, Gwalior, India Ajay Kumar Sharma Geetenjali Institute of Technical Studies, Udaipur, Rajasthan, India Amit Sharma Institute of Computer Technologies and Informational Security, Southern Federal University, Rostov-on-Don, Russia; Chitkara University Institute of Engineering and Technology, Chitkara University, Rajpura, Punjab, India Girraj Sharma Department of ECE, Jaipur Engineering College and Research Centre, Jaipur, India Paawan Sharma Pandit Deendayal Energy University, Gandhinagar, Gujarat, India Raju Pratap Sharma Department of Computer Science and Engineering, Dr. BR Ambedkar National Institute of Technology Jalandhar, Punjab, India Saurabh Sharma Research Scholar, Department of Computer Science and Engineering, Amity School of Engineering and Technology (ASET), Amity University, Gwalior, India A. Shobanadevi Department of Data Science and Business Systems, SRM Institute of Science and Technology, Kattankulathur, Chengalpattu, Tamil Nadu, India Harsimran Jit Singh UPES University, Dehradun, India Jaspreet Singh Department of Computer Science and Engineering, GD Goenka University, Sohna, India Nikhil Singh Amity University Lucknow Campus, Lucknow, India
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Nongmeikapam Thoiba Singh Department of Computer Science and Engineering, Chandigarh University, Mohali, Punjab, India Pawan Singh Department of Computer Science and Engineering, Amity School of Engineering and Technology, Amity University, Lucknow, Uttar Pradesh, India Pradeep Kumar Singh Narsee Monjee Institute of Management (NMIMS), STME, Chandigarh, India
Studies
Samayveer Singh Department of Computer Science and Engineering, Dr. B. R. Ambedkar National Institute of Technology, Jalandhar, Punjab, India Shikha Singh Department of Computer Science and Engineering, Amity School of Engineering and Technology Lucknow, Amity University, Lucknow, Uttar Pradesh, India Shubham Singh Department of Computer Science and Engineering, Amity School of Engineering and Technology, Amity University, Lucknow, Uttar Pradesh, India Vaishali Singh Maharishi University of Information Technology, Lucknow, India Harsh Sinha Department of Computer Science, Maharaja Surajmal Institute, Janakpuri, New Delhi, India P. Sivagami Sathyabama Institute of Science and Technology, Chennai, India S. Sreeji Department of Computer Science and Engineering, Sathyabama Institute of Science and Technology, Semmancheri, Chennai, India P. Srideviponmalar Department of Computational Intelligence, School of Computing, Faculty of Engineering Technology, SRM Institute of Science and Technology, Chennai, India Garima Srivastava Maharishi University of Information Technology, Lucknow, India; Amity University, Lucknow Campus, Lucknow, India Praveen Srivastava School of Electronics and Electrical Engineering, Lovely Professional University, Phagwara, Punjab, India; Department of Electronics and Communication Engineering, Pranveer Singh Institute of Technology, Kanpur, India S. Suchitra Department of Data Science and Business Systems, SRM Institute of Science and Technology, Kattankulathur, Chengalpattu, Tamil Nadu, India Namrata Tadanki Symbiosis Institute of Technology, Pune Campus, Symbiosis International (Deemed University), Pune, India Surendra Talari Department of Mathematics GIS, GITAM Deemed to be University, Visakhapatnam, Andhra Pradesh, India Sudeep Tanwar Department of Computer Science and Engineering, Institute of Technology, Nirma University, Ahmedabad, Gujarat, India;
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Department of Computer Science and Engineering, Nirma University, Ahmedabad, India Dhrumin Thakkar Computer Engineering Department, Vishwakarma Government Engineering College, Ahmedabad, India Abhishek Tomar Yogananda School of Artificial Intelligence, Computers and Data Sciences, Shoolini University, Solan, India Alexey Tselykh Department of Information and Analytical Security Systems, Southern Federal University, Rostov-On-Don, Russia Sudhanshu Tyagi Thapar Institute of Engineering and Technology, Deemed to be University, Patiala, Punjab, India Y. Vahidhabanu Department of Computer Science and Engineering, Kongunadu College of Engineering and Technology (Autonomous), Trichy, India Robert Van Zyl Department of Electrical, Electronics and Computer Engineering, French South African Institute of Technology, Cape Peninsula University of Technology, Cape Town, South Africa Shriram K. Vasudevan Evangelist Intel Software Innovator, Lucknow, India David Verde ADiT-LAB, Instituto Politécnico de Viana do Castelo, Viana do castelo, Portugal Ashwin Verma Department of Computer Science and Engineering, Institute of Technology, Nirma University, Ahmedabad, Gujarat, India Jai Prakash Verma Institute of Technology, Nirma University, Ahmadabad, Gujarat, India; CSE Department, Institute of Technology, Nirma University, Ahmedabad, India Shanu Verma J.C. Bose University of Science and Technology, Faridabad, India K. Vignesh Saravanan Department of Computer Science and Engineering, Ramco Institute of Technology, Rajapalayam, India V. Vishnu Praba Department of Computer Science and Engineering, Ramco Institute of Technology, Rajapalayam, India Sandeep Vyas Department of ECE, Jaipur Engineering College and Research Centre, Jaipur, India Sonali Vyas UPES University, Dehradun, India Shivali Amit Wagle Symbiosis Institute of Technology, Pune Campus, Symbiosis International (Deemed University), Pune, India Rukhsar Zafar Swami Keshvanand Institute of Technology Management and Gramothan, Jaipur, India
