Machine Learning Algorithms For Enhancing Cyber Defense Systems
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Machine Learning Algorithms for Enhancing Cyber Defense Systems
Author: Arokia Suresh Kumar Joseph
language: en
Publisher: RK Publication
Release Date: 2024-11-19
Machine Learning Algorithms for Enhancing Cyber Defense Systems the transformative role of machine learning in fortifying cybersecurity frameworks. The provides a comprehensive analysis of key algorithms, their applications in threat detection, anomaly analysis, and automated response, and their ability to adapt to evolving cyber threats. With an emphasis on real-world case studies and emerging trends, it bridges the gap between theoretical concepts and practical implementations, offering insights for professionals, researchers, and students aiming to harness machine learning for robust and intelligent cyber defense.
Machine Learning and Security
Author: Clarence Chio
language: en
Publisher: "O'Reilly Media, Inc."
Release Date: 2018-01-26
Can machine learning techniques solve our computer security problems and finally put an end to the cat-and-mouse game between attackers and defenders? Or is this hope merely hype? Now you can dive into the science and answer this question for yourself. With this practical guide, you’ll explore ways to apply machine learning to security issues such as intrusion detection, malware classification, and network analysis. Machine learning and security specialists Clarence Chio and David Freeman provide a framework for discussing the marriage of these two fields, as well as a toolkit of machine-learning algorithms that you can apply to an array of security problems. This book is ideal for security engineers and data scientists alike. Learn how machine learning has contributed to the success of modern spam filters Quickly detect anomalies, including breaches, fraud, and impending system failure Conduct malware analysis by extracting useful information from computer binaries Uncover attackers within the network by finding patterns inside datasets Examine how attackers exploit consumer-facing websites and app functionality Translate your machine learning algorithms from the lab to production Understand the threat attackers pose to machine learning solutions
Machine Learning Approaches in Cyber Security Analytics
This book introduces various machine learning methods for cyber security analytics. With an overwhelming amount of data being generated and transferred over various networks, monitoring everything that is exchanged and identifying potential cyber threats and attacks poses a serious challenge for cyber experts. Further, as cyber attacks become more frequent and sophisticated, there is a requirement for machines to predict, detect, and identify them more rapidly. Machine learning offers various tools and techniques to automate and quickly predict, detect, and identify cyber attacks.