Machine Learning And Ai For Cybersecurity Enhancing Threat Detection And Response
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Machine Learning and AI for Cybersecurity: Enhancing Threat Detection and Response
Machine Learning and AI for Cybersecurity: Enhancing Threat Detection and Response explores how cutting-edge artificial intelligence and machine learning technologies are revolutionizing cybersecurity. This book provides a comprehensive overview of AI-driven threat detection, behavior-based anomaly analysis, and automated incident response systems. Covering key techniques such as deep learning, natural language processing, and reinforcement learning, it highlights real-world applications in malware detection, intrusion prevention, and phishing defense. Designed for researchers, professionals, and students, the book bridges the gap between theory and practice, offering practical insights into deploying intelligent cybersecurity solutions in an increasingly complex digital landscape.
AI in Cybersecurity
This book presents a collection of state-of-the-art AI approaches to cybersecurity and cyberthreat intelligence, offering strategic defense mechanisms for malware, addressing cybercrime, and assessing vulnerabilities to yield proactive rather than reactive countermeasures. The current variety and scope of cybersecurity threats far exceed the capabilities of even the most skilled security professionals. In addition, analyzing yesterday’s security incidents no longer enables experts to predict and prevent tomorrow’s attacks, which necessitates approaches that go far beyond identifying known threats. Nevertheless, there are promising avenues: complex behavior matching can isolate threats based on the actions taken, while machine learning can help detect anomalies, prevent malware infections, discover signs of illicit activities, and protect assets from hackers. In turn, knowledge representation enables automated reasoning over network data, helping achieve cybersituational awareness. Bringing together contributions by high-caliber experts, this book suggests new research directions in this critical and rapidly growing field.
Data Science For Cyber-security
Cyber-security is a matter of rapidly growing importance in industry and government. This book provides insight into a range of data science techniques for addressing these pressing concerns.The application of statistical and broader data science techniques provides an exciting growth area in the design of cyber defences. Networks of connected devices, such as enterprise computer networks or the wider so-called Internet of Things, are all vulnerable to misuse and attack, and data science methods offer the promise to detect such behaviours from the vast collections of cyber traffic data sources that can be obtained. In many cases, this is achieved through anomaly detection of unusual behaviour against understood statistical models of normality.This volume presents contributed papers from an international conference of the same name held at Imperial College. Experts from the field have provided their latest discoveries and review state of the art technologies.