The "Essence" of Network Security: An End-to-End Panorama 9789811593161, 9789811593178

Table of contents :
Preface
Acknowledgements
Description
Contents
Editors and Contributors
Acronyms
List of Figures
List of Tables
List of Graphs
Part IIntroduction
Introduction to Network Security Technologies
1 Introduction
2 Network Security Attacks
2.1 Passive Attacks
2.2 Active Attacks
2.3 Advanced Attacks
2.4 Malwares
3 Cutting Edge Network Security Technologies
3.1 Topical Forensics Approaches
3.2 Blockchain and Cryptography
3.3 Impact of Artificial Intelligence and Machine Learning on Security Aspects
3.4 Security Networking
3.5 Anonymous Traffic Networking
4 Conclusion
References
Part IIReview of Recent Trends in Forensics
A Systematic Review of Digital, Cloud and IoT Forensics
1 Introduction
2 Digital Forensics and Its Evolution
2.1 Document Metadata in Digital Forensics and Steganography
2.2 Digital Forensics and Full Disk Encryption
2.3 A Solution to the Problem of Scale
2.4 Digital Forensics Is a Real-Time Task
2.5 Ramping up the Speed of Forensic Processes
3 Cloud Forensics Till Date
3.1 Tools Under Test
3.2 Forensic Readiness: A Proactive Measure
3.3 Logging and Log Segregation in the Cloud
3.4 Enhancing Reliability and Trust in Cloud
4 IoT Forensics: The Budding Field of Forensics
4.1 Forensics of the Enabling Technologies of IoT
4.2 Challenges in IoT Forensics
4.3 An IoT Forensics Model
4.4 A Decentralized IoT Forensics Framework
4.5 IoTFC: A Blockchain-Based IoT Forensic Framework
5 Open Areas of Research
5.1 Enhancement of Digital Forensics Tools
5.2 Distributed Computing and GPU-Based Digital Forensics
5.3 Enhancement of Physical Memory Forensics
5.4 Reduction of Cloud Data Acquisition Time in Cloud Forensics
5.5 Privacy Preservation in Blockchain-Based IoT Forensics
5.6 Preservation of Overwritten Data in IoT Systems
5.7 Document File Meta Data Removal
6 Conclusion
References
Part IIIBlockchain and Cryptography
Blockchain-Based Framework for Managing Customer Consent in Open Banking
1 Introduction
1.1 Significance of Customer Consent Management in Open Banking
1.2 How Technology Can Help
2 Blockchain Technology
2.1 Types of Blockchain Networks
2.2 Consortium Blockchain
3 Related Work
4 Working Principle of Blockchain-Based Solution
4.1 Defining Standards for Third-Party Providers
5 Blockchain-Based Solution Architecture
6 Features of Blockchain-Based Solution
7 Comparative Analysis
8 Issues and Challenges
9 Conclusion
References
A Comprehensive Study of Pros and Cons on Implementation of Blockchain for IoT Device Security
1 Introduction
2 IoT Architecture
3 Classification of Attacks on IoT Devices
4 Security Concern of IoT Devices
5 Issues and Challenges
6 Blockchain Solutions for IoT Devices
7 Other Blockchain Solutions
8 Conclusion
References
Role of Cryptography in Network Security
1 Introduction
2 Classical Cryptosystems
2.1 Data Encryption Standard
2.2 Triple Data Encryption Standard
2.3 Advanced Data Encryption Standard
2.4 Blowfish Algorithm
2.5 Rivest Cipher or Ron’s Code Version 5 Algorithm
2.6 Honey Encryption
3 Public Key Cryptosystem
3.1 RSA Algorithm
3.2 Diffie-Hellman Key Exchange Technique
3.3 Elliptic Curve Cryptography Algorithm
3.4 Hyperelliptic Curve Cryptography
4 Authentication and Digital Signature Algorithms
4.1 Message Encryption
4.2 Message Authentication Code
4.3 Hash Function
5 Quantum Cryptography
5.1 Quantum Key Distribution
5.2 Quantum Secret Direct Communication
5.3 Quantum Secret Sharing
5.4 Applications of Quantum Computing for Network Security
6 Homomorphic Cryptography
7 Light Weight Cryptographic Techniques for Wireless Sensor Network and IoT
7.1 Scalable Encryption Algorithm
7.2 Chaotic S-Box for Wireless Sensor Network
7.3 Cognitive Radio Encryption Standard Algorithm
8 Network-on-Chip Security
9 Conclusion
References
Part IVMachine Learning and Artificial Intelligence in Network Security
Cyber Security with AI—Part I
1 Introduction
2 Background of Cyber Security
3 Summary of Artificial Intelligence, Machine Learning and Deep Learning in Cyber security
