-
Browse Book Series
- Adhesion and Adhesives: Fundamental and Applied Aspects
- Advances in Additive Manufacturing Technologies
- Advances in Antenna, Microwave and Communication Engineering
- Advances in Biofeedstocks and Biofuels
- Advances in Cyber Security
- Advances in Data Engineering and Machine Learning
- Advances in E-Mobility
- Advances in Hydrogen Production and Storage
- Advances in Intelligent and Scientific Computing (AISC)
- Advances in Learning Analytics for Intelligent Cloud-IoT Systems
- Advances in Membrane Processes
- Advances in Nanotechnology and Applications
- Advances in Natural Gas Engineering
- Advances in Pipes and Pipelines
- Advances in Production Engineering
- Advances in Solar Cell Materials and Storage
- Applied Functional Materials
- Artificial Intelligence and Soft Computing for Industrial Transformation
- Astrobiology Perspectives on Life in the Universe
- Bioprocessing in Food Science
- Computational Intelligence and Biomedical Engineering
- Concise Introductions to AI and Data Science
- Cyber Systems and Quantum Engineering
- Decentralized Systems and Next-Generation Internet
- Diatoms: Biology and Applications
- Digital Convergence in Engineering Systems
- Emerging Trends in Medicinal and Pharmaceutical Chemistry
- Engineering Systems Design for Sustainable Development
- Fintech in a Sustainable Digital Society
- Industry 5.0 Transformation Applications
- Infectious and Rare Diseases
- Innovations in Materials and Manufacturing
- Leading-Edge Breakthroughs in Artificial Intelligence
- Machine Learning in Biomedical Science and Healthcare Informatics
- Materials Degradation and Failure
- Mathematics and Computer Science
- Next-Generation Computing and Communication Engineering
- Performability Engineering Series
- Rotating Machinery Fundamentals and Advances
- Studies in Computational Intelligence and Smart Technologies
- Sustainable Computing and Optimization
Browse Subject Areas
For Authors
Submit a ProposalWireless Communication in Cybersecurity
 | Edited by S. Sountharrajan, R. Maheswar, Geetanjali Rathee, and M. Akila Series: Advances in Antenna, Microwave and Communication Engineering Copyright: 2024 | Status: Published ISBN: 9781119910435 | Hardcover | 278 pages Price: $225 USD  |
One Line Description
Presenting the concepts and advances of wireless communication in cybersecurity, this volume, written and edited by a global team of experts, also goes into the practical applications for the engineer, student, and other industry professionals.
Audience
Researchers, software developers, engineers, scientists, students, and other professionals in communication engineering, electronics, electrical engineering, and other areas of research
Researchers, software developers, engineers, scientists, students, and other professionals in communication engineering, electronics, electrical engineering, and other areas of research
Description
Rapid advancement in wireless communications and related technologies has led to the use of newer technologies like 6G, Internet of Things (IoT), Radar, and others. Not only are the technologies expanding, but the impact of wireless communication is also changing, becoming an inevitable part of daily life. With increased use comes great responsibilities and challenges for any newer technology. The growing risks in the direction of security, authentication, and encryption are some major areas of concern, together with user privacy and security. We have seen significant development in blockchain technology along with development in a wireless network that has proved extremely useful in solving various security issues. Quite efficient secure cyber-physical systems can be constructed using these technologies.
This comprehensive new volume covers the many methods and technologies used in intrusion detection in wireless networks. This book allows readers to reach their solutions using various predictive algorithm-based approaches and some curated real-time protective examples that are defined herein. Artificial intelligence (AI) concepts are devised and proposed for helping readers understand the core concepts of efficiencies of threats, and the parallel solutions are covered. The chapters also state the challenges in privacy and security levels for various algorithms and various techniques and tools are proposed for each challenge. It focuses on providing exposure to readers about data security and privacy for wider domains.
The editorial and author team aims to address all possible solutions to the various problems faced in the newer techniques of wireless communications, improving the accuracies and reliability over the possible vulnerabilities and security threats to wireless communications. It is a must have for any engineer, scientist, or other industry professional working in this area.