Communication and Network Technologies
Design and Implementation of an IoT-Based Indoor Hydroponics Farm with Automated Climate and Light Control Swati Jain and Mandeep Kaur
Abstract With the boom of industrialization and the escalation of world population, there is a significant decline in the land suitable for farming and an increase in demand for food. Hydroponics, a branch of agriculture, facilitates the growth of plants in water without the use of soil. This offers a lifeline of sorts by making vertical farming possible. Hydroponics gives us the freedom to wholly control the parameters that affect plant growth, and if done correctly, it can be beneficial both commercially and environmentally. Manual monitoring of all the variables of plant growth is difficult and can lead to growth failures. This paper proposes how the Internet of Things (IoT), a revolutionary technology can be integrated with hydroponics to automate the process of climate monitoring and control. A practical model is implemented in this paper where IoT sensors are used to control the climate conditions and ambient lights of the hydroponic farm. Sensors monitor the climate and light conditions throughout the day and automatically maintain suitable growth conditions. Keywords Internet of things · IoT · Smart farming · Precision agriculture · Indoor farms · Hydroponics
1 Introduction Hydroponics, an agricultural branch that has plants growing in aqueous solutions and without any need for soil is based on the technique of precision agriculture (PA) [1]. PA is a farming technique that makes use of information technology to ensure that the crops get the right amount of nutrition and environmental growth conditions for optimal health and productivity. This is done by accessing real-time data of the farm conditions, such as air quality, climate conditions including humidity and temperature, and light intensity through the use of IoT sensors on the farms. The data coming from sensors is then used to control the ambient conditions through decision-making S. Jain (B) · M. Kaur Department of Computer Science and Engineering, School of Engineering and Technology, Sharda University, Greater Noida, India e-mail: [email protected] © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2023 S. Tanwar et al. (eds.), Proceedings of Fourth International Conference on Computing, Communications, and Cyber-Security, Lecture Notes in Networks and Systems 664, https://doi.org/10.1007/978-981-99-1479-1_1
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algorithms. For example, hydroponic farms require 60–70% humidity during the germination stage of plants, and the sensors constantly monitor the current humidity level in the farm, and when the level reaches below 60%, it automatically turns on the humidifier attached to the farm. This is how IoT can be integrated into hydroponics for automated climate and light control. In this paper, we propose and implement an IoT system that unceasingly monitors and maintains all the environmental parameters and light conditions necessary for the growth of plants in indoor hydroponic farms [2, 3]. As a whole, the system process works as follows: Create the IoT setup of sensors, actuators, and a microcontroller in the indoor farm and place the germinated plant in the hydroponic system. Once installed, this IoT-based climate control model will monitor and maintain the temperature, humidity, and ambient light levels of the hydroponics farm continuously in their optimal range resulting in faster and healthier growth of the plants. Classically, hydroponics and precision agriculture need support and interaction from humans for parameter maintenance. The intent of this system is to create an IoT-enabled indoor smart farm that is automated completely and works virtually without the need for any human intervention. The said IoT design was implemented using NodeMCU as a microcontroller, MQTT broker, sensors for parameter sensing, Firebase as the cloud platform for receiving sensor data, and a mobile application to operate the IoT system remotely. A literature study of the previously implemented hydroponic farms with IoT automation has been presented in Sect. 2. Section 3 titled proposed system design methodology discusses the proposed and implemented system architecture, the decision-making algorithm used for IoT automation for weather and light control, and the mobile application developed to support remote access to the farm at all times. In the next section, the results of the implemented system are presented in the form of IoT setup, indoor farm setup, and graphs to highlight the average ambient weather conditions of the indoor farm maintained automatically for the period. In the concluding section, the benefit and future scope of this study is discussed alongside how this study helps in solving the problems of food crisis due to urbanization and population explosion.
