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| artificial intelligence in forensic science: Artificial Intelligence (AI) in Forensic Sciences Zeno Geradts, Katrin Franke, 2024-01-29 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. |
| artificial intelligence in forensic science: Artificial Intelligence in Forensic Science Kavita Saini, Swaroop S. Sonone, Mahipal Singh Sankhla, Naveen Kumar, 2024-08-26 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. |
| artificial intelligence in forensic science: Machine Learning Forensics for Law Enforcement, Security, and Intelligence Jesus Mena, 2016-04-19 Increasingly, crimes and fraud are digital in nature, occurring at breakneck speed and encompassing large volumes of data. To combat this unlawful activity, knowledge about the use of machine learning technology and software is critical. Machine Learning Forensics for Law Enforcement, Security, and Intelligence integrates an assortment of deductive |
| artificial intelligence in forensic science: Critical Concepts, Standards, and Techniques in Cyber Forensics Husain, Mohammad Shahid, Khan, Mohammad Zunnun, 2019-11-22 Advancing technologies, especially computer technologies, have necessitated the creation of a comprehensive investigation and collection methodology for digital and online evidence. The goal of cyber forensics is to perform a structured investigation while maintaining a documented chain of evidence to find out exactly what happened on a computing device or on a network and who was responsible for it. Critical Concepts, Standards, and Techniques in Cyber Forensics is a critical research book that focuses on providing in-depth knowledge about online forensic practices and methods. Highlighting a range of topics such as data mining, digital evidence, and fraud investigation, this book is ideal for security analysts, IT specialists, software engineers, researchers, security professionals, criminal science professionals, policymakers, academicians, and students. |
| artificial intelligence in forensic science: Confluence of AI, Machine, and Deep Learning in Cyber Forensics Misra, Sanjay, Arumugam, Chamundeswari, Jaganathan, Suresh, S., Saraswathi, 2020-12-18 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. |
| artificial intelligence in forensic science: Cyber Security and Digital Forensics Sabyasachi Pramanik, Mangesh M. Ghonge, Ramchandra Mangrulkar, Dac-Nhuong Le, 2022-01-12 CYBER SECURITY AND DIGITAL FORENSICS Cyber security is an incredibly important issue that is constantly changing, with new methods, processes, and technologies coming online all the time. Books like this are invaluable to professionals working in this area, to stay abreast of all of these changes. Current cyber threats are getting more complicated and advanced with the rapid evolution of adversarial techniques. Networked computing and portable electronic devices have broadened the role of digital forensics beyond traditional investigations into computer crime. The overall increase in the use of computers as a way of storing and retrieving high-security information requires appropriate security measures to protect the entire computing and communication scenario worldwide. Further, with the introduction of the internet and its underlying technology, facets of information security are becoming a primary concern to protect networks and cyber infrastructures from various threats. This groundbreaking new volume, written and edited by a wide range of professionals in this area, covers broad technical and socio-economic perspectives for the utilization of information and communication technologies and the development of practical solutions in cyber security and digital forensics. Not just for the professional working in the field, but also for the student or academic on the university level, this is a must-have for any library. Audience: Practitioners, consultants, engineers, academics, and other professionals working in the areas of cyber analysis, cyber security, homeland security, national defense, the protection of national critical infrastructures, cyber-crime, cyber vulnerabilities, cyber-attacks related to network systems, cyber threat reduction planning, and those who provide leadership in cyber security management both in public and private sectors |
| artificial intelligence in forensic science: Artificial Intelligence for Audit, Forensic Accounting, and Valuation Al Naqvi, 2020-08-25 Strategically integrate AI into your organization to compete in the tech era The rise of artificial intelligence is nothing short of a technological revolution. AI is poised to completely transform accounting and auditing professions, yet its current application within these areas is limited and fragmented. Existing AI implementations tend to solve very narrow business issues, rather than serving as a powerful tech framework for next-generation accounting. Artificial Intelligence for Audit, Forensic Accounting, and Valuation provides a strategic viewpoint on how AI can be comprehensively integrated within audit management, leading to better automated models, forensic accounting, and beyond. No other book on the market takes such a wide-ranging approach to using AI in audit and accounting. With this guide, you’ll be able to build an innovative, automated