Back to Top
Rapid advancement in wireless communications and related technologies has led to the use of newer technologies like 6G, Internet of Things (IoT), Radar, and others. Not only are the technologies expanding, but the impact of wireless communication is also changing, becoming an inevitable part of daily life. With increased use comes great responsibilities and challenges for any newer technology. The growing risks in the direction of security, authentication, and encryption are some major areas of concern, together with user privacy and security. We have seen significant development in blockchain technology along with development in a wireless network that has proved extremely useful in solving various security issues. Quite efficient secure cyber-physical systems can be constructed using these technologies.
This comprehensive new volume covers the many methods and technologies used in intrusion detection in wireless networks. This book allows readers to reach their solutions using various predictive algorithm-based approaches and some curated real-time protective examples that are defined herein. Artificial intelligence (AI) concepts are devised and proposed for helping readers understand the core concepts of efficiencies of threats, and the parallel solutions are covered. The chapters also state the challenges in privacy and security levels for various algorithms and various techniques and tools are proposed for each challenge. It focuses on providing exposure to readers about data security and privacy for wider domains.
The editorial and author team aims to address all possible solutions to the various problems faced in the newer techniques of wireless communications, improving the accuracies and reliability over the possible vulnerabilities and security threats to wireless communications. It is a must have for any engineer, scientist, or other industry professional working in this area.
Back to Top
Author / Editor Details
S. Sountharrajan, PhD has completed his B.E (IT) from Periyar University in the year 2003, M.E (CSE) from Anna University in the year 2010, and Ph.D. in the field of Machine Learning from Anna University in the year 2017 and He is currently working as an Associate Professor and Program Head, B.Tech Computer Science and Engineering in School of Computing (SOC) at Amrita Vishwa Vidyapeetham, Chennai Campus. He has published 50 Scopus-indexed papers.
S. Sountharrajan, PhD has completed his B.E (IT) from Periyar University in the year 2003, M.E (CSE) from Anna University in the year 2010, and Ph.D. in the field of Machine Learning from Anna University in the year 2017 and He is currently working as an Associate Professor and Program Head, B.Tech Computer Science and Engineering in School of Computing (SOC) at Amrita Vishwa Vidyapeetham, Chennai Campus. He has published 50 Scopus-indexed papers.
R. Maheswar, PhD has completed his B.E (ECE) from Madras University in the year 1999, M.E (Applied Electronics) from Bharathiyar University in the year 2002 and Ph.D in the field of Wireless Sensor Network from Anna University in the year 2012. He is presently designated as Director In-Charge in the Centre for Research and Development, KPR Institute of Engineering and Technology, Coimbatore, India.
Geetanjali Rathee, PhD is currently working as an Assistant Professor in the Department of Computer Science and Engineering of Netaji Subhas University of Technology (NSUT), Dwarka, New Delhi. She received her B.Tech, M.Tech & Ph.D all in Computer Science & Engineering in 2011, 2014 and 2017 respectively.
M. Akila, PhD is Computer Science Professor inspiring and motivating students by providing a thorough understanding of a variety of computer concepts. Facilitated and lectured undergraduate and postgraduate college students of Computer Science courses, and actively engaged with professional organizations such as IET and IEEE.
Back to Top
Table of Contents
Preface
1. BBUCAF: A Biometric-Based User Clustering Authentication Framework in Wireless Sensor Network
Rinesh, S., Thamaraiselvi, K., Mahdi Ismael Omar and Abdulfetah Abdulahi Ahmed
1.1 Introduction to Wireless Sensor Network
1.2 Background Study
1.3 A Biometric-Based User Clustering Authentication Framework
1.3.1 Biometric-Based Model
1.3.2 Clustering
1.4 Experimental Analysis
1.5 Conclusion
References
2. DeepNet: Dynamic Detection of Malwares Using Deep Learning Techniques
Nivaashini, M., Soundariya, R. S., Vishnupriya, B. and Tharsanee, R. M.
