Klappentext

Generative AI for Cybersecurity and Privacy offers a groundbreaking exploration of how generative artificial intelligence is reshaping the landscape of cybersecurity and privacy protection in an era of rapid digital transformation.

Inhalt

Part I: Foundations and Core Concepts 1. A Systematic Review of Machine Learning and Deep Learning Applications in Information Security 2. Impact of Generative AI on Cybersecurity and Data Privacy Part II: Applications in Threat Detection and Defense 3. Generative Adversarial Networks for Intrusion and Malware Detection 4. Harnessing Generative AI for Enhanced Cybersecurity in E-Health Systems 5. Leveraging Generative AI for Enhancing SDN Security: A Two-Level Classification Framework Against Relay-Based Link Fabrication Attacks Part III: Sector-Specific Use Cases 6. Adoption of Artificial Intelligence in Smart Cities: Literature Review and Bibliometric Analysis 7. Securing AI in Agriculture: Emerging Cyber Threats, Vulnerabilities, and Resilience Strategies 8. Blockchain-SDN-Based Secure Architectures for Industrial IoT 9. Towards Next-Generation Cyber Threat Intelligence in Edge-IoT: A Synergy of Generative AI, Federated Learning, and Blockchain Part IV: Ethics, Education, and Future Directions 10. Higher Education and Generative Artificial Intelligence: Applications, Challenges, and Ethics 11. On Exploring Generative AI for Privacy Preservation in IoT Ecosystems 12. Navigating Dualities - The Role of Generative AI in Cybersecurity for Defense and Attacks 13. Generative AI-Driven Penetration Testing: Frameworks, Methodologies, and Ethical Considerations