This book offers a groundbreaking exploration of how Artificial Intelligence is revolutionizing cybersecurity and digital forensics. It covers a wide range of topics, from AI-based threat detection and zero-day vulnerability defense to legal frameworks and ethical considerations in cybercrime investigations.
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.
Chapter 1 Artificial Intelligence for CybersecurityFundamentals and
Evaluation
Rasmita Kumari Mohanty, Satya Prakash Sahoo, Manas Ranjan Kabat, and Basim
Alhadidi
Chapter 2 Predicting Tomorrows Threats: A Legal Framework for AIBased
Predictive Analytics in Cybersecurity
Sarvesh Nimbulkar and Souradeep Rakshit
Chapter 3 The Invisible Defence: Detecting ZeroDay Threats with AI
Debojyoti Gupta
Chapter 4 Fusion of Deep Architectures in IntentDriven Networks for
Intrusion Detection
Obinna Johnbosco Awoke, Rajesh Prasad, Ndubuisi Godcares, and Najeeb Saiyed
Chapter 5 An Indepth Analysis of Intrusion Detection Systems with an
Emphasis on MultiAccess 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 MultiFactor Authentication for Smart Internet Transactions
B. Madhu, B.N. Shubhada, and Shubham Kumar Saras
Chapter 8 Adaptive Machine Learning Strategies for NextGeneration Botnet
Host Detection
Aniket Jhariya, Dhvani Parekh, Anurag Mogal, Joshua Lobo, and Mangal Singh
Chapter 9 Artificial IntelligenceBased 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
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.