2.1 Introduction
2.2 Literature Survey
2.2.1 ML or Metaheuristic Methods for Malware Detection
2.2.2 Deep Learning Algorithms for Malware Detection
2.3 Malware Datasets
2.3.1 Android Malware Dataset
2.3.2 SOREL-20M Dataset
2.4 Deep Learning Architecture
2.4.1 Deep Neural Networks (DNN)
2.4.2 Convolutional Neural Networks (CNN)
2.4.3 Recurrent Neural Networks (RNN)
2.4.4 Deep Belief Networks (DBN)
2.4.5 Stacked Autoencoders (SAE)
2.5 Proposed System
2.5.1 Datasets Used
2.5.2 System Architecture
2.5.3 Data Preprocessing
2.5.4 Proposed Methodology
2.5.5 DeepNet
2.5.6 DBN
2.5.7 SAE
2.5.8 Categorisation
2.6 Result and Analysis
2.7 Conclusion & Future Work
References
3. State of Art of Security and Risk in Wireless Environment Along with Healthcare Case Study
Deepa Arora and Oshin Sharma
3.1 Introduction
3.2 Literature Survey
3.3 Applications of Wireless Networks
3.4 Types of Attacks
3.4.1 Passive Attacks
3.4.2 Release of Message Contents
3.4.3 Traffic Analysis
3.4.4 Eavesdropping
3.5 Active Attacks
3.5.1 Malware
3.5.2 Password Theft
3.5.3 Bandwidth Stealing
3.5.4 Phishing Attacks
3.5.5 DDoS
3.5.6 Cross-Site Attack
3.5.7 Ransomware
3.5.8 Message Modification
3.5.9 Message Replay
3.5.10 Masquerade
3.6 Layered Attacks in WSN
3.6.1 Attacks in Physical Layer
3.6.2 Attacks in Data Link Layer
3.6.3 Attacks in Network Layer
3.6.4 Attacks in Transport Layer
3.6.5 Attacks in Application Layer
3.7 Security Models
3.7.1 Bio-Inspired Trust and Reputation Model
3.7.2 Peer Trust System
3.8 Case Study: Healthcare
3.8.1 Security Risks in Healthcare
3.8.2 Prevention from Security Attacks in Healthcare
3.9 Minimize the Risks in a Wireless Environment
3.9.1 Generate Strong Passwords
3.9.2 Change Default Wi-Fi Username and Password
3.9.3 Use Updated Antivirus
3.9.4 Send Confidential Files with Passwords
3.9.5 Detect the Intruders
3.9.6 Encrypt Network
3.9.7 Avoid Sharing Files Through Public Wi-Fi
3.9.8 Provide Access to Authorized Users
3.9.9 Used a Wireless Controller
3.10 Conclusion
References
4. Machine Learning-Based Malicious Threat Detection and Security Analysis on Software-Defined Networking for Industry 4.0
J. Ramprasath, N. Praveen Sundra Kumar, N. Krishnaraj and M. Gomathi
4.1 Introduction
4.1.1 Software-Defined Network
4.1.2 Types of Attacks
4.1.2.1 Denial of Services
4.1.2.2 Distributed Denial of Service
4.2 Related Works
4.3 Proposed Work for Threat Detection and Security Analysis
4.3.1 Traffic Collection
4.3.1.1 Data Flow Monitoring and Data Collection
4.3.1.2 Purpose of Data Flow Monitoring and Data Collection
4.3.1.3 Types of Collection
4.3.2 Feature Selection Using Entropy
4.3.3 Malicious Traffic Detection
4.3.3.1 Framing of the Expected Traffic Status
4.3.3.2 Traffic Filtering Using Regression
4.3.4 Traffic Mitigation
4.4 Implementation and Results
4.5 Conclusion
References
5. Privacy Enhancement for Wireless Sensor Networks and the Internet of Things Based on Cryptological Techniques
Karthiga, M., Indirani, A., Sankarananth, S., S. S. Sountharrajan and E. Suganya
5.1 Introduction
5.2 System Architecture
5.3 Literature Review
5.4 Proposed Methodology
5.5 Results and Discussion
5.6 Analysis of Various Security and Assaults
5.7 Conclusion
References
