This book covers a variety of topics that span from industry to academics: hybrid AI model for IDS in IoT, intelligent authentication framework for IoMT mobile devices for extracting bioelectrical signals, security audit in terms of vulnerability analysis to protect the electronic medical records in healthcare system using AI, classification using CNN a multi-face recognition attendance system with anti-spoofing capability, challenges in face morphing attack detection, a dimensionality reduction and feature-level fusion technique for morphing attack detection (MAD) systems, findings and discussion on AI-assisted forensics, challenges and open issues in the application of AI in forensics, a terrorist computational model that uses Baum–Welch optimization to improve the intelligence and predictive accuracy of the activities of criminal elements, a novel method for detecting security violations in IDSs, graphical-based city block distance algorithm method for E-payment systems, image encryption, and AI methods in ransomware mitigation and detection. It assists the reader in exploring new research areas, wherein AI can be applied to offer solutions through the contribution from researchers and academia.

The book provides a valuable reference for cyber security experts, digital forensic practitioners and network security professionals. In recent years, AI has gained substantial attention from researchers in both academia and industry, and as a result AI’s capabilities are constantly increasing at an extraordinary pace. AI is considered to be the Fourth Industrial Revolution or at least the next significant technological change after the evolution in mobile and cloud computing technologies. AI is a vehicle for improving the quality of our lives across every spectrum with a broad range of beneficial applications in various sectors. Notwithstanding its numerous beneficial use, AI simultaneously poses numerous legal, ethical, security and privacy challenges that are compounded by its malicious use by criminals. These challenges pose many risks to both our privacy and security at national, organisational and individual levels. In view of this, this book aims to help address some of these challenges focusing on the implication, impact and mitigations of the stated issues. The book provides a comprehensive coverage of not only the technical and ethical issues presented by the use of AI but also the adversarial application of AI and its associated implications. The authors recommend a number of novel approaches to assist in better detecting, thwarting and addressing AI challenges. The book also looks ahead and forecasts what attacks can be carried out in the future through the malicious use of the AI if sufficient defences are not implemented. The research contained in the book fits well into the larger body of work on various aspects of AI and cyber security. It is also aimed at researchers seeking to obtain a more profound knowledge of machine learning and deep learning in the context of cyber security, digital forensics and cybercrime. Furthermore, the book is an exceptional advanced text for Ph.D. and master’s degree programmes in cyber security, digital forensics, network security, cyber terrorism and computer science. Each chapter contributed to the book is written by an internationally renowned expert who has extensive experience in law enforcement, industry or academia. Furthermore, this book blends advanced research findings with practice-based methods to provide the reader with advanced understanding and relevant skills.

Digital forensics plays a crucial role in identifying, analysing, and presenting cyber threats as evidence in a court of law. Artificial intelligence, particularly machine learning and deep learning, enables automation of the digital investigation process. This book provides an in-depth look at the fundamental and advanced methods in digital forensics. It also discusses how machine learning and deep learning algorithms can be used to detect and investigate cybercrimes. This book demonstrates digital forensics and cyber-investigating techniques with real-world applications. It examines hard disk analytics and style architectures, including Master Boot Record and GUID Partition Table as part of the investigative process. It also covers cyberattack analysis in Windows, Linux, and network systems using virtual machines in real-world scenarios. Digital Forensics in the Era of Artificial Intelligence will be helpful for those interested in digital forensics and using machine learning techniques in the investigation of cyberattacks and the detection of evidence in cybercrimes.

This book provides readers with up-to-date research of emerging cyber threats and defensive mechanisms, which are timely and essential. It covers cyber threat intelligence concepts against a range of threat actors and threat tools (i.e. ransomware) in cutting-edge technologies, i.e., Internet of Things (IoT), Cloud computing and mobile devices. This book also provides the technical information on cyber-threat detection methods required for the researcher and digital forensics experts, in order to build intelligent automated systems to fight against advanced cybercrimes. The ever increasing number of cyber-attacks requires the cyber security and forensic specialists to detect, analyze and defend against the cyber threats in almost real-time, and with such a large number of attacks is not possible without deeply perusing the attack features and taking corresponding intelligent defensive actions – this in essence defines cyber threat intelligence notion. However, such intelligence would not be possible without the aid of artificial intelligence, machine learning and advanced data mining techniques to collect, analyze, and interpret cyber-attack campaigns which is covered in this book. This book will focus on cutting-edge research from both academia and industry, with a particular emphasis on providing wider knowledge of the field, novelty of approaches, combination of tools and so forth to perceive reason, learn and act on a wide range of data collected from different cyber security and forensics solutions. This book introduces the notion of cyber threat intelligence and analytics and presents different attempts in utilizing machine learning and data mining techniques to create threat feeds for a range of consumers. Moreover, this book sheds light on existing and emerging trends in the field which could pave the way for future works. The inter-disciplinary nature of this book, makes it suitable for a wide range of audiences with backgrounds in artificial intelligence, cyber security, forensics, big data and data mining, distributed systems and computer networks. This would include industry professionals, advanced-level students and researchers that work within these related fields.

