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AI and Machine Learning for Cybersecurity provides comprehensive guidance integrating artificial intelligence and machine learning with cybersecurity best practices. The work combines clarity and technical depth equipping readers with operational expertise in network security and threat defense. Coverage addresses AI techniques, supervised and unsupervised learning applications, and real-world security implementations. The book examines ethical, legal, and policy dimensions of AI in security contexts. Topics include anomaly detection, intrusion prevention, malware analysis, and emerging threats. The work emphasizes practical frameworks and strategic deployment. Designed for security professionals, engineers, and students, this resource develops understanding of AI-enhanced cybersecurity technologies transforming threat detection and response capabilities. Case studies and research-based approaches support implementation. Research methodologies and evaluation strategies advance security capabilities.
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