6. Security and Confidentiality Concerns in Blockchain Technology: A Review
G. Prabu Kanna, Abinash M.J., Yogesh Kumar, Jagadeesh Kumar and E. Suganya
6.1 Introduction
6.2 Blockchain Technology
6.3 Blockchain Revolution Drivers
6.3.1 Transparent, Decentralised Consensus
6.3.2 Model of Agreement(s)
6.3.3 Immutability and Security
6.3.4 Anonymity and Automation
6.3.5 Impact on Business, Regulation, and Services
6.3.6 Access and Identity
6.4 Blockchain Classification
6.4.1 Public Blockchain
6.4.2 Private Blockchain
6.4.3 Blockchain Consortium
6.5 Blockchain Components and Operation
6.5.1 Data
6.5.2 Hash
6.5.3 MD5
6.5.4 SHA 256
6.5.5 MD5 vs. SHA-256
6.6 Blockchain Technology Applications
6.6.1 Blockchain Technology in the Healthcare Industry
6.6.2 Stock Market Uses of Blockchain Technology
6.6.3 Financial Exchanges in Blockchain Technology
6.6.4 Blockchain in Real Estate
6.6.5 Blockchain in Government
6.6.6 Other Opportunities in the Industry
6.7 Difficulties
6.8 Conclusion
References
7. Explainable Artificial Intelligence for Cybersecurity
P. Sharon Femi, K. Ashwini, A. Kala and V. Rajalakshmi
7.1 Introduction
7.1.1 Use of AI in Cybersecurity
7.1.2 Limitations of AI
7.1.3 Motivation to Integrate XAI to Cybersecurity
7.1.4 Contributions
7.2 Cyberattacks
7.2.1 Phishing Attack
7.2.1.1 Spear Phishing
7.2.1.2 Whaling
7.2.1.3 Smishing
7.2.1.4 Pharming
7.2.2 Man-in-the-Middle (MITM) Attack
7.2.2.1 ARP Spoofing
7.2.2.2 DNS Spoofing
7.2.2.3 HTTPS Spoofing
7.2.2.4 Wi-Fi Eavesdropping
7.2.2.5 Session Hijacking
7.2.3 Malware Attack
7.2.3.1 Ransomware
7.2.3.2 Spyware
7.2.3.3 Botnet
7.2.3.4 Fileless Malware
7.2.4 Denial-of-Service Attack
7.2.5 Zero-Day Exploit
7.2.6 SQL Injection
7.3 XAI and Its Categorization
7.3.1 Intrinsic or Post-Hoc
7.3.2 Model-Specific or Model-Agnostic
7.3.3 Local or Global
7.3.4 Explanation Output
7.4 XAI Framework
7.4.1 SHAP (SHAPley Additive Explanations) and SHAPley Values
7.4.1.1 Computing SHAPley Values
7.4.2 LIME - Local Interpretable Model Agnostic Explanations
7.4.2.1 Working of LIME
7.4.3 ELI5
7.4.4 Skater
7.4.5 DALEX
7.5 Applications of XAI in Cybersecurity
7.5.1 Smart Healthcare
7.5.2 Smart Banking
7.5.3 Smart Cities
7.5.4 Smart Agriculture
7.5.5 Transportation
7.5.6 Governance
7.5.7 Industry 4.0
7.5.8 5G and Beyond Technologies
7.6 Challenges of XAI Applications in Cybersecurity
7.6.1 Datasets
7.6.2 Evaluation
7.6.3 Cyber Threats Faced by XAI Models
7.6.4 Privacy and Ethical Issues
7.7 Future Research Directions
7.8 Conclusion
References
8. AI-Enabled Threat Detection and Security Analysis
A. Saran Kumar, S. Priyanka, V. Praveen and G. Sivapriya
8.1 Introduction
8.1.1 Phishing
8.1.2 Features
8.1.3 Optimizer Types
8.1.4 Gradient Descent
8.1.5 Types of Phishing Attack Detection
8.2 Literature Survey
8.3 Proposed Work
8.3.1 Data Collection and Pre-Processing
8.3.2 Dataset Description
8.3.3 Performance Metrics
8.4 System Evaluation
8.5 Conclusion
References
9. Security Risks and Its Preservation Mechanism Using Dynamic Trusted Scheme
Geetanjali Rathee, Akshay Kumar, S. Karthikeyan and N. Yuvaraj
9.1 Introduction
9.1.1 Need of Trust
9.1.2 Need of Trust-Based Mechanism in IoT Devices
9.1.3 Contribution
9.2 Related Work