accounting strategy, using artificial intelligence as the cornerstone and foundation. This is a must, because AI is quickly growing to be the single competitive factor for audit and accounting firms. With better AI comes better results. If you aren’t integrating AI and automation in the strategic DNA of your business, you’re at risk of being left behind. See how artificial intelligence can form the cornerstone of integrated, automated audit and accounting services Learn how to build AI into your organization to remain competitive in the era of automation Go beyond siloed AI implementations to modernize and deliver results across the organization Understand and overcome the governance and leadership challenges inherent in AI strategy Accounting and auditing firms need a comprehensive framework for intelligent, automation-centric modernization. Artificial Intelligence for Audit, Forensic Accounting, and Valuation delivers just that—a plan to evolve legacy firms by building firmwide AI capabilities. |
| artificial intelligence in forensic science: Technology in Forensic Science Deepak Rawtani, Chaudhery Mustansar Hussain, 2020-11-02 The book Technology in Forensic Science provides an integrated approach by reviewing the usage of modern forensic tools as well as the methods for interpretation of the results. Starting with best practices on sample taking, the book then reviews analytical methods such as high-resolution microscopy and chromatography, biometric approaches, and advanced sensor technology as well as emerging technologies such as nanotechnology and taggant technology. It concludes with an outlook to emerging methods such as AI-based approaches to forensic investigations. |
| artificial intelligence in forensic science: Aiding Forensic Investigation Through Deep Learning and Machine Learning Frameworks Raj, Alex Noel Joseph, Mahesh, Vijayalakshmi G. V., Nerssison, Ruban, Yu, Ang, Gentry, Jennifer, 2022-06-24 It is crucial that forensic science meets challenges such as identifying hidden patterns in data, validating results for accuracy, and understanding varying criminal activities in order to be authoritative so as to hold up justice and public safety. Artificial intelligence, with its potential subsets of machine learning and deep learning, has the potential to transform the domain of forensic science by handling diverse data, recognizing patterns, and analyzing, interpreting, and presenting results. Machine Learning and deep learning frameworks, with developed mathematical and computational tools, facilitate the investigators to provide reliable results. Further study on the potential uses of these technologies is required to better understand their benefits. Aiding Forensic Investigation Through Deep Learning and Machine Learning Frameworks provides an outline of deep learning and machine learning frameworks and methods for use in forensic science to produce accurate and reliable results to aid investigation processes. The book also considers the challenges, developments, advancements, and emerging approaches of deep learning and machine learning. Covering key topics such as biometrics, augmented reality, and fraud investigation, this reference work is crucial for forensic scientists, law enforcement, computer scientists, researchers, scholars, academicians, practitioners, instructors, and students. |
| artificial intelligence in forensic science: Artificial Intelligence, Computational Modelling and Criminal Proceedings Serena Quattrocolo, 2020-08-27 This book discusses issues relating to the application of AI and computational modelling in criminal proceedings from a European perspective. Part one provides a definition of the topics. Rather than focusing on policing or prevention of crime – largely tackled by recent literature – it explores ways in which AI can affect the investigation and adjudication of crime. There are two main areas of application: the first is evidence gathering, which is addressed in Part two. This section examines how traditional evidentiary law is affected by both new ways of investigation – based on automated processes (often using machine learning) – and new kinds of evidence, automatically generated by AI instruments. Drawing on the comprehensive case law of the European Court of Human Rights, it also presents reflections on the reliability and, ultimately, the admissibility of such evidence. Part three investigates the second application area: judicial decision-making, providing an unbiased review of the meaning, benefits, and possible long-term effects of ‘predictive justice’ in the criminal field. It highlights the prediction of both violent behaviour, or recidivism, and future court decisions, based on precedents. Touching on the foundations of common law and civil law traditions, the book offers insights into the usefulness of ‘prediction’ in criminal proceedings. |
