Digital Defence: Harnessing the Power of Artificial Intelligence for Cybersecurity and Digital Forensics

by Ahlad Kumar (Editor), Naveen Kumar Chaudhary (Editor), Apoorva S Shastri (Editor), Mangal Singh (Editor), Anand J. Kulkarni (Editor)

Overview

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.

Product Details

ISBN-13:	9781040342725
Publisher:	CRC Press
Publication date:	07/11/2025
Sold by:	Barnes & Noble
Format:	eBook
Pages:	188
File size:	6 MB

About the Author

Ahlad Kumar is currently serving as an Assistant Professor at the National Forensic Sciences University (Institute of National Importance) (Under the Home Ministry), Gandhinagar. Dr. Kumar has several papers published in well-renowned journals, including those of IEEE. His areas of interest include machine learning, deep learning, reinforcement learning, and analog design.

Naveen Kumar Chaudhary is a distinguished Professor of Cyber Security and Dean at the National Forensic Sciences University, Gandhinagar, India. He also heads the Training and International Relations Department and serves as Director of the NFSU, Goa Campus. Dr. Chaudhary has been recently appointed as a Courtesy Research Professor at Florida International University, Miami, USA. He held several key roles in the Government of India, including Director at the Ministry of External Affairs. Dr. Chaudhary has made significant contributions to policy formulation, ICT projects, and cybersecurity education globally.

Apoorva S Shastri holds a PhD in Optimization Algorithms and Applications from Symbiosis International (Deemed University). Currently, she is a Research Assistant Professor at Institute of Artificial Intelligence at the Dr Vishwanath Karad MITWPU, Pune, India. Her research interests include optimization algorithms, VLSI design, multi-objective optimization, continuous, discrete, and combinatorial optimization, complex systems, manufacturing, and self-organizing systems.

Mangal Singh is working as an Associate Professor, Electronics & Telecommunication Engineering at Symbiosis Institute of Technology, Symbiosis International (Deemed University), Pune. He has an experience of more than 23 years in the field of Teaching, Research and Administration. He is a Senior Member of IEEE and life member of the IETE and ISTE, India.

Anand J Kulkarni holds a PhD in Optimization from Nanyang Technological University, Singapore, MS in AI from University of Regina, Canada. He worked as Research Fellow at University of Windsor, Canada. He is the founder of OAT Research Lab and has published over 80 research papers along with 23 books.

Table of Contents

Chapter 1 ◾ Artificial Intelligence for Cybersecurity—Fundamentals and Evaluation

Rasmita Kumari Mohanty, Satya Prakash Sahoo, Manas Ranjan Kabat, and Basim Alhadidi

Chapter 2 ◾ Predicting Tomorrow’s Threats: A Legal Framework for AI‑Based Predictive Analytics in Cybersecurity

Sarvesh Nimbulkar and Souradeep Rakshit

Chapter 3 ◾ The Invisible Defence: Detecting Zero‑Day Threats with AI

Debojyoti Gupta

Chapter 4 ◾ Fusion of Deep Architectures in Intent‑Driven Networks for Intrusion Detection

Obinna Johnbosco Awoke, Rajesh Prasad, Ndubuisi Godcares, and Najeeb Saiyed

Chapter 5 ◾ An In‑depth Analysis of Intrusion Detection Systems with an Emphasis on Multi‑Access Edge Computing and Machine Learning

Shruti Saxena and Nikunj Tahilramani

Chapter 6 ◾ The Legal and Ethical Crossroads of Artificial Intelligence in Cybersecurity and Digital Forensics

Gyanendra Tiwari, Khushi Pandey, Manali Desai, Vinayak Musale, Dhanashri Wategaonkar, and Mangesh Bedekar

Chapter 7 ◾ Multi‑Factor Authentication for Smart Internet Transactions

B. Madhu, B.N. Shubhada, and Shubham Kumar Saras

Chapter 8 ◾ Adaptive Machine Learning Strategies for Next‑Generation Botnet Host Detection

Aniket Jhariya, Dhvani Parekh, Anurag Mogal, Joshua Lobo, and Mangal Singh

Chapter 9 ◾ Artificial Intelligence‑Based Cybercrime Prevention and Data Security

Srinivasa Rao Gundu, Panem Charanarur, and J. Vijaylaxmi

Chapter 10 ◾ Insight into How Legal and Ethical Consideration Improve Artificial Intelligence Capabilities to Enhance the Performance of Cyber Forensic Accounting

Pham Quang Huy and M.A. Vu Kien Phuc