9.3 Proposed Framework
9.3.1 Dynamic Trust Updation Model
9.3.2 Blockchain Network
9.4 Performance Analysis
9.4.1 Dataset Description and Simulation Settings
9.4.2 Traditional Method and Evaluation Metrics
9.5 Results Discussion
9.6 Empirical Analysis
9.7 Conclusion
References
10. 6G Systems in Secure Data Transmission
A.V.R. Mayuri, Jyoti Chauhan, Abhinav Gadgil, Om Rajani and Soumya Rajadhyaksha
10.1 Introduction
10.2 Evolution of 6G
10.3 Functionality
10.3.1 Security and Privacy Issues
10.3.1.1 Artificial Intelligence (AI)
10.3.1.2 Molecular Communication
10.3.1.3 Quantum Communication
10.3.2 Blockchain
10.3.3 TeraHertz Technology
10.3.4 Visible Light Communication (VLC)
10.4 6G Security Architectural Requirements
10.5 Future Enhancements
10.6 Summary
References
11. A Trust-Based Information Forwarding Mechanism for IoT Systems
Geetanjali Rathee, Hemraj Saini, R. Maheswar and M. Akila
11.1 Introduction
11.1.1 Need of Security
11.1.2 Role of Trust-Based Mechanism in IoT Systems
11.1.3 Contribution
11.2 Related Works
11.3 Estimated Trusted Model
11.4 Blockchain Network
11.5 Performance Analysis
11.5.1 Dataset Description and Simulation Settings
11.5.2 Comparison Methods and Evaluation Metrics
11.6 Results Discussion
11.7 Empirical Analysis
11.8 Conclusion
References
About the Editors
Index
Back to Top
Preface
1. BBUCAF: A Biometric-Based User Clustering Authentication Framework in Wireless Sensor Network
Rinesh, S., Thamaraiselvi, K., Mahdi Ismael Omar and Abdulfetah Abdulahi Ahmed
1.1 Introduction to Wireless Sensor Network
1.2 Background Study
1.3 A Biometric-Based User Clustering Authentication Framework
1.3.1 Biometric-Based Model
1.3.2 Clustering
1.4 Experimental Analysis
1.5 Conclusion
References
2. DeepNet: Dynamic Detection of Malwares Using Deep Learning Techniques
Nivaashini, M., Soundariya, R. S., Vishnupriya, B. and Tharsanee, R. M.
2.1 Introduction
2.2 Literature Survey
2.2.1 ML or Metaheuristic Methods for Malware Detection
2.2.2 Deep Learning Algorithms for Malware Detection
2.3 Malware Datasets
2.3.1 Android Malware Dataset
2.3.2 SOREL-20M Dataset
2.4 Deep Learning Architecture
2.4.1 Deep Neural Networks (DNN)
2.4.2 Convolutional Neural Networks (CNN)
2.4.3 Recurrent Neural Networks (RNN)
2.4.4 Deep Belief Networks (DBN)
2.4.5 Stacked Autoencoders (SAE)
2.5 Proposed System
2.5.1 Datasets Used
2.5.2 System Architecture
2.5.3 Data Preprocessing
2.5.4 Proposed Methodology
2.5.5 DeepNet
2.5.6 DBN
2.5.7 SAE
2.5.8 Categorisation
2.6 Result and Analysis
2.7 Conclusion & Future Work
References
3. State of Art of Security and Risk in Wireless Environment Along with Healthcare Case Study
Deepa Arora and Oshin Sharma
3.1 Introduction
3.2 Literature Survey
3.3 Applications of Wireless Networks
3.4 Types of Attacks
3.4.1 Passive Attacks
3.4.2 Release of Message Contents
3.4.3 Traffic Analysis
3.4.4 Eavesdropping
3.5 Active Attacks
3.5.1 Malware
3.5.2 Password Theft
3.5.3 Bandwidth Stealing
3.5.4 Phishing Attacks
3.5.5 DDoS
3.5.6 Cross-Site Attack
3.5.7 Ransomware
3.5.8 Message Modification
3.5.9 Message Replay
3.5.10 Masquerade
3.6 Layered Attacks in WSN
3.6.1 Attacks in Physical Layer
3.6.2 Attacks in Data Link Layer
3.6.3 Attacks in Network Layer
