Affiliation:
1. Independent Researcher, India
Abstract
The intersection of cybersecurity and generative artificial intelligence (AI) has become a crucial frontier as the digital landscape changes. By examining the interaction between AI-powered attacks and defence mechanisms and concentrating on applications like anomaly detection, synthetic data generation, automated incident response, and forensics, the chapter examines the potential of generative artificial intelligence (AI) in redefining conventional cybersecurity paradigms. In order to reduce the hazards associated with deepfakes and synthetic media, the chapter discusses the examination of adversarial machine learning techniques and strategies. Along with offering guidance on incorporating AI into security operations, encouraging human-AI cooperation, and building strong AI skills, it also discusses the ethical ramifications of AI-driven security procedures. It also serves as a comprehensive guide for security professionals, researchers, and decision-makers, offering a holistic understanding of the synergies between AI and cybersecurity.
Reference37 articles.
1. Akhtar, N., & Ghosh, J. (2019). Recent Trends in Deep Neural Networks Based Adversarial Attacks and Defenses. arXiv preprint arXiv:1908.03603.
2. Applying generative adversarial networks to enhance network anomaly detection.;H. M.Al-Khateeb;IEEE International Conference on Systems, Man and Cybernetics (SMC),2019
3. On the Dangers of Stochastic Parrots
4. Wild patterns: Ten years after the rise of adversarial machine learning
5. Exploring Generative Artificial Intelligence for the Responsible Design of Trustworthy Systems.;T.Bremermann;Proceedings of the 2022 ACM Conference on Fairness, Accountability, and Transparency,2022