This book provides a comprehensive analysis covering the confluence of Artificial Intelligence (AI), Cyber Forensics and Digital Policing in the context of the United Kingdom (UK), United States (US) and European Union (EU) national cybersecurity. More specifically, this book explores ways in which the adoption of AI algorithms (such as Machine Learning, Deep Learning, Natural Language Processing, and Big Data Predictive Analytics (BDPAs) transforms law enforcement agencies (LEAs) and intelligence service practices. It explores the roles that these technologies play in the manufacture of security, the threats to freedom and the levels of social control in the surveillance state. This book also examines the malevolent use of AI and associated technologies by state and non-state actors. Along with this analysis, it investigates the key legal, political, ethical, privacy and human rights implications of the national security uses of AI in the stated democracies. This book provides a set of policy recommendations to help to mitigate these challenges. Researchers working in the security field as well advanced level students in computer science focused on security will find this book useful as a reference. Cyber security professionals, network security analysts, police and law enforcement agencies will also want to purchase this book.

This book addresses the topics related to artificial intelligence, the Internet of Things, blockchain technology, and machine learning. It brings together researchers, developers, practitioners, and users interested in cybersecurity and forensics. The first objective is to learn and understand the need for and impact of advanced cybersecurity and forensics and its implementation with multiple smart computational technologies. This objective answers why and how cybersecurity and forensics have evolved as one of the most promising and widely-accepted technologies globally and has widely-accepted applications. The second objective is to learn how to use advanced cybersecurity and forensics practices to answer computational problems where confidentiality, integrity, and availability are essential aspects to handle and answer. This book is structured in such a way so that the field of study is relevant to each reader’s major or interests. It aims to help each reader see the relevance of cybersecurity and forensics to their career or interests. This book intends to encourage researchers to develop novel theories to enrich their scholarly knowledge to achieve sustainable development and foster sustainability. Readers will gain valuable knowledge and insights about smart computing technologies using this exciting book. This book: • Includes detailed applications of cybersecurity and forensics for real-life problems • Addresses the challenges and solutions related to implementing cybersecurity in multiple domains of smart computational technologies • Includes the latest trends and areas of research in cybersecurity and forensics • Offers both quantitative and qualitative assessments of the topics Includes case studies that will be helpful for the researchers Prof. Keshav Kaushik is Assistant Professor in the Department of Systemics, School of Computer Science at the University of Petroleum and Energy Studies, Dehradun, India. Dr. Shubham Tayal is Assistant Professor at SR University, Warangal, India. Dr. Akashdeep Bhardwaj is Professor (Cyber Security & Digital Forensics) at the University of Petroleum & Energy Studies (UPES), Dehradun, India. Dr. Manoj Kumar is Assistant Professor (SG) (SoCS) at the University of Petroleum and Energy Studies, Dehradun, India.

The future policing ought to cover identification of new assaults, disclosure of new ill-disposed patterns, and forecast of any future vindictive patterns from accessible authentic information. Such keen information will bring about building clever advanced proof handling frameworks that will help cops investigate violations. Artificial Intelligence for Cyber Defense and Smart Policing will describe the best way of practicing artificial intelligence for cyber defense and smart policing. Salient Features: • Combines AI for both cyber defense and smart policing in one place. • Covers novel strategies in future to help cybercrime examinations and police. • Discusses different AI models to fabricate more exact techniques. • Elaborates on problematization and international issues. • Includes case studies and real-life examples. This book is primarily aimed at graduates, researchers, and IT professionals. Business executives will also find this book helpful.