3.6.4 Attacks in Transport Layer
3.6.5 Attacks in Application Layer
3.7 Security Models
3.7.1 Bio-Inspired Trust and Reputation Model
3.7.2 Peer Trust System
3.8 Case Study: Healthcare
3.8.1 Security Risks in Healthcare
3.8.2 Prevention from Security Attacks in Healthcare
3.9 Minimize the Risks in a Wireless Environment
3.9.1 Generate Strong Passwords
3.9.2 Change Default Wi-Fi Username and Password
3.9.3 Use Updated Antivirus
3.9.4 Send Confidential Files with Passwords
3.9.5 Detect the Intruders
3.9.6 Encrypt Network
3.9.7 Avoid Sharing Files Through Public Wi-Fi
3.9.8 Provide Access to Authorized Users
3.9.9 Used a Wireless Controller
3.10 Conclusion
References
4. Machine Learning-Based Malicious Threat Detection and Security Analysis on Software-Defined Networking for Industry 4.0
J. Ramprasath, N. Praveen Sundra Kumar, N. Krishnaraj and M. Gomathi
4.1 Introduction
4.1.1 Software-Defined Network
4.1.2 Types of Attacks
4.1.2.1 Denial of Services
4.1.2.2 Distributed Denial of Service
4.2 Related Works
4.3 Proposed Work for Threat Detection and Security Analysis
4.3.1 Traffic Collection
4.3.1.1 Data Flow Monitoring and Data Collection
4.3.1.2 Purpose of Data Flow Monitoring and Data Collection
4.3.1.3 Types of Collection
4.3.2 Feature Selection Using Entropy
4.3.3 Malicious Traffic Detection
4.3.3.1 Framing of the Expected Traffic Status
4.3.3.2 Traffic Filtering Using Regression
4.3.4 Traffic Mitigation
4.4 Implementation and Results
4.5 Conclusion
References
5. Privacy Enhancement for Wireless Sensor Networks and the Internet of Things Based on Cryptological Techniques
Karthiga, M., Indirani, A., Sankarananth, S., S. S. Sountharrajan and E. Suganya
5.1 Introduction
5.2 System Architecture
5.3 Literature Review
5.4 Proposed Methodology
5.5 Results and Discussion
5.6 Analysis of Various Security and Assaults
5.7 Conclusion
References
6. Security and Confidentiality Concerns in Blockchain Technology: A Review
G. Prabu Kanna, Abinash M.J., Yogesh Kumar, Jagadeesh Kumar and E. Suganya
6.1 Introduction
6.2 Blockchain Technology
6.3 Blockchain Revolution Drivers
6.3.1 Transparent, Decentralised Consensus
6.3.2 Model of Agreement(s)
6.3.3 Immutability and Security
6.3.4 Anonymity and Automation
6.3.5 Impact on Business, Regulation, and Services
6.3.6 Access and Identity
6.4 Blockchain Classification
6.4.1 Public Blockchain
6.4.2 Private Blockchain
6.4.3 Blockchain Consortium
6.5 Blockchain Components and Operation
6.5.1 Data
6.5.2 Hash
6.5.3 MD5
6.5.4 SHA 256
6.5.5 MD5 vs. SHA-256
6.6 Blockchain Technology Applications
6.6.1 Blockchain Technology in the Healthcare Industry
6.6.2 Stock Market Uses of Blockchain Technology
6.6.3 Financial Exchanges in Blockchain Technology
6.6.4 Blockchain in Real Estate
6.6.5 Blockchain in Government
6.6.6 Other Opportunities in the Industry
6.7 Difficulties
6.8 Conclusion
References
7. Explainable Artificial Intelligence for Cybersecurity
P. Sharon Femi, K. Ashwini, A. Kala and V. Rajalakshmi
7.1 Introduction
7.1.1 Use of AI in Cybersecurity
7.1.2 Limitations of AI
7.1.3 Motivation to Integrate XAI to Cybersecurity
7.1.4 Contributions
7.2 Cyberattacks
7.2.1 Phishing Attack
7.2.1.1 Spear Phishing