2 Literature Review Kulkarni and Surwade [4] in their work titled “The future of farming through the IoT perspective” identified the lack of real-time information for farming. A model was proposed to convert unstructured information collected through IoT sensors into structured information, saving this information on the cloud and using data mining algorithms to produce useful information important to predict good farming conditions for the future. Dagar et al. [5] proposed a model for a poly house implementation paired with a motion detection sensor of IoT. This sensor can recognize any unusual movement on the field and then informs the server about it. This is used to keep animals away from the farm in the absence of human supervision. Perwiratama et al. [6] in their work proposed a hydroponic farm with automated climate control and nutrient manipulation system through IoT sensors. A greenhouse system is proposed
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where the inside environment will be controlled, and based on the measurements from multiple sensors, gates to the nutrient solution would be opened or closed and the pump would operate. The algorithm for nutrient manipulation and climate control was presented in the paper. Ruengittinun et al. [7] in their work proposed a Hydroponic Farming Ecosystem (HFE) with IoT-based weather monitoring and nutrient management. HFE is supported by an android application to control the IoT devices in HFE, and it has a feature of alarming the user when the farm is in any abnormal situation. Lakshmanan et al. [8] in their work implemented IoT functionality in an existing hydroponic farm where ambient weather and light conditions were monitored and sent to the cloud server NodeRed which is a free IoT server. A mobile app or a web app was proposed as a user interface to monitor farm conditions. Ani and Gopalakrishnan [9], Jaiswal et al. [11], Kaburuan et al. [12] and Dholu et al. [13] in their respective research work proposed monitoring of temperature and humidity conditions of the farm and presenting it to the user through the mobile app. Semi-automated farms were proposed since ambient light conditions were not monitored through sensors and to control the farm conditions user intervention is needed. Chowdhury et al. [10] in their work designed an IoT-based automated indoor vertical hydroponic farm in Qatar. The system mainly automated the temperature control and water flow control into the farm with the use of sensors, and the real-time updates were sent to the user through a mobile application. Bhojwani et al. [14] in their work proposed an IoT-based model for modeling and analysis of various factors affecting crop production in an agricultural field. This helps in deciding the ideal crop to be planted according to the environmental conditions sensed using the IoT setup.
3 System Design Methodology The proposed system design methodology is divided into three parts, namely system architecture, IoT system decision-making flow, and user interface mobile application.
3.1 System Architecture The block diagram of IoT system designed to automate weather and light controls in a hydroponic farm consists of three main parts: • Client-side sensing and control unit made up of microcontroller NodeMCU, relay switches attached to external appliances, and temperature and humidity sensors to transmit farm conditions. • Server-side cloud platform with a server and an online database. The server receives sensor data from the microcontroller through the MQTT broker and sends the same to the GUI applications for users, and the online database creates
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Fig. 1 Block diagram of IoT system for weather and light automation [17]
a log of all the sensor data for further evaluation and data analysis of ideal farm conditions. • GUI through a mobile application to provide remote access to the farm control to the user. Data collected from all the sensors connected to the microcontroller can be accessed through the mobile application. The complete block diagram of the system is presented in Fig. 1. The system starts when the temperature and humidity sensors continuously monitor the current climate conditions of the farm and NodeMCU, and the main microcontroller of the system receives the real-time data of sensors and shares it with other parts of the system. Based on the inherent logic and settings, NodeMCU processes the received data, shares it with the IoT database through the MQTT broker and server, and simultaneously sends action signals to the relay module to control connected climate control equipment. MQTT broker acts as an intermediary between NodeMCU and the server [15, 16]. It performs two tasks: First, it sends all the data to the server which in turn saves the data in the database or presents it to the users. Second, it receives control information from the users through the server and forwards it to the NodeMCU unit.
3.2 IoT System Decision Flow To constantly monitor and maintain the weather and light conditions of the farm in the ideal range of parameters, continuous decision making needs to happen in the client-side sensing and control. This decision making happens at regular intervals when the sensors transmit current parameters to the microcontroller which in turn decides whether the parameter is in the ideal range or not and if not, it sends a signal to the relay unit to turn on the corresponding appliance to maintain the ideal
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Fig. 2 Flowchart of IoT system decision-making algorithm [19]
parameter [18]. The decision algorithms and control flow for temperature, humidity, and ambient lights work in the following way (Fig. 2): Temperature—The system works by getting the temperature reading (T ) from the DHT11 sensor after every 30 min. T is then compared with the required optimal temperature for the farm which is set to 25 °C in this case. If T is greater than 25 °C, a signal is sent to the relay to switch on the AC. Otherwise, if the ambient temperature T is below 25 °C, a check is made on the relay status and if it is already on then the signal is sent to the relay to turn off the AC switch. The complete process is repeated after an interval of 30 min (Fig. 2). Humidity—The humidity control process starts by reading the current ambient humidity value (H) from the DHT11 sensor. If current humidity is more than the optimal ambient humidity value of 70% and the humidifier is on, a humidifier off signal is sent to the relay. If H is less than 50% and the humidifier is currently off, it is turned on. The complete system goes to stand by and the whole process is repeated after 30 min. No action is taken when the H is in the range of 50–70% (Fig. 3). Lights—The light automation control starts by getting the current time (CT) from the internet. The CT, if available from the internet is updated in the RTC module and if not then, it is fetched from the RTC module. Once the CT is fetched, it is checked
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Fig. 3 a Hydro Robo—basic-level mobile app. b Hydro Robo—advanced level mobile app
whether it lies between the duration of lights_On and lights_OFF time. If it is true and light relay is Off, then the ON signal is sent to light relay, and if it is false and light relay is On, then the Off signal is sent to the light relay.
