рдпрд╛ рдИ-рдкреБрд╕реНрддрдХрд╛рд╡рд┐рд╖рдпреА
It covers core principles of machine learning, threat detection strategies, and the cyber attack kill chain with AI intervention points.
Readers will learn about emerging threats leveraging AI techniques, including social engineering, phishing attacks, and adversarial machine learning challenges.
The book provides insights into secure data acquisition, handling biases, and ensuring data integrity, alongside frameworks for compliance and privacy.
Practical guidance on designing algorithms, feature selection, and model evaluation is shared, along with real-world case studies such as insider threat detection, threat hunting automation, and intrusion detection systems.
Emphasis is placed on developing explainable AI, ethical considerations, resilient infrastructure, and deploying AI-powered security tools at scale.
It also discusses future trends like quantum computing, autonomous defense systems, and the integration of AI with existing security frameworks.
This book serves as an essential resource for cybersecurity professionals, researchers, and anyone interested in the strategic application of AI to protect digital assets in an ever-changing threat landscape.
рдЖрдгрдЦреА рдбрд┐рд╕реНрдХрд╡реНрд╣рд░ рдХрд░рд╛
рд▓реЗрдЦрдХрд╛рд╡рд┐рд╖рдпреА
With a robust background in Communications and IT cultivated during a distinguished military career, the author naturally transitioned into the dynamic field of Cyber Security. This shift not only marked a significant professional evolution but also became the most rewarding decision of their life. Passionate about sharing knowledge and insights, they draw from real-world experiences to illuminate the critical importance of cybersecurity in todayтАЩs digital age.