7.2.1.2 Whaling
7.2.1.3 Smishing
7.2.1.4 Pharming
7.2.2 Man-in-the-Middle (MITM) Attack
7.2.2.1 ARP Spoofing
7.2.2.2 DNS Spoofing
7.2.2.3 HTTPS Spoofing
7.2.2.4 Wi-Fi Eavesdropping
7.2.2.5 Session Hijacking
7.2.3 Malware Attack
7.2.3.1 Ransomware
7.2.3.2 Spyware
7.2.3.3 Botnet
7.2.3.4 Fileless Malware
7.2.4 Denial-of-Service Attack
7.2.5 Zero-Day Exploit
7.2.6 SQL Injection
7.3 XAI and Its Categorization
7.3.1 Intrinsic or Post-Hoc
7.3.2 Model-Specific or Model-Agnostic
7.3.3 Local or Global
7.3.4 Explanation Output
7.4 XAI Framework
7.4.1 SHAP (SHAPley Additive Explanations) and SHAPley Values
7.4.1.1 Computing SHAPley Values
7.4.2 LIME - Local Interpretable Model Agnostic Explanations
7.4.2.1 Working of LIME
7.4.3 ELI5
7.4.4 Skater
7.4.5 DALEX
7.5 Applications of XAI in Cybersecurity
7.5.1 Smart Healthcare
7.5.2 Smart Banking
7.5.3 Smart Cities
7.5.4 Smart Agriculture
7.5.5 Transportation
7.5.6 Governance
7.5.7 Industry 4.0
7.5.8 5G and Beyond Technologies
7.6 Challenges of XAI Applications in Cybersecurity
7.6.1 Datasets
7.6.2 Evaluation
7.6.3 Cyber Threats Faced by XAI Models
7.6.4 Privacy and Ethical Issues
7.7 Future Research Directions
7.8 Conclusion
References
8. AI-Enabled Threat Detection and Security Analysis
A. Saran Kumar, S. Priyanka, V. Praveen and G. Sivapriya
8.1 Introduction
8.1.1 Phishing
8.1.2 Features
8.1.3 Optimizer Types
8.1.4 Gradient Descent
8.1.5 Types of Phishing Attack Detection
8.2 Literature Survey
8.3 Proposed Work
8.3.1 Data Collection and Pre-Processing
8.3.2 Dataset Description
8.3.3 Performance Metrics
8.4 System Evaluation
8.5 Conclusion
References
9. Security Risks and Its Preservation Mechanism Using Dynamic Trusted Scheme
Geetanjali Rathee, Akshay Kumar, S. Karthikeyan and N. Yuvaraj
9.1 Introduction
9.1.1 Need of Trust
9.1.2 Need of Trust-Based Mechanism in IoT Devices
9.1.3 Contribution
9.2 Related Work
9.3 Proposed Framework
9.3.1 Dynamic Trust Updation Model
9.3.2 Blockchain Network
9.4 Performance Analysis
9.4.1 Dataset Description and Simulation Settings
9.4.2 Traditional Method and Evaluation Metrics
9.5 Results Discussion
9.6 Empirical Analysis
9.7 Conclusion
References
10. 6G Systems in Secure Data Transmission
A.V.R. Mayuri, Jyoti Chauhan, Abhinav Gadgil, Om Rajani and Soumya Rajadhyaksha
10.1 Introduction
10.2 Evolution of 6G
10.3 Functionality
10.3.1 Security and Privacy Issues
10.3.1.1 Artificial Intelligence (AI)
10.3.1.2 Molecular Communication
10.3.1.3 Quantum Communication
10.3.2 Blockchain
10.3.3 TeraHertz Technology
10.3.4 Visible Light Communication (VLC)
10.4 6G Security Architectural Requirements
10.5 Future Enhancements
10.6 Summary
References
11. A Trust-Based Information Forwarding Mechanism for IoT Systems
Geetanjali Rathee, Hemraj Saini, R. Maheswar and M. Akila
11.1 Introduction
11.1.1 Need of Security
11.1.2 Role of Trust-Based Mechanism in IoT Systems
11.1.3 Contribution
11.2 Related Works
11.3 Estimated Trusted Model
11.4 Blockchain Network
11.5 Performance Analysis
11.5.1 Dataset Description and Simulation Settings
11.5.2 Comparison Methods and Evaluation Metrics
11.6 Results Discussion
11.7 Empirical Analysis
11.8 Conclusion
References
About the Editors
Index
Back to Top