3.3 User Interface Mobile Application After designing the complete hardware architecture, IoT setup, and automation algorithms, the next necessary element to achieve a completely automated system is a way for farm owners to remotely access the farm so that there is no need for them to be physically present at the farm location at all times [19]. This can be accomplished by providing an interface between the users and the farm in the form of a mobile or a web application. In this study, an android OS-based mobile application named Hydro Robo has been designed to enable remote access to the farm. Hydro Robo provides two kinds of interfaces based on the access rights granted to the app user for the farm in the following two ways: • The first interface is that of the basic privilege level (Fig. 3a) wherein the interaction of the IoT system and app user is only one way. The user is only allowed to receive and visualize the data coming from the controller. User has no manual control over the controller or its actions. The app user can remotely monitor all the farm conditions, but the provision to make changes in the farm environment is not granted to the user.
Design and Implementation of an IoT-Based Indoor Hydroponics Farm …
9
• The second interface is of the advanced privilege level (Fig. 3b) wherein the app user can remotely monitor as well as control the farm conditions by turning on/off farm devices remotely through the app. At this level, additional privileges are given along with basic-level controls. User can now visualize the data and can take manual decisions to switch on/off the relay in addition to automatic controls, along with that the user can change certain Controller settings through the remote app such as optimal ambient temperature, minimum humidity level, maximum humidity level, and the system stand-by time.
4 Results In this automated indoor farm, all the sensors required for the automation are controlled and maintained by the NodeMCU central microcontroller. The relay unit connected to NodeMCU controlled the artificial lights, humidifier, and air conditioner to maintain optimal weather conditions. Finally, all the sensed data from the microcontroller is sent to the online platform Firebase for mobile application. After the tuning and testing of the sensors and all the components modules of the system (Fig. 5), the IoT-based and completely automated indoor vertical hydroponic system was employed and tested for a period of one month. In the initial execution, the hydroponic setup was used to cultivate lettuce in an indoor area as shown in Fig. 4. Table 1 represents the temperature, and humidity data sensed from the farm in real time for the duration of 15 days. The complete duration of 24 h was divided into eight time slots of 3 h each, and for each slot, the live temperature and humidity were recorded through the sensors as represented in Table 1. The daily average temperature Fig. 4 IoT setup for farm automation
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Fig. 5 Lettuce cultivation in the indoor hydroponic farm
and humidity levels were calculated to compare against the ideal growth conditions needed for the lettuce growth. In Fig. 6, the system performance is illustrated by graphically representing the average climate conditions automatically maintained at the farm for the period of 15 days the automated farm was put to test [20]. The entire automated system was effective in monitoring and controlling the ambient climate conditions of the indoor farm to provide favorable growth conditions for the lettuce plant as evidenced by the growth of lettuce in Fig. 5. For analysis purposes, the hourly temperature and humidity of the farm were recorded and the daily average was calculated. It is evident that the IoT setup of sensors and actuators was successful in maintaining the temperature at 25.14 °C (Fig. 6a) and humidity at 69.76% (Fig. 6b) both in the specified range with 25 °C being the optimal temperature and 70% being the optimal humidity required for lettuce growth, and whenever the parameters deviated from the expected range, the decision-making algorithm as discussed in Sect. 3.2 was able to control them with the system flow shown in Fig. 2.
