Download Free Digital Forensics In The Era Of Artificial Intelligence Book in PDF and EPUB Free Download. You can read online Digital Forensics In The Era Of Artificial Intelligence and write the review.

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.
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.
ARTIFICIAL INTELLIGENCE (AI) IN FORENSIC SCIENCES Foundational text for teaching and learning within the field of Artificial Intelligence (AI) as it applies to forensic science Artificial Intelligence (AI) in Forensic Sciences presents an overview of the state-of-the-art applications of Artificial Intelligence within Forensic Science, covering issues with validation and new crimes that use AI; issues with triage, preselection, identification, argumentation and explain ability; demonstrating uses of AI in forensic science; and providing discussions on bias when using AI. The text discusses the challenges for the legal presentation of AI data and interpretation and offers solutions to this problem while addressing broader practical and emerging issues in a growing area of interest in forensics. It builds on key developing areas of focus in academic and government research, providing an authoritative and well-researched perspective. Compiled by two highly qualified editors with significant experience in the field, and part of the Wiley — AAFS series ‘Forensic Science in Focus’, Artificial Intelligence (AI) in Forensic Sciences includes information on: Cyber IoT, fundamentals on AI in forensic science, speaker and facial comparison, and deepfake detection Digital-based evidence creation, 3D and AI, interoperability of standards, and forensic audio and speech analysis Text analysis, video and multimedia analytics, reliability, privacy, network forensics, intelligence operations, argumentation support in court, and case applications Identification of genetic markers, current state and federal legislation with regards to AI, and forensics and fingerprint analysis Providing comprehensive coverage of the subject, Artificial Intelligence (AI) in Forensic Sciences is an essential advanced text for final year undergraduates and master’s students in forensic science, as well as universities teaching forensics (police, IT security, digital science and engineering), forensic product vendors and governmental and cyber security agencies.
Digital forensics is the science of detecting evidence from digital media like a computer, smartphone, server, or network. It provides the forensic team with the most beneficial methods to solve confused digital-related cases. AI and blockchain can be applied to solve online predatory chat cases and photo forensics cases, provide network service evidence, custody of digital files in forensic medicine, and identify roots of data scavenging. The increased use of PCs and extensive use of internet access, have meant easy availability of hacking tools. Over the past two decades, improvements in the information technology landscape have made the collection, preservation, and analysis of digital evidence extremely important. The traditional tools for solving cybercrimes and preparing court cases are making investigations difficult. We can use AI and blockchain design frameworks to make the digital forensic process efficient and straightforward. AI features help determine the contents of a picture, detect spam email messages and recognize swatches of hard drives that could contain suspicious files. Blockchain-based lawful evidence management schemes can supervise the entire evidence flow of all of the court data. This book provides a wide-ranging overview of how AI and blockchain can be used to solve problems in digital forensics using advanced tools and applications available on the market.
Artificial Intelligence in Forensic Science addresses the current and emerging opportunities being utilized to apply modern Artificial Intelligence (AI) technologies to current forensic and investigation practices. The book also showcases the increasing benefits of AI where and when it can be applied to various techniques and forensic disciplines. The increasing rate of sophisticated crimes has increased the opportunity and need for the forensic field to explore a variety of emerging technologies to counter criminals—and AI is no exception. There are many current investigative challenges that, with ingenuity and application, can be helped with the application of AI, especially in the digital forensic and cyber-crime arena. The book also explains many practical studies that have been carried out to test AI technologies in crime detection, uncovering evidence, and identifying perpetrators. In the last decade, the use of AI has become common in many fields and now is an ideal time to look at the various ways AI can be integrated into judicial, forensic, and criminal cases to better collect and analyze evidence, thereby improving outcomes.
Developing a knowledge model helps to formalize the difficult task of analyzing crime incidents in addition to preserving and presenting the digital evidence for legal processing. The use of data analytics techniques to collect evidence assists forensic investigators in following the standard set of forensic procedures, techniques, and methods used for evidence collection and extraction. Varieties of data sources and information can be uniquely identified, physically isolated from the crime scene, protected, stored, and transmitted for investigation using AI techniques. With such large volumes of forensic data being processed, different deep learning techniques may be employed. Confluence of AI, Machine, and Deep Learning in Cyber Forensics contains cutting-edge research on the latest AI techniques being used to design and build solutions that address prevailing issues in cyber forensics and that will support efficient and effective investigations. This book seeks to understand the value of the deep learning algorithm to handle evidence data as well as the usage of neural networks to analyze investigation data. Other themes that are explored include machine learning algorithms that allow machines to interact with the evidence, deep learning algorithms that can handle evidence acquisition and preservation, and techniques in both fields that allow for the analysis of huge amounts of data collected during a forensic investigation. This book is ideally intended for forensics experts, forensic investigators, cyber forensic practitioners, researchers, academicians, and students interested in cyber forensics, computer science and engineering, information technology, and electronics and communication.
