Advanced AI Techniques for Cybersecurity: Concepts, Architectures, And Emerging Trends
This book discusses the impact of more sophisticated artificial intelligence methods and practices that are changing the current state of cybersecurity, allowing proactive, adaptive and automated defense. It offers the basics of AI and machine learning, changing nature of threat and how data analytics is used to detect malicious trends. Basic chapters describe the intrusion detective, malware analysis, and predictive intelligence supervised, unsupervised, deep, and reinforcement learning frameworks. The article considers the use of AI in cloud, IoT, and SOC activities with a focus on automated response and threat hunting. Specialized sections focus on adversarial learning of machines, machine resiliency, explainability, privatization aware methods, and governance. Future directions are discussed as the emerging trends of graph neural networks, edge AI, federated learning, and autonomous cyber defense. The book in general gives a systematic guide to researchers and practitioners on how to develop resilient smart security systems.
