Cyber Attacks and Defense: AI-Driven Approaches and Techniques

This dissertation explores the application of AI-driven cyber attacks and defense methods in the field of cyber security. First, it introduces the application of AI in attacks, including AI-enhanced phishing attacks, automated phishing and spoofing, AI-driven DDoS attacks, and AI-assisted malware generation, which utilize AI's sophistication and adaptive capabilities to pose challenges to cybersecurity. The paper then discusses the use of AI in defense, such as AI-driven threat detection and prevention, anomalous behavior recognition, authentication and access control, and the use of AI in network monitoring and response, which improve the efficiency and accuracy of security teams. In addition, the paper analyzes the challenges of AI in cybersecurity, including adversarial attacks, data privacy, and ethical issues. Finally, trends and future research directions for AI in cybersecurity are discussed, including improving the robustness and interpretability of AI models. This paper emphasizes the potential of AI in cybersecurity and provides recommendations for future research.