This book aims to provide a comprehensive overview of the applications of Artificial Intelligence (AI) in the area of Cybersecurity and Digital Forensics. The various chapters of this book are written to explore how cutting?edge technologies can be used to improve the detection, prevention, and investigation of cybercrime and help protect digital assets.

Digital Defence covers an overview of deep learning and AI techniques and their relevance to cybersecurity and digital forensics, discusses common cyber threats and vulnerabilities, and how deep learning and AI can detect and prevent them. It focuses on how deep learning/artificial learning techniques can be used for intrusion detection in networks and systems, analyze and classify malware, and identify potential sources of malware attacks. This book also explores AI's role in digital forensics investigations, including data recovery, incident response and management, real?time monitoring, automated response analysis, ethical and legal considerations, and visualization. By covering these topics, this book will provide a valuable resource for researchers, students, and cybersecurity and digital forensics professionals interested in learning about the latest advances in deep learning and AI techniques and their applications.

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Yes, you can access Digital Defence by Ahlad Kumar,Naveen Kumar Chaudhary,Apoorva S Shastri,Mangal Singh,Anand J. Kulkarni in PDF and/or ePUB format, as well as other popular books in Computer Science & Cyber Security. We have over one million books available in our catalogue for you to explore.

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Index

Cover
Half Title
Title Page
Copyright Page
Table of Contents
Preface
Editor Biographies
Contributors
Chapter 1 ◾ Artificial Intelligence for Cybersecurity—Fundamentals and Evaluation
Chapter 2 ◾ Predicting Tomorrow’s Threats: A Legal Framework for AI-Based Predictive Analytics in Cybersecurity
Chapter 3 ◾ The Invisible Defence: Detecting Zero-Day Threats with AI
Chapter 4 ◾ Fusion of Deep Architectures in Intent-Driven Networks for Intrusion Detection
Chapter 5 ◾ An In-depth Analysis of Intrusion Detection Systems with an Emphasis on Multi-Access Edge Computing and Machine Learning
Chapter 6 ◾ The Legal and Ethical Crossroads of Artificial Intelligence in Cybersecurity and Digital Forensics
Chapter 7 ◾ Multi-Factor Authentication for Smart Internet Transactions
Chapter 8 ◾ Adaptive Machine Learning Strategies for Next-Generation Botnet Host Detection
Chapter 9 ◾ Artificial Intelligence-Based Cybercrime Prevention and Data Security
Chapter 10 ◾ Insight into How Legal and Ethical Consideration Improve Artificial Intelligence Capabilities to Enhance the Performance of Cyber Forensic Accounting
Index

About this book

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Table of contents