Unleashing ML for Advanced Threat Detection by Mehak Khurana (.PDF)
File Size: 12.7 MB
Unleashing Machine Learning for Advanced Threat Detection and Prevention in Industry 4.0 (Computer Science, Technology and Applications; Cybercrime and Cybersecurity Research) by Mehak Khurana, Shilpa Mahajan, Asif Ali Laghari
Requirements: .PDF reader, 12.7 MB | True PDF
Overview: Unleashing Machine Learning (ML) for Advanced Threat Detection and Prevention 4.0 examines the transformative role of ML in enhancing cybersecurity. It explores how machine learning is revolutionizing cybersecurity in the era of smart industries. The book explores incorporating state-of-the-art ML approaches to detect, predict, prevent, and defend against complex cyberattacks in the age of IoT devices and critical infrastructures. This book takes a deep dive into the challenges posed by cyber threats and presents innovative ML models that offer effective ways of identifying and mitigating these risks. The book delves into practical applications of various ML algorithms, including supervised, unsupervised, and hybrid models, which are employed to detect malicious activities in Cyber-Physical Production Systems (CPPSs). Readers will gain insights into data-driven security models, automated threat response mechanisms, and the latest advancements in AI-powered cybersecurity solutions. It outlines case studies that present the successful implementation of ML by bridging the gap between theory and practice in enhancing industrial security.
Genre: Non-Fiction > Tech & Devices
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