Generative AI for Cybersecurity and Privacy (Hardcover, 1)

Preface Aknowledgments Part I: Introduction to Generative AI for Cybersecurity and Privacy 1. Understanding Generative AI: Concepts and Frameworks o Overview of Generative AI o Historical Context and Evolution o Key Algorithms and Models 2. The Importance of Generative AI in Cybersecurity and Privacy o Impact on Cybersecurity o Enhancing Privacy with AI o Ethical and Legal Considerations Part II: Applications of Generative AI in Cybersecurity 3. Anomaly Detection with Generative AI o Techniques and Approaches o Real-world Applications and Case Studies o Performance Metrics and Evaluation 4. Generative Adversarial Networks (GANs) for Cyber Threat Intelligence o Generating Threat Signatures o Predictive Analytics for Threat Forecasting o Practical Implementations 5. Generative AI for Malware Detection and Analysis o Approaches to Malware Classification o Behavioral Analysis using Generative Models o Advanced Threat Detection Mechanisms 6. Phishing Detection and Prevention with Generative AI o Identifying and Mitigating Phishing Attacks o Simulating Phishing Scenarios with Generative Models o Best Practices and Countermeasures Part III: Enhancing Privacy and Data Security with Generative AI 7. Privacy-preserving Generative Models o Differential Privacy Techniques o Data Anonymization and Secure Multi-party Computation o Case Studies and Applications 8. Secure Data Sharing and Federated Learning o Ensuring Data Security in Collaborative Environments o Blockchain for Secure Data Transactions o Practical Implementations and Challenges 9. AI-driven Encryption and Decryption o Generative Approaches to Cryptography o Enhancing Existing Security Protocols o Emerging Trends and Innovations Part IV: Case Studies and Real-world Implementations 10. Generative AI in Financial Sector Security o Threat Detection and Fraud Prevention o Addressing Privacy Concerns o Lessons Learned and Best Practices 11. Generative AI in Healthcare Security o Protecting Patient Data o Detecting and Mitigating Security Breaches o Future Directions and Research Opportunities 12. Generative AI in Government and Defense o Enhancing National Security with AI o Cyber Warfare and AI-driven Defense Mechanisms o Policy Implications and Ethical Considerations Part V: Managing Generative AI in Cybersecurity and Privacy 13. Developing a Generative AI Strategy for Cybersecurity o Planning, Prioritization, and Resourcing o Implementation Strategies o Risk Management Approaches 14. Incident Response and Generative AI o Preparing for AI-driven Cybersecurity Incidents o Response Strategies and Best Practices o Post-incident Analysis and Improvement 15. Business Continuity and Disaster Recovery with Generative AI o Ensuring Resilience in the Face of Cybersecurity Threats o AI-driven Continuity Planning o Recovery Strategies 16. Measuring and Reporting on AI-enhanced Cybersecurity o Metrics, Dashboards, and Communication o Evaluating AI Effectiveness o Reporting to Stakeholders About the Authors Index