| artificial intelligence in forensic science: Machine Learning for Authorship Attribution and Cyber Forensics Farkhund Iqbal, Mourad Debbabi, Benjamin C. M. Fung, 2020-12-04 The book first explores the cybersecurity’s landscape and the inherent susceptibility of online communication system such as e-mail, chat conversation and social media in cybercrimes. Common sources and resources of digital crimes, their causes and effects together with the emerging threats for society are illustrated in this book. This book not only explores the growing needs of cybersecurity and digital forensics but also investigates relevant technologies and methods to meet the said needs. Knowledge discovery, machine learning and data analytics are explored for collecting cyber-intelligence and forensics evidence on cybercrimes. Online communication documents, which are the main source of cybercrimes are investigated from two perspectives: the crime and the criminal. AI and machine learning methods are applied to detect illegal and criminal activities such as bot distribution, drug trafficking and child pornography. Authorship analysis is applied to identify the potential suspects and their social linguistics characteristics. Deep learning together with frequent pattern mining and link mining techniques are applied to trace the potential collaborators of the identified criminals. Finally, the aim of the book is not only to investigate the crimes and identify the potential suspects but, as well, to collect solid and precise forensics evidence to prosecute the suspects in the court of law. |
| artificial intelligence in forensic science: Forensic Science E-Magazine (Jan-2024) Archana Singh, 2024-02-12 We proudly present the January issue (Vol 19) of your favorite magazine, Forensic Science E-Magazine. As usual, the magazine's current issue has helpful content related to forensic science. Our editorial team works diligently to deliver the study material while keeping in mind the needs of our valued readers. We are confident that if you read it attentively and patiently, it will go a long way toward giving you the information you need to tackle the difficult process of the exams and study and bring you certain knowledge and victory. Reputable authors have provided several important pieces on forensic science and science in the current edition. A variety of questions collected from various competitive exams are included in the magazine's most important section. Contents: Flow Chart Of Forensic Science: A Broad Overview Article On Cryptography and Network Security in Digital Forensics MCQs On Digital Forensics Flowchart for Forensic Ballistic Analysis: A Broad Overview Artificial Intelligence Technology and Forensic Science MCQs On Artificial Intelligence and Forensic Science Flowchart of Crime scene investigation: A Broad Overview Psychological Autopsy: Need of Forensic Psychology MCQs on Psychological Autopsy Flowchart for a Homicide Investigation: A Broad Overview Identification With Earprints: A Unique Form Of Forensic Evidence MCQs on Earprints Flowchart for Fingerprint Analysis: A Broad Overview |
| artificial intelligence in forensic science: Computational Forensics Sargur N. Srihari, Katrin Franke, 2008-08-04 This Lecture Notes in Computer Science (LNCS) volume contains the papers presented at the Second International Workshop on Computational Forensics (IWCF 2008), held August 7–8, 2008. It was a great honor for the organizers to host this scienti?c event at the renowned National Academy of Sciences: Keck Center in Washington, DC, USA. Computational Forensics is an emerging research domain focusing on the investigation of forensic problems using computational methods. Its primary goalis the discoveryand advancement of forensicknowledgeinvolving modeling, computer simulation, and computer-based analysis and recognition in studying and solving forensic problems. The Computational Forensics workshop series is intended as a forum for researchers and practitioners in all areas of computational and forensic sciences. This forum discusses current challenges in computer-assisted forensic investi- tions and presents recent progress and advances. IWCF addresses a broad spectrum of forensic disciplines that use computer tools for criminal investigation. This year’s edition covers presentations on c- putational methods for individuality studies, computer-based3D processing and analysis of skulls and human bodies, shoe print preprocessing and analysis, n- ural language analysis and information retrieval to support law enforcement, analysis and group visualization of speech recordings, scanner and print device forensics, and computer-based questioned document and signature analysis. |
| artificial intelligence in forensic science: Artificial Intelligence and Blockchain in Digital Forensics P. Karthikeyan, Hari Mohan Pande, Velliangiri Sarveshwaran, 2023-02-06 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: Judicial Applications of Artificial Intelligence Giovanni Sartor, Karl Branting, 1998-12-31 The judiciary is in the early stages of a transformation in which AI (Artificial Intelligence) technology will help to make the judicial process faster, cheaper, and more predictable without compromising the integrity of judges' discretionary reasoning. Judicial decision-making is an area of daunting complexity, where highly sophisticated legal expertise merges with cognitive and emotional competence. How can AI contribute to a process that encompasses such a wide range of knowledge, judgment, and experience? Rather than aiming at the impossible dream (or nightmare) of building an automatic judge, AI research has had two more practical goals: producing tools to support judicial activities, including