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.
Introduction to AI in Forensic Investigation 1.1 Historical Context Forensic investigation, the art and science of solving crimes, has a rich and storied history. It dates back centuries, with ancient civilizations employing rudimentary forensic techniques to resolve disputes and administer justice. The evolution of forensic investigation parallels the development of human societies. We'll journey through time, exploring the milestones in forensic science, from fingerprints in ancient Babylon to the first recorded use of blood splatter analysis in the early 19th century. Understanding this history provides a crucial backdrop for comprehending how AI is reshaping the field. 1.2 The Emergence of Artificial Intelligence The 20th century saw remarkable advancements in technology, including the development of computers and artificial intelligence. AI, once a subject of science fiction, became a tangible reality. The principles of machine learning and neural networks laid the foundation for AI's integration into diverse fields, including forensics. In this section, we'll trace AI's journey from its conceptualization to its current capabilities. We'll explore how the convergence of data, computing power, and algorithmic innovation has made AI a game-changer in forensic investigations. Introduction to AI in Forensic Investigation 1.1 Historical Context Forensic investigation, the art and science of solving crimes, has a rich and storied history. It dates back centuries, with ancient civilizations employing rudimentary forensic techniques to resolve disputes and administer justice. The evolution of forensic investigation parallels the development of human societies. We'll journey through time, exploring the milestones in forensic science, from fingerprints in ancient Babylon to the first recorded use of blood splatter analysis in the early 19th century. Understanding this history provides a crucial backdrop for comprehending how AI is reshaping the field. 1.2 The Emergence of Artificial Intelligence The 20th century saw remarkable advancements in technology, including the development of computers and artificial intelligence. AI, once a subject of science fiction, became a tangible reality. The principles of machine learning and neural networks laid the foundation for AI's integration into diverse fields, including forensics. In this section, we'll trace AI's journey from its conceptualization to its current capabilities. We'll explore how the convergence of data, computing power, and algorithmic innovation has made AI a game-changer in forensic investigations. 1. Introduction to AI in Forensic Investigation 2. Historical Perspective: How Forensics Evolved 3. The Power of Data: AI and Digital Forensics 4. Image and Video Analysis with AI 5. AI's Role in Fingerprint and Biometric Identification 6. Text and Speech Analysis in Forensic Linguistics 7. AI-Enhanced Crime Scene Analysis 8. Cyber security and AI: Tracing Digital Footprints 9. DNA Sequencing and Analysis with Artificial Intelligence 10. Document Forgery Detection with Machine Learning 11. AI in Ballistics and Firearms Identification 12. Behavioral Analysis and Profiling with AI 13. Case Studies: Real-Life Examples of AI in Forensics 14. Ethical Considerations and Challenges in AI Forensics 15. The Future of AI in Forensic Investigation
This book delivers insights into how social science and technology might aid new advancements in managing the complexity inherent within national and international security landscape. The digital policing landscape is dynamic and intricate, emanating from crimes that are both persistent and transnational. Globalization, human and drug trafficking, cybercrime, terrorism, and other forms of transnational crime can have a significant impact on societies around the world. This necessitates a reassessment of what crime, national security, and policing mean. Recent global events such as human and drug trafficking, the COVID-19 pandemic, violent protests, cyber threats, and terrorist activities underline vulnerabilities residing in our current security and digital policing posture. As an interdisciplinary collection of studies, this book encapsulates concepts, theories, and technology applications, offering a comprehensive analysis of current and emerging trends and threats within the context of national and international security. Undertaking an evidence-based approach, this book offers an extraordinarily perceptive and detailed account of issues and solutions related to the complex national and international security landscape. To this end, the book: presents insights into emerging and potential technological and methodological solutions as well as advancements in relation to integrated computational and analytical solutions that could be deployed for the purposes of national and international security; provides a comprehensive analysis of technical, ethical, legal, privacy, and civil liberty challenges stemming from the aforementioned advancements; and, accordingly, offers detailed recommendations supporting the design and implementation of best practices including technical, ethical, and legal approaches for national and international security uses. The research contained in the book fits well into the larger body of work on various aspects of AI, cybersecurity, national security, digital forensics, cyberterrorism, ethics, human rights, cybercrime, and law. It provides a valuable reference for LEAs and security organizations, policymakers, cybersecurity experts, digital forensic practitioners, researchers, academicians, graduates and advanced undergraduates, and other stakeholders with an interest in national and global security.