5 Conclusion Factors like population explosion, industrialization, and urbanization have resulted in the decline in the amount of arable lands and the simultaneous surge in food demands. For decades, researchers are involved in finding out a smart and sustainable solution to agriculture that can work on limited resources and provide more yields. Hydroponic farming is one such sustainable farming method that was first introduced in the 1930s [10]. It allows the growth of plants in an indoor environment with a vertical structure
Temperature
25.8
24.4
24-09-2022
5
25.1
23.9
68.7
68.4
04-10-2022
Date
20-09-2022
21-09-2022
22-09-2022
15
S. No.
1
2
3
69.1
09:00 A.M
Humidity
25.5
03-10-2022
14
24.5
24.1
01-10-2022
02-10-2022
12
23.1
25.1
13
30-09-2022
11
25.3
28-09-2022
29-09-2022
9
10
24.8
27-09-2022
8
25.2
25-09-2022
26-09-2022
6
7
23.8
22-09-2022
23-09-2022
3
4
25.9
25.2
20-09-2022
21-09-2022
1
09:00 A.M
2
Date
S. No.
68.9
69.3
69.3
12:00 P.M
24.3
25.7
24.4
24.9
23.7
25.3
26.1
25.1
26.1
24.7
26.2
24.2
25.4
25.7
26.4
12:00 P.M
69.8
70.1
70.3
03:00 P.M
25.4
26.2
25.6
25.4
25.3
26.3
26.4
25.7
26.1
25.7
26.7
25.2
26.7
25.5
26.8
03:00 P.M
70.5
69.6
69.7
06:00 P.M
25.1
25.9
25.3
25.1
25.1
26.3
26.2
25.4
25.9
25.3
26.5
25.0
26.4
26.1
27.4
06:00 P.M
69.3
69.1
69.6
09:00 P.M
24.7
25.7
24.5
24.7
24.6
26.1
25.9
24.9
25.8
24.9
26.4
24.4
26.2
25.8
26.9
09:00 P.M
68.7
69.2
69.1
12:00 A.M
24.2
25.6
24.4
24.4
24.3
25.6
25.7
24.4
25.6
24.8
26.3
24.4
25.9
25.8
26.4
12:00 A.M
68.0
69.0
68.9
03:00 A.M
23.6
25.4
24.1
24.3
23.5
24.9
25.6
24.5
25.4
24.7
25.9
24.1
25.8
25.7
26.3
03:00 A.M
67.8
69.3
68.7
06:00 A.M
23.5
25.4
23.9
24.1
23.4
24.7
25.4
24.3
25.2
24.5
25.9
23.9
25.5
25.4
26.1
06:00 A.M
Table 1 Temperature and humidity levels of the farm maintained automatically throughout the day over the period of 15 days
68.93
69.29
69.34
(continued)
Average humidity
24.3
25.7
24.5
24.7
24.1
25.5
25.8
24.9
25.7
24.9
26.2
24.4
25.9
25.7
26.5
Average temperature
Design and Implementation of an IoT-Based Indoor Hydroponics Farm … 11
70.9
70.0
70.4
68.7
23-09-2022
24-09-2022
25-09-2022
26-09-2022
27-09-2022
28-09-2022
29-09-2022
30-09-2022
01-10-2022
02-10-2022
03-10-2022
04-10-2022
5
6
7
8
9
10
11
12
13
14
15
70.3
70.3
70.4
69.3
68.9
67.8
68.6
68.9
09:00 A.M
4
Humidity
Date
S. No.
Table 1 (continued)
70.9
70.6
70.9
70.2
68.6
68.2
68.7
70.5
69.6
69.3
70.5
70.9
12:00 P.M
71.1
71.2
71.4
69.6
69.8
69.2
69.4
71.2
69.9
69.8
70.8
71.4
03:00 P.M
70.8
71.3
70.7
69.4
69.6
69.3
69.9
71.1
69.2
70.6
71.1
71.7
06:00 P.M
70.3
70.8
70.6
69.4
69.0
68.4
69.6
70.8
68.8
69.8
71.4
70.9
09:00 P.M
69.9
70.4
70.4
69.0
69.0
68.2
69.9
70.6
68.7
70.2
70.5
70.7
12:00 A.M
69.7
70.1
70.4
69.4
68.5
68.1
69.7
70.3
68.6
69.6
69.7
70.5
03:00 A.M
69.6
69.9
70.2
69.1
68.4
67.9
69.3
70.2
68.4
68.8
69.8
70.4
06:00 A.M
70.33
70.58
70.63
69.43
68.98
68.39
69.40
70.64
68.98
69.63
70.48
70.93
Average humidity
12 S. Jain and M. Kaur
Design and Implementation of an IoT-Based Indoor Hydroponics Farm …
13
Fig. 6 a Average temperature of the farm maintained automatically over the period of one month. b Average humidity of the farm maintained automatically over the period of one month
thus reducing the need for arable lands by 75%. In this research, an automated indoor hydroponic farm system is implemented by using IoT to provide optimal growth conditions artificially. The parameters of the farm were sensed using the IoT sensors, and optimal parameters were calculated based on the type of crop cultivated. All the data from sensors were available at the firebase platform and can be accessed by the user remotely anytime through the android mobile application Hydro Robo. In conclusion, more indoor farms with optimal utilization of the available resources can provide a solution to the problem of the difference between the demand and supply of food resources and thus reduce the dependency on traditional farming methodologies to fulfill the food requirements of the world’s population.
