AI-Driven Security Systems and Intelligence Threat Response Using Autonomous Cyber Defense
Salam Al-E’mari, Yousef K. Sanjalawe, Fuad Manna Fataftah · Advances in computational intelligence and robotics book series · 2025
The expanding cyber threat landscape has compelled organizations to adopt AI-driven security systems for robust defense against sophisticated attacks. This chapter explores artificial intelligence in cybersecurity, emphasizing its role in intelligent threat detection, analysis, and response. AI models, including supervised and unsupervised learning, deep learning, and reinforcement learning, have redefined cybersecurity by enabling behavior-based anomaly detection and automated threat mitigation. Key discussions highlight autonomous systems making real-time decisions, leveraging adaptive control loops, and employing self-healing mechanisms for resilience. This chapter also examines challenges in operational scalability, ethical implications of automation, and the necessity of human oversight in decision-making. The findings underscore the need for synergy between automation and human expertise to foster an intelligent, adaptive cyber defense ecosystem.