Predicting The Unknown Machine Learning For Zero Day Vulnerability Detection A Data Driven Approach To Securing The Future
Download Predicting The Unknown Machine Learning For Zero Day Vulnerability Detection A Data Driven Approach To Securing The Future PDF/ePub or read online books in Mobi eBooks. Click Download or Read Online button to get Predicting The Unknown Machine Learning For Zero Day Vulnerability Detection A Data Driven Approach To Securing The Future book now. This website allows unlimited access to, at the time of writing, more than 1.5 million titles, including hundreds of thousands of titles in various foreign languages.
Predicting the Unknown: Machine Learning for Zero-Day Vulnerability Detection – A Data-Driven Approach to Securing the Future
Author: Hariprasad Sivaraman
language: en
Publisher: Libertatem Media Private Limited
Release Date: 2022-07-15
Zero-day vulnerabilities pose one of the most pressing cybersecurity threats, allowing attackers to exploit software flaws before security teams can respond. Predicting the Unknown: Machine Learning for Zero- Day Vulnerability Detection presents a cutting-edge approach to combating these threats using AI-driven techniques, empowering security professionals with proactive defense strategies. This book explores the limitations of traditional security models—such as signature-based and heuristic detection—and highlights how machine learning (ML) is transforming zero-day threat detection. Readers will discover how ML models, including anomaly detection, supervised and unsupervised learning, and reinforcement learning, can analyze vast datasets of network traffic and system logs to identify emerging vulnerabilities before they are exploited. From feature engineering and real-time anomaly detection to adversarial machine learning and evasion tactics, Predicting the Unknown delves into the core components of AI-powered cybersecurity. The book also examines advanced ML techniques like deep learning and reinforcement learning, showcasing their role in dynamic threat mitigation. Packed with case studies, technical insights, and future trends—including the integration of quantum computing and explainable AI—this book provides a comprehensive roadmap for security professionals, data scientists, and researchers. Whether you're looking to strengthen enterprise defenses or pioneer nextgeneration cybersecurity solutions, Predicting the Unknown equips you with the tools to stay ahead of evolving cyber threats.
Smart Analytics, Artificial Intelligence and Sustainable Performance Management in a Global Digitalised Economy
Author: Pallavi Tyagi
language: en
Publisher: Emerald Group Publishing
Release Date: 2023-05-29
The Covid 19 pandemic has created chaos in the business world and forced leaders to rethink their operational status quo. Balancing the physical and virtual spaces of the global digital economy has called for additional support from data-driven technologies like smart analytics and artificial intelligence.
Ubiquitous Security
This book constitutes the refereed proceedings of the Second International Conference, UbiSec 2022, held in Zhangjiajie, China, during December 28–31, 2022. The 34 full papers and 4 short papers included in this book were carefully reviewed and selected from 98 submissions. They were organized in topical sections as follows: cyberspace security, cyberspace privacy, cyberspace anonymity and short papers.