Utilizing Generative AI for Cyber Defense Strategies 1st Edition by Noor Zaman Jhanjhi ISBN 9798369389454 by -- instant download after payment.

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ISBN 13: 9798369389454
Author: Noor Zaman Jhanjhi

Utilizing Generative AI for Cyber Defense Strategies 1st Table of contents:

Chapter 1: Federated Learning for Collaborative Cyber Defense
ABSTRACT
INTRODUCTION
CHALLENGES IN CYBER DEFENSE
FEDERATED LEARNING IN IOT
APPLICATIONS OF FEDERATED LEARNING IN CYBER DEFENSE
FEDERATED LEARNING FRAMEWORKS AND ARCHITECTURES
PRIVACY-PRESERVING TECHNIQUES IN FEDERATED LEARNING
CASE STUDIES AND USE CASES
ETHICAL AND LEGAL CONSIDERATIONS IN FEDERATED LEARNING
CONCLUSION
REFERENCES
Chapter 2: Risk Assessment and Mitigation With Generative AI Models
ABSTRACT
INTRODUCTION
ETHICAL PRINCIPLES IN AI
SECURE WEB MODEL GENERATION
BIAS AND FAIRNESS CONSIDERATIONS
PRIVACY AND DATA PROTECTION
TRANSPARENCY AND EXPLAINABILITY
ETHICAL DECISION-MAKING IN WEB MODEL GENERATION
RESPONSIBLE DEPLOYMENT AND GOVERNANCE
COMMUNITY ENGAGEMENT AND STAKEHOLDER PARTICIPATION
REGULATORY COMPLIANCE AND LEGAL IMPLICATIONS
CONCLUSION
REFERENCES
Chapter 3: Dynamic Defense Strategies With Generative AI
ABSTRACT
INTRODUCTION
CHALLENGES IN CYBER DEFENSE
FUNDAMENTALS OF GENERATIVE ARTIFICIAL INTELLIGENCE FOR CYBER DEFENSE
DYNAMIC THREAT DETECTION AND RESPONSE
ADAPTIVE SECURITY CONTROLS
PREDICTIVE ANALYTICS AND FORECASTING
THREAT INTELLIGENCE FUSION
CASE STUDIES AND USE CASES
ETHICAL AND LEGAL CONSIDERATIONS
FUTURE DIRECTIONS AND EMERGING TRENDS
CONCLUSION
REFERENCES
Chapter 4: Unleashing the Power of Generative Adversarial Networks for Cybersecurity:
ABSTRACT
Introduction
Anomaly Detection and Threat modelling using GANs
GANs for Malware Analysis and Defensive Strategies
Adversarial Defense and Robustness with GANs
Practical Implementation and Deployment Considerations
Ethical Considerations and Responsible Usage of GANs
The road ahead
REFERENCES
Chapter 5: Enhancing Security Through Generative AI-Based Authentication
ABSTRACT
INTRODUCTION
REFERENCES
Chapter 6: Generative AI for Threat Intelligence and Information Sharing
ABSTRACT
INTRODUCTION
FUNDAMENTALS OF THREAT INTELLIGENCE
CHALLENGES IN TRADITIONAL THREAT INTELLIGENCE
GENERATIVE AI TECHNIQUES FOR THREAT INTELLIGENCE
ENHANCING THREAT DETECTION AND ANALYSIS
INFORMATION SHARING AND COLLABORATION
CASE STUDIES AND USE CASES
ETHICAL AND LEGAL CONSIDERATIONS
FUTURE DIRECTIONS AND EMERGING TRENDS
CONCLUSION
REFERENCES
Chapter 7: Generative AI for Threat Hunting and Behaviour Analysis
ABSTRACT
INTRODUCTION
FUNDAMENTALS OF THREAT HUNTING
CHALLENGES IN TRADITIONAL THREAT HUNTING
GENERATIVE AI TECHNIQUES FOR THREAT HUNTING
ANOMALY DETECTION AND BEHAVIORAL PROFILING
THREAT INTELLIGENCE INTEGRATION
AUTOMATED THREAT RESPONSE
CASE STUDIES AND USE CASES
ETHICAL AND LEGAL CONSIDERATIONS
FUTURE DIRECTIONS AND EMERGING TRENDS
CONCLUSION
REFERENCES
Chapter 8: A Methodical Approach to Exploiting Vulnerabilities and Countermeasures Using AI
ABSTRACT
INTRODUCTION
LITERATURE REVIEW
METHODOLOGY
CONCLUSION
REFERENCES
Chapter 9: Variational Autoencoders (VAEs) for Anomaly Detection
ABSTRACT
INTRODUCTION
LITERATURE REVIEW
CONCLUSION
REFERENCES
Chapter 10: A Novel Approach for Intrusion Detection System Using Deep Learning Architecture
ABSTRACT
INTRODUCTION
LITERATURE REVIEW
METHODOLOGY
RESULTS
CONCLUSION
REFERENCES
Chapter 11: A New Approach for Detecting Malware Using a Convolutional Autoencoder With Kernel Density Estimation
ABSTRACT
INTRODUCTION
LITERATURE REVIEW
METHODOLOGY
RESULTS
CONCLUSION
REFERENCES
Chapter 12: Scouting the Juncture of Internet of Things (IoT), Deep Learning, and Cybercrime:
ABSTRACT
INTRODUCTION
IOT AND DEEP LEARNING IN ENHANCING CYBERCRIME INVESTIGATIONS
DEEP LEARNING IN CYBER CRIMES
LEGAL ANALYSIS: EXAMINATION OF CURRENT LEGAL FRAMEWORKS GOVERNING CYBERCRIME INVESTIGATIONS
INFERENCES OF IOT AND DEEP LEARNING IN CYBER CRIMES INVESTIGATIONS
CONCLUSION AND FUTURE SCOPE
REFERENCES
Chapter 13: Muscles of Deep Learning (DL) and Internet of Things (IoT) in Cyber Crimes Investigation:
ABSTRACT
INTRODUCTION AND BACKGROUND
INTERNET OF THINGS (IOT) AND DEEP LEARNING (DL) IN CYBER CRIMES INVESTIGATION
ROLE OF IOT IN ENHANCING CYBER CRIME DETECTION AND PREVENTION
DEEP LEARNING IN CYBER SECURITY: DL TECHNIQUES APPLIED TO CYBER SECURITY
USE OF IOT AND DL IN DETECTION AND THREAT INTELLIGENCE
CYBER CRIMES IN FINANCIAL ASPECTS: IOT AND DEEP LEARNING- LEGAL CHALLENGES AND ETHICAL CONSIDERATIONS
LEGAL FRAMEWORK FOR FUTURE DATA ANALYTICS: IOT AND DL FOR TACKLING CYBER CRIMES
INTERNATIONAL COOPERATION: CYBER CRIME INVESTIGATION ASSIMILATING IOT AND DL
CONCLUSION AND FUTURE SCOPE
REFERENCES
Chapter 14: Safeguarding the Future:
ABSTRACT
INTRODUCTION
AN OVERVIEW OF THE DIGITAL AGE'S CYBERSECURITY CHALLENGES
AN OVERVIEW OF GENERATIVE AI AND ITS POTENTIAL IN CYBERSECURITY
Foundations of Generative AI
RELEVANCE OF GENERATIVE AI IN CYBERSECURITY
RESEARCH GAPS
CASE STUDIES
DIFFICULTIES IN UTILIZING GENERATIVE AI FOR CYBERSECURITY
CONCLUSION
FUTURE RESEARCH DIRECTION
REFERENCES
Compilation of References
About the Contributors
Index

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