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References 1. Ramos C, Nóbrega L, Baras K, Gomes L (2019) Experimental NFT hydroponics system with lower energy consumption. In: 2019 5th experiment international conference (exp. at ‘19), Funchal (Madeira Island), Portugal, pp 102–106. http://doi.org/10.1109/EXPAT.2019.8876479 2. Muralimohan G, Arjun SV, Sakthivel G (2021) Design and development of IoT based hydroponic farming setup for production of green fodder. NVEO Nat Vol Essent Oils 8(2021):4325–4340 3. Kori AA, Veena KN, Basarkod PI, Harsha R (2021) Hydroponics system based on IoT. Ann Rom Soc Cell Biol 9683–9688 4. Kulkarni CN, Surwade A (2019) The future of farming through the IoT perspective. Int Res J Eng Technol (IRJET) 500–503. e-ISSN: 2395-0056 5. Dagar R, Som S, Khatri SK (2018) Smart farming—IoT in agriculture. In: 2018 international conference on inventive research in computing applications (ICIRCA), Coimbatore, pp 1052– 1056. http://doi.org/10.1109/ICIRCA.2018.8597264 6. Perwiratama R, Setiadi YK, Suyoto (2019) Smart hydroponic farming with IoT-based climate and nutrient manipulation system. In: 2019 international conference of artificial intelligence and information technology (ICAIIT), Yogyakarta, Indonesia, pp 129–132. http://doi.org/10. 1109/ICAIIT.2019.8834533 7. Ruengittinun S, Phongsamsuan S, Sureeratanakorn P (2017) Applied internet of thing for smart hydroponic farming ecosystem (HFE). In: 10th international conference on Ubi-media computing and workshops (Ubi-Media), Pattaya, pp 1–4. http://doi.org/10.1109/UMEDIA. 2017.8074148 8. Lakshmanan R, Djama M, Selvaperumal SK, Abdulla R (2020) Automated smart hydroponics system using internet of things. Int J Electr Comput Eng (IJECE) 10:6389. http://doi.org/10. 11591/ijece.v10i6.pp6389-6398 9. Ani A, Gopalakrishnan P (2020) Automated hydroponic drip irrigation using big data, pp 370–375. http://doi.org/10.1109/ICIRCA48905.2020.9182908 10. Chowdhury MEH, Khandakar A, Ahmed S, Al-Khuzaei F, Hamdalla J, Haque F, Reaz MBI, Al Shafei A, Al-Emadi N (2020) Design, construction and testing of IoT based automated indoor vertical hydroponics farming test-bed in Qatar. Sensors 20(19):5637. http://doi.org/10.3390/ s20195637 11. Jaiswal H, Singuluri R, Sampson SA (2019) IoT and machine learning based approach for fully automated greenhouse. In: 2019 IEEE Bombay section signature conference (IBSSC), pp 1–6. http://doi.org/10.1109/IBSSC47189.2019.8973086 12. Kaburuan ER, Jayadi R, Harisno (2019) A design of IoT-based monitoring system for intelligence indoor micro-climate horticulture farming in Indonesia. Procedia Comput Sci 157:459–464. ISSN 1877-0509. https://doi.org/10.1016/j.procs.2019.09.001 13. Dholu M, Ghodinde KA (2018) Internet of things (IoT) for precision agriculture application. In: 2018 2nd international conference on trends in electronics and informatics (ICOEI), pp 339–342. http://doi.org/10.1109/ICOEI.2018.8553720 14. Bhojwani Y, Singh R, Reddy R, Perumal B (2020) Crop selection and IOT based monitoring system for precision agriculture. In: 2020 international conference on emerging trends in information technology and engineering (Ic-ETITE). http://doi.org/10.1109/ic-etite47903.202 0.123 15. Pravin A, Prem Jacob T, Asha P (2018) Enhancement of plant monitoring using IOT. Int J Eng Technol 7(3.27):53. http://doi.org/10.14419/ijet.v7i3.27.17653 16. Abhiram MSD, Kuppili J, Manga NA (2020) Smart farming system using IOT for efficient crop growth. In: 2020 IEEE international students’ conference on electrical, electronics and computer science (SCEECS). http://doi.org/10.1109/sceecs48394.2020.147 17. Joshitha C, Kanakaraja P, Kumar KS, Akanksha P, Satish G (2021) An eye on hydroponics: the IoT initiative. In: 2021 7th international conference on electrical energy systems (ICEES). http://doi.org/10.1109/icees51510.2021.9383694
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18. Ethirajan L, Govindaraju C (2019) Hydroponic-based smart irrigation system using Internet of Things. Int J Commun Syst e4071. http://doi.org/10.1002/dac.4071 19. Ramakrishnam Raju SV, Dappuri B, Ravi Kiran Varma P, Yachamaneni M, Verghese DM, Mishra MK (2022) Design and implementation of smart hydroponics farming using IOT-based AI controller with mobile application system. J Nanomaterials 1–12. https://doi.org/10.1155/ 2022/4435591 20. Hermawan H, Uddin N, Darajat TM (2022) A development of web application for hydroponic monitoring systems. E3S Web Conf 348:00024. http://doi.org/10.1051/e3sconf/202234800024
Drone Ecosystem: Architecture for Configuring and Securing UAVs Harsh Sinha, Nikita Malik, and Menal Dahiya
Abstract Unmanned aerial vehicles (UAVs) are small aircraft that are guided autonomously, or by remote control, or both. Generally, these UAVs are used for providing aerial views when tackling complex scenarios in dangerous locations where human intervention is not possible. Internet of Drones (IoD) is a new term that has been created for separating general IoT devices like smart refrigerators, bulbs, cars, etc. from special use-cases drones. IoD is an infrastructure designed to provide access and control of UAVs over the cellular or internet via the ground station. The use of insecure drones in the civilian domain risks the general population to a very high privacy breach, as well as other domains such as policing, medical support, public safety, and industrial delivery system. Therefore, the concept of cybersecurity issues, privacy risks, and vulnerabilities introduced in the UAV ecosystem is important and is explored through this work. This research paper deals with UAV infrastructure and lays out a plan for the IoD communication architecture based on QUIC messaging protocol rather than TCP over the 5G cellular network. According to our research, over 87% of the UAVs are vulnerable to at least seven types of attack vectors and their variants that we have mentioned. Only high-end UAVs that are used for military reconnaissance and recovery operations are thoroughly secured to evade basic attacks but are still vulnerable to sophisticated attacks. Keywords Unmanned aerial vehicles · Internet of drones · QUIC protocol · Network slicing · 5G network · IoT
1 Introduction IoD is an emerging infrastructure concept from “drone on internet” due to the rapid and bulk usage of drones. It has gained the attention of academicians, researchers, scholars, students, and industrialists alike due to its vast usability in multiple domains H. Sinha · N. Malik (B) · M. Dahiya Department of Computer Science, Maharaja Surajmal Institute, Janakpuri, New Delhi 110058, India e-mail: [email protected] © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2023 S. Tanwar et al. (eds.), Proceedings of Fourth International Conference on Computing, Communications, and Cyber-Security, Lecture Notes in Networks and Systems 664, https://doi.org/10.1007/978-981-99-1479-1_2
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and different applications in the areas of civilian health, surveillance security, logistics supply, connectivity, smart agriculture, industry, safety, and the military usage that made the IoD/UAV ecosystem a critical infrastructure for the world [1]. UAVs are very small aircraft with a size range anywhere between 0.5 and 12.5 m. and are controlled and pivoted by an onboard computer system rather than an onboard pilot [2]. By understanding the crucial need and usability of UAV infrastructure in modern society, cybersecurity researchers have raised questions about security and privacy. The hype of this new technology has attracted Black Hats (a sect of the hacker community having mal-intentions) and individuals who are highly trained in finding vulnerabilities and creating custom exploits to fit their attack vector requirements. To aid them, there are already tools and exploits on the open-source platform ranging from easy distributed denial-of-service (DDoS) attacks to advanced remote code execution (RCE) attacks [3]. In order to obtain the desired performance from the IoD devices, it is therefore important to safeguard the UAV infrastructure, remove vulnerabilities, and stand against these threat walls, and this involves resources and energy being expelled. The nature of this paper is to provide the security and privacy aspects of the UAV ecosystem that is highly neglected during the production stage and the software updates. Even while configuring these drones, developers miss out on safeguarding these UAVs against new attack types. Understanding these attack vectors helps us in creating and implementing prevention methodologies for this complex infrastructure of interconnected technologies in the UAV ecosystem that have loopholes like protocol misconfiguration, open ports, weak or no firewalls, broken authentication, and insecure wireless access points (WAPs) that aid the Black Hats hackers in attacking the UAV system by utilizing these loopholes in the drone infrastructure. A major chunk of these attacks can be prevented just by implementing safeguards like firewalls and secure WAPs to defend against 0-day vulnerabilities and protocol misconfiguration. The use of Transmission Control Protocol (TCP) or Hypertext Transfer Protocol (HTTP) over Quick UDP Internet Connection (QUIC) is an example of protocol misconfiguration that results in insecure communication between UAV, ground station (GS), and the Cloud that can be intercepted because these protocols use plaintext communication which is not protected by Transport Layer Security (TSL) or Secure Socket Layer (SSL) security protocols, further on increasing the likelihood of signal-spoofing attacks [4]. This is just one example out of hundreds; therefore, understanding these components and core technologies that are used in the simple and complex UAV ecosystem is essential. Figure 1 summarizes the different sections discussed through this research work.
Drone Ecosystem: Architecture for Configuring and Securing UAVs
19
Fig. 1 Structure of the paper
Fig. 2 Combination of standard components in a UAV ecosystem
2 UAV Ecosystem Infrastructure There are multiple combinations in which UAV ecosystem’s architecture can exist where some additional components such as the SGS or Cloud Backup (CBu)/CloudBased Storage (CBS) may not be required [1]. These additional components are included to improve the robustness of the entire system; for our research, we will focus on a very standard-operated UAV architecture [2] such as given in Fig. 2, which is generally used for civilian safety, industrial delivery, military usage, etc. The entire data relay telemetry (as illustrated in Fig. 6 and explained in Table 2) including the drones, UAV cluster, ground station, and 5G cellular network has been divided into three stages and explained in the subsequent sections of the paper.
3 Communication Architecture-Stage One Stage one of data telemetry includes drone(s), light-weight cryptographic function, drone cluster, cluster heads, and ad hoc network. The entire telemetry of the data is shown in Table 2.
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Fig. 3 Variations of UAVs based on factors [6]
3.1 UAV or Drones Drones are aircraft without a human pilot, crew, or passengers onboard and are the main component of the UAV ecosystem, operated by the GS or SGS with the help of an onboard computer system. They come in multiple variations such as given in Fig. 3, and some models are defined by their usage and requirements. But there are four types of UAV(s): multi-rotor drones, fixed-wing drones, single-rotor drones, and fixed-wing hybrid VTOLs [5] that are classified under six drone categories of Pioneer, Skyeye, Hunter, Watchkeeper, Fire scout, and Eagle eye [2].
3.2 Light-Weight Cryptographic Function Note light-weight cryptographic function like RSA based [7] on the Diffie–Hellman key exchange encryption protocol is necessary because it requires less computation complexity and memory to be implemented on an IOD device limited by the power supply. That can encrypt the entire firmware, onboard flight module, and telemetry data of the UAV(s) so that no data can be extrapolated or poisoned on the drone(s) [5] by an attacker.
Drone Ecosystem: Architecture for Configuring and Securing UAVs
21
3.3 Ad Hoc Network Ad hoc network is a connection between two or more wireless UAV(s) replacing the traditional use of network infrastructure equipment such as wireless access points (WAPs) [8]. Drones need to communicate with each other to share the navigation data, cluster integrity information, aerial scans, terrain depth, collected raw video, and essential datasets with other nodes, seemingly acting as one large sharing device that collectively shares data over the mobile ad hoc network (MANET). The entire cluster needs to relay intact data without sending redundant information from multiple drone(s) by the use of cluster optimization algorithms (routing algorithms), and cluster network infrastructures are necessary to decide autonomously for which node to relay the data to the GS. The use of MANET in the UAV cluster is suggested since it makes the cluster decentralized, where each node dynamically participates in routing by forwarding data to other nodes [8].
4 Communication Architecture-Stage Two Stage two of data telemetry includes 5G cellular network, 5G cellular tower, network slicing, and IoD network slice.
4.1 5G Cellular Network The entire telemetry between the UAV and GS to the Cloud is based on a multi-hop communication network [2] that operates on frequencies of 2.4 GHz and 5.8 GHz that can provide a swift and robust relay of data even during the rapid node switching [9]. Therefore, it is essential to select the network configuration that can improve the lifetime of the entire network.
4.2 5G Cellular Tower 5G cellular tower exhibited in Fig. 4 emits three operating bands for the 5G cellular network as given in Table 1. The higher we travel in the bandwidth spectrum, the closer we have to be to the cellular site. Building and maintaining a network is a high-value job, but in a 5G network, automating the process of network control and forwarding functions we decouple the manual architecture by using software-defined networking (SDN) [10]. This enables network controls to be directly programmable, allowing network managers
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Fig. 4 5G cellular tower (site) semantics [11]
Table 1 5G cellular bandwidth operand name, spectrum, coverage, and bandwidth speed Bandwidth operands
Spectrum (GHz)
Area coverage
Bandwidth speed
Low band