3.1 Support Vector Machine
3.2 Decision Tree
3.3 k-Nearest Neighbor
3.4 Clustering
3.5 Genetic Algorithm (GA) and Genetic Programming (GP)
3.6 Hidden Markov Models (HMM)
3.7 Inductive Learning
3.8 Random Forest Tree
3.9 Self-organizing Map
3.10 Artificial Neural Networks
3.11 Deep Learning
4 Difference between Deep Learning and Machine Learning
5 Artificial Intelligence and Machine Learning Applied to Cyber Security
6 Error Decisive Factors
7 Cyber Security Datasets
8 Future Research Directions and Challenges
9 Conclusion
References
Cyber Security with AI–Part II
1 Introduction
2 Cyber Security
3 Network Security
3.1 Importance of Network Security
3.2 Disruptions Due to Lack of Network Security
3.3 Types of Network Security Attacks
4 Types of Network Security
5 Artificial Intelligence and Its Types
6 Role of AI in the Improvement of Cyber Security
7 Conclusion
References
Detection of Malicious URLs Using Deep Learning Approach
1 Introduction
1.1 Web Phishing and Malicious URL Detection
1.2 Existing Phishing Scenario
1.3 Anti-phishing Solutions
1.4 Preventing Methods
1.5 User Training Schemes
1.6 Phishing Detection Schemes
2 Existing State of Art
2.1 Classification-Based Approach
2.2 Machine Learning-Based Approach
2.3 Deep Learning-Based Approach
2.4 Statement of the Problem
2.5 Contributions of the Present Work
3 Data Collection Method
4 Feature Engineering and Deep Learning-Based Approach for Malicious URL Detection
4.1 Feature Based on the URL Lexical Information
4.2 Feature Extracted from CNN
5 Architecture Preliminaries
5.1 Convolutional Neural Network (CNN)
5.2 Long Short Term Memory (LSTM)
5.3 Bidirectional Long Short Term Memory
6 Configuration of the Proposed Model
6.1 Combination of CNN and LSTM
7 Model Comparisons and Results Achieved
7.1 Accuracy and Loss Plot of Various Traditional Deep Learning Models
7.2 Accuracy and Loss Plots of Emerging Deep Learning Models
8 Constraint of Proposed Model
9 Concluding Remarks
References
Part VSecurity Networking
Software-Defined Network Vulnerabilities
1 Introduction
2 Architecture of Software-Defined Network
2.1 Characteristics of SDN Architecture
2.2 Few Components of SDN Architecture
2.3 OpenFlow Protocol
3 Classification of SDN Logical Components
4 Attributes of Secured Communication Network
5 Security Threats of SDN
6 Mechanism for Designing Secure and Dependable SDN Environment
7 Security Issues of SDN Data Plane
7.1 SDN Data Plane Vulnerabilities
7.2 SDN Data Plane Attacks and Countermeasures
8 Security Issues of SDN Control Plane
8.1 Vulnerability of Control Plane
8.2 SDN Control Plane Attack and Countermeasures
8.3 Security Vulnerabilities in OpenFlow
9 Security Issues of SDN Application Plane
10 Conclusion
References
Demystifying Security on NDN: A Survey of Existing Attacks and Open Research Challenges
1 Introduction
2 NDN Overview
2.1 NDN Protocol Stack
2.2 Naming
2.3 Packet Forwarding in NDN
3 Inherent Features Providing Security Support in NDN
4 Classification of Attacks in NDN
4.1 Attacks in the Application Layer and Its Countermeasures
4.2 Attacks in Network Layer and Its Countermeasures
4.3 Attacks in Strategy Layer and Its Countermeasures
4.4 Attacks in Data Link Layer and Its Countermeasures
5 Discussion and Open Research Challenges
5.1 TCP-IP Security Versus NDN Security
5.2 Research Challenges
6 Conclusion
References
Anonymous Traffic Networks
1 Introduction
1.1 Idea of Anonymous Traffic Network (ATN)
1.2 History and the Driving Force Behind
1.3 Which User Community is Showing Interests Toward ATN?
1.4 How Does ATN (Like Tor Network) Work?
2 Types of Implementation of ATN
2.1 Anonymity Ecosystem
2.2 Mix Networks
2.3 Batching Strategies
2.4 High-Latency Anonymity Systems
2.5 Low-Latency Anonymity Systems
3 Challenges of Anonymous Traffic Networks (ATN)
4 Tools and Technologies
4.1 The Onion Router (Tor)
4.2 Anonymous Browsers
5 Relevance of Anonymity and Privacy of Users for ATN
6 Anonymous Traffic Networks—Projects
6.1 Invisible Internet Project [I2P]
6.2 PipeNet
6.3 Freenet
7 Conclusion
References
Appendix List of Standards
Author Index