programs for intelligent document assembly, case retrieval, and support for discretionary decision-making; and developing new analytical tools for understanding and modeling the judicial process, such as case-based reasoning and formal models of dialectics, argumentation, and negotiation. Judges, squeezed between tightening budgets and increasing demands for justice, are desperately trying to maintain the quality of their decision-making process while coping with time and resource limitations. Flexible AI tools for decision support may promote uniformity and efficiency in judicial practice, while supporting rational judicial discretion. Similarly, AI may promote flexibility, efficiency and accuracy in other judicial tasks, such as drafting various judicial documents. The contributions in this volume exemplify some of the directions that the AI transformation of the judiciary will take. |
| artificial intelligence in forensic science: Artificial Intelligence for Cyber Defense and Smart Policing S Vijayalakshmi, P Durgadevi, Lija Jacob, Balamurugan Balusamy, Parma Nand, 2024-03-19 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. |
| artificial intelligence in forensic science: Artificial intelligence in forensic microbiology Chen Li, Yu-Dong Yao, Jiangwei Yan, Marcin Grzegorzek, 2023-05-02 |
| artificial intelligence in forensic science: Applying Artificial Intelligence in Cybersecurity Analytics and Cyber Threat Detection Shilpa Mahajan, Mehak Khurana, Vania Vieira Estrela, 2024-06-12 Comprehensive resource providing strategic defense mechanisms for malware, handling cybercrime, and identifying loopholes using artificial intelligence (AI) and machine learning (ML) Applying Artificial Intelligence in Cyber Security Analytics and Cyber Threat Detection is a comprehensive look at state-of-the-art theory and practical guidelines pertaining to the subject, showcasing recent innovations, emerging trends, and concerns as well as applied challenges encountered, and solutions adopted in the fields of cybersecurity using analytics and machine learning. The text clearly explains theoretical aspects, framework, system architecture, analysis and design, implementation, validation, and tools and techniques of data science and machine learning to detect and prevent cyber threats. Using AI and ML approaches, the book offers strategic defense mechanisms for addressing malware, cybercrime, and system vulnerabilities. It also provides tools and techniques that can be applied by professional analysts to safely analyze, debug, and disassemble any malicious software they encounter. With contributions from qualified authors with significant experience in the field, Applying Artificial Intelligence in Cyber Security Analytics and Cyber Threat Detection explores topics such as: Cybersecurity tools originating from computational statistics literature and pure mathematics, such as nonparametric probability density estimation, graph-based manifold learning, and topological data analysis Applications of AI to penetration testing, malware, data privacy, intrusion detection system (IDS), and social engineering How AI automation addresses various security challenges in daily workflows and how to perform automated analyses to proactively mitigate threats Offensive technologies grouped together and analyzed at a higher level from both an offensive and defensive standpoint Providing detailed coverage of a rapidly expanding field, Applying Artificial Intelligence in Cyber Security Analytics and Cyber Threat Detection is an essential resource for a wide variety of researchers, scientists, and professionals involved in fields that intersect with cybersecurity, artificial intelligence, and machine learning. |
| artificial intelligence in forensic science: Cyber Warfare and Terrorism: Concepts, Methodologies, Tools, and Applications Management Association, Information Resources, 2020-03-06 Through the rise of big data and the internet of things, terrorist organizations have been freed from geographic and logistical confines and now have more power than ever before to strike the average citizen directly at home. This, coupled with the inherently asymmetrical nature of cyberwarfare, which grants great advantage to the attacker, has created an unprecedented national security risk that both governments and their citizens are woefully ill-prepared to face. Examining cyber warfare and terrorism through a critical and academic perspective can lead to a better understanding of its foundations and implications. Cyber Warfare and Terrorism: Concepts, Methodologies, Tools, and Applications is an essential reference for the latest research on the utilization of online tools by terrorist organizations to communicate with and recruit potential extremists and examines effective countermeasures employed by law enforcement agencies to defend against such threats. Highlighting a range of topics such as cyber threats, digital intelligence, and counterterrorism, this multi-volume book is ideally designed for law enforcement, government officials, lawmakers, security analysts, IT specialists, software developers, intelligence and security practitioners, students, educators, and researchers. |
| artificial intelligence in forensic science: Forensic Science and Humanitarian Action Roberto C. Parra, Sara C. Zapico, Douglas H. Ubelaker, 2020-01-22 Widens traditional concepts of forensic science to include humanitarian, social, and cultural aspects Using the preservation of the dignity of the deceased as its foundation, Forensic Science and Humanitarian Action: Interacting with the Dead and the Living is a unique examination of the applications of humanitarian forensic science. Spanning two comprehensive volumes, the text is sufficiently detailed for forensic practitioners, yet accessible enough for non-specialists, and discusses both the latest technologies and real-world interactions. Arranged into five sections, this book addresses the ‘management of the dead’ across five major areas in humanitarian forensic science. Volume One presents the first three of these areas: History, Theory, Practice, and Legal Foundation; Basic Forensic Information to Trace Missing Persons; and Stable Isotopes Forensics. Topics covered include: Protection of The Missing and the Dead Under International Law Social, Cultural and Religious Factors in Humanitarian Forensic Science Posthumous Dignity and the Importance in Returning Remains of the Deceased The New Disappeared – Migration and Forensic Science Stable Isotope Analysis in Forensic Anthropology Volume Two covers two further areas of interest: DNA Analysis and the Forensic Identification Process. It concludes with a comprehensive set of case studies focused on identifying the deceased, and finding missing persons from around the globe, including: Forensic Human Identification from an Australian Perspective Skeletal Remains and Identification Processing at the FBI Migrant Deaths along the Texas/Mexico Border Humanitarian Work in Cyprus by The Committee on Missing Persons (CMP) Volcán De Fuego Eruption – Natural Disaster Response from Guatemala Drawing upon a wide range of contributions from respected academics working in the field, Forensic Science and Humanitarian Action is a unique reference for forensic practitioners, communities of humanitarian workers, human rights defenders, and government and non-governmental officials. |
| artificial intelligence in forensic science: Digital Forensic Science B Suresh Shetty, Pavanchand Shetty, 2020-09-30 It is our pleasure to place before you the book Digital Forensic Science. This book makes up a major part of the broad specialty of Digital Forensic Science, comprising mainly of tools and technologies of cyber forensic experts for their future practice. This book has been designed to merge a range of new ideas and unique works of authors from topics like fundamental principles of forensic cyber analysis, and protocols and rules needed for the best digital forensics. We hope that it will be useful to practitioners of forensic medicine, experts, cyber experts, law makers, investigating authorities, and undergraduate and postgraduate medical school graduates of medicine. |
| artificial intelligence in forensic science: Forensic Human Identification Tim Thompson, Sue Black, 2006-11-14 Identity theft, criminal investigations of the dead or missing, mass disasters both by natural causes and by criminal intent with this as our day to day reality, the establishment and verification of human identity has never been more important or more prominent in our society. Maintaining and protecting the integrity of out identity has reached |
| artificial intelligence in forensic science: Social Network Forensics, Cyber Security, and Machine Learning P. Venkata Krishna, Sasikumar Gurumoorthy, Mohammad S. Obaidat, 2018-12-29 This book discusses the issues and challenges in Online Social Networks (OSNs). It highlights various aspects of OSNs consisting of novel social network strategies and the development of services using different computing models. Moreover, the book investigates how OSNs are impacted by cutting-edge innovations. |
| artificial intelligence in forensic science: Illustrated Guide to Home Forensic Science Experiments Robert Bruce Thompson, Barbara Fritchman Thompson, 2012-08-07 Have you ever wondered whether the forensic science you’ve seen on TV is anything like the real thing? There’s no better way to find out than to roll up your sleeves and do it yourself. This full-color book offers advice for setting up an inexpensive home lab, and includes more than 50 hands-on lab sessions that deal with forensic science experiments in biology, chemistry, and physics. You’ll learn the practical skills and fundamental knowledge needed to pursue forensics as a lifelong hobby—or even a career. The forensic science procedures in this book are not merely educational, they’re the real deal. Each chapter includes one or more lab sessions devoted to a particular topic. You’ll find a complete list of equipment and chemicals you need for each session. Analyze soil, hair, and fibers Match glass and plastic specimens Develop latent fingerprints and reveal blood traces Conduct drug and toxicology tests Analyze gunshot and explosives residues Detect forgeries and fakes Analyze impressions, such as tool marks and footprints Match pollen and diatom samples Extract, isolate, and visualize DNA samples Through their company, The Home Scientist, LLC (thehomescientist.com/forensics), the authors also offer inexpensive custom kits that provide specialized equipment and supplies you’ll need to complete the experiments. Add a microscope and some common household items and you’re good to go. |
| artificial intelligence in forensic science: Driving Forensic Innovation in the 21st Century Simona Francese, |
| artificial intelligence in forensic science: AI Detective: Solving Crimes with Artificial Intelligence Daniel D. Lee, 2024-05-07 AI Detective: Solving Crimes with Artificial Intelligence is an in-depth exploration of the transformative impact artificial intelligence (AI) has on law enforcement and crime-solving. This book provides a comprehensive analysis of how AI technologies are reshaping the landscape of public safety, from predictive policing to forensic analysis, highlighting both the opportunities and challenges these innovations present. Throughout its detailed chapters, the book examines the integration of AI in various facets of law enforcement, including its role in enhancing investigative techniques, improving data analysis, and optimizing resource allocation. Readers will delve into how AI aids in real-time crime mapping, facial recognition, and the rapid analysis of massive datasets, which enables law enforcement agencies to anticipate criminal activity and efficiently deploy preventive measures. The book also addresses the ethical and privacy concerns associated with AI in law enforcement, such as potential biases in AI algorithms and the implications of surveillance technologies. It discusses the balance between enhancing security and protecting individual privacy rights, offering insights into the ongoing debate among policymakers, law enforcement officials, and civil rights advocates. AI Detective extends beyond just theoretical discussions, presenting case studies and real-world examples where AI has been successfully implemented to solve crimes and enhance public safety. These examples not only illustrate the practical applications of AI but also highlight the evolving nature of crime in the digital age and how law enforcement must adapt to keep pace with technological advancements. This book is an essential resource for anyone interested in the intersection of technology and law enforcement, including students, professionals in the field, and technology enthusiasts. It offers a forward-looking perspective on the future challenges and possibilities that AI presents for crime-solving and public safety. By providing a balanced discussion on the benefits and potential drawbacks of AI in policing, AI Detective serves as a crucial guide for understanding how AI will continue to influence law enforcement practices in the years to come. |
| artificial intelligence in forensic science: Advances in Information and Communication Kohei Arai, 2023-03-01 This book gathers the proceedings of the eighth Future of Information and Computing Conference, which was held successfully in virtual mode. It received a total of 369 paper submissions from renowned and budding scholars, academics, and distinguished members of the industry. The topics fanned across various fields involving computing, Internet of Things, data science, and artificial intelligence. Learned scholars from all walks of life assembled under one roof to share their unique, original, and breakthrough researches and paved a new technological path for the world. Many of the studies seek to change the face of the world itself. Their innovative thinking indeed aims to solve several gruesome problems in the field of communication, data science, ambient intelligence, networking, computing, security, and privacy. The authors have strived to render valuable pieces of study in this edition and hope to acquire enthusiastic support from the readers. |
| artificial intelligence in forensic science: Oxford Handbook of Ethics of AI Markus D. Dubber, Frank Pasquale, Sunit Das, 2020-06-30 This volume tackles a quickly-evolving field of inquiry, mapping the existing discourse as part of a general attempt to place current developments in historical context; at the same time, breaking new ground in taking on novel subjects and pursuing fresh approaches. The term A.I. is used to refer to a broad range of phenomena, from machine learning and data mining to artificial general intelligence. The recent advent of more sophisticated AI systems, which function with partial or full autonomy and are capable of tasks which require learning and 'intelligence', presents difficult ethical questions, and has drawn concerns from many quarters about individual and societal welfare, democratic decision-making, moral agency, and the prevention of harm. This work ranges from explorations of normative constraints on specific applications of machine learning algorithms today-in everyday medical practice, for instance-to reflections on the (potential) status of AI as a form of consciousness with attendant rights and duties and, more generally still, on the conceptual terms and frameworks necessarily to understand tasks requiring intelligence, whether human or A.I. |
| artificial intelligence in forensic science: Infrared and Raman Spectroscopy in Forensic Science John M. Chalmers, Howell G. M. Edwards, Michael D. Hargreaves, 2012-03-05 This book will provide a survey of the major areas in which information derived from vibrational spectroscopy investigations and studies have contributed to the benefit of forensic science, either in a complementary or a unique way. This is highlighted by examples taken from real case studies and analyses of forensic relevance, which provide a focus for current and future applications and developments. |
| artificial intelligence in forensic science: Implications of Artificial Intelligence for Cybersecurity National Academies of Sciences, Engineering, and Medicine, Division on Engineering and Physical Sciences, Intelligence Community Studies Board, Computer Science and Telecommunications Board, 2020-01-27 In recent years, interest and progress in the area of artificial intelligence (AI) and machine learning (ML) have boomed, with new applications vigorously pursued across many sectors. At the same time, the computing and communications technologies on which we have come to rely present serious security concerns: cyberattacks have escalated in number, frequency, and impact, drawing increased attention to the vulnerabilities of cyber systems and the need to increase their security. In the face of this changing landscape, there is significant concern and interest among policymakers, security practitioners, technologists, researchers, and the public about the potential implications of AI and ML for cybersecurity. The National Academies of Sciences, Engineering, and Medicine convened a workshop on March 12-13, 2019 to discuss and explore these concerns. This publication summarizes the presentations and discussions from the workshop. |
| artificial intelligence in forensic science: Digital Forensics and Internet of Things Anita Gehlot, Rajesh Singh, Jaskaran Singh, Neeta Raj Sharma, 2022-04-19 DIGITAL FORENSICS AND INTERNET OF THINGS It pays to be ahead of the criminal, and this book helps organizations and people to create a path to achieve this goal. The book discusses applications and challenges professionals encounter in the burgeoning field of IoT forensics. IoT forensics attempts to align its workflow to that of any forensics practice—investigators identify, interpret, preserve, analyze and present any relevant data. As with any investigation, a timeline is constructed, and, with the aid of smart devices providing data, investigators might be able to capture much more specific data points than in a traditional crime. However, collecting this data can often be a challenge, as it frequently doesn’t live on the device itself, but rather in the provider’s cloud platform. If you can get the data off the device, you’ll have to employ one of a variety of methods given the diverse nature of IoT devices hardware, software, and firmware. So, while robust and insightful data is available, acquiring it is no small undertaking. Digital Forensics and Internet of Things encompasses: State-of-the-art research and standards concerning IoT forensics and traditional digital forensics Compares and contrasts IoT forensic techniques with those of traditional digital forensics standards Identifies the driving factors of the slow maturation of IoT forensic standards and possible solutions Applies recommended standards gathered from IoT forensic literature in hands-on experiments to test their effectiveness across multiple IoT devices Provides educated recommendations on developing and establishing IoT forensic standards, research, and areas that merit further study. Audience Researchers and scientists in forensic sciences, computer sciences, electronics engineering, embedded systems, information technology. |
| artificial intelligence in forensic science: Wildlife DNA Analysis Adrian Linacre, Shanan Tobe, 2013-03-27 Clearly structured throughout, the introduction highlights the different types of crime where these techniques are regularly used. This chapter includes a discussion as to who performs forensic wildlife examinations, the standardisation and validation of methods, and the role of the expert witness in this type of alleged crime. This is followed by a detailed section on the science behind DNA typing including the problems in isolating DNA from trace material and subsequent genetic analysis are also covered. The book then undertakes a comprehensive review of species testing using DNA, including a step-by-step guide to sequence comparisons. A comparison of the different markers used in species testing highlights the criteria for a genetic marker. A full set of case histories illustrates the use of the different markers used. The book details the use of genetic markers to link two or more hairs/feather/leaves/needles to the same individual organism and the software used in population assignment. The problems and possibilities in isolating markers, along with the construction of allele databases are discussed in this chapter. The book concludes with evaluation and reporting of genetic evidence in wildlife forensic science illustrated by examples of witness statements. |
| artificial intelligence in forensic science: Advances in Deep Learning M. Arif Wani, Farooq Ahmad Bhat, Saduf Afzal, Asif Iqbal Khan, 2019-03-14 This book introduces readers to both basic and advanced concepts in deep network models. It covers state-of-the-art deep architectures that many researchers are currently using to overcome the limitations of the traditional artificial neural networks. Various deep architecture models and their components are discussed in detail, and subsequently illustrated by algorithms and selected applications. In addition, the book explains in detail the transfer learning approach for faster training of deep models; the approach is also demonstrated on large volumes of fingerprint and face image datasets. In closing, it discusses the unique set of problems and challenges associated with these models. |
| artificial intelligence in forensic science: Intelligent Human Systems Integration 2020 Tareq Ahram, Waldemar Karwowski, Alberto Vergnano, Francesco Leali, Redha Taiar, 2020-01-22 This book presents cutting-edge research on innovative human systems integration and human–machine interaction, with an emphasis on artificial intelligence and automation, as well as computational modeling and simulation. It covers a wide range of applications in the areas of design, construction and operation of products, systems and services, and discusses the human factors in a wide range of settings. Gathering the proceedings of the 3rd International Conference on Intelligent Human Systems Integration (IHSI 2020), held on February 19–21, 2020, in Modena, Italy, the book’s goal is to advance the theory and applications of artificial cognitive systems and improve human-artificial systems collaboration. Special emphasis is placed on automotive design, autonomous vehicles and the applications of artificial intelligence. The book offers a timely survey and source of inspiration for human factors engineers, automotive engineers, IT developers and UX designers who are working to shape the future of automated intelligent systems. |
| artificial intelligence in forensic science: Digital Evidence and Computer Crime Eoghan Casey, 2011-04-20 Though an increasing number of criminals are using computers and computer networks, few investigators are well versed in the issues related to digital evidence. This work explains how computer networks function and how they can be used in a crime. |
| artificial intelligence in forensic science: Introduction to Forensic Science James T. Spencer, 2024-10-07 Introduction to Forensic Science: The Science of Criminalistics is a textbook that takes a unique and holistic approach to forensic science. This book focuses on exploring the underlying scientific concepts as presented at the introductory college and senior high school levels. Chapters introduce readers to each of the important areas of forensic science, grouping chapters together by discipline and following a logical progression and flow between chapters. This systematically allows students to understand the fundamental scientific concepts, recognize their various applications to the law and investigations, and discern how each topic fits broadly within the context of forensic science. The writing is accessible throughout, maintaining students’ interest – including both science and non-science majors – while inspiring them to learn more about the field. Concepts are demonstrated with numerous case studies and full-color illustrations that serve to emphasize the important ideas and issues related to a particular topic. This approach underscores scientific understanding, allowing the student to go beyond simple rote learning to develop deeper insights into the field, regardless of their scientific background. This book has been extensively classroom-tested to provide the most comprehensive and up-to-date survey of various forensic disciplines and the current state of the science, policies, and best practices. Key features: Presents a wholly new, fresh approach to addressing a broad survey of techniques and evidentiary analyses in the field of forensic science. All concepts – and the underpinnings of forensic practice – are explained in simple terms, using understandable analogies and illustrations to further clarify concepts. Introduces topics that other introductory texts fail to address, including serology, behavioral science, forensic medicine and anthropology, forensic ecology, palynology, zoology, video analysis, AI/computer forensics, and forensic engineering. Highly illustrated with over 1,000 full-color photographs, drawings, and diagrams to further highlight key concepts. Suitable for both high school senior-level instruction and two- and four-year university courses for majors, non-majors, and criminal justice students enrolled in introductory forensic science classes. Support Materials – including an Instructor’s Manual with test bank and chapter PowerPoint lecture slides – are available to professors with qualified course adoption. |
| artificial intelligence in forensic science: Analytical Techniques in Forensic Science Rosalind Wolstenholme, Sue Jickells, Shari Forbes, 2021-01-26 An in-depth text that explores the interface between analytical chemistry and trace evidence Analytical Techniques in Forensic Science is a comprehensive guide written in accessible terms that examines the interface between analytical chemistry and trace evidence in forensic science. With contributions from noted experts on the topic, the text features a detailed introduction analysis in forensic science and then subsequent chapters explore the laboratory techniques grouped by shared operating principles. For each technique, the authors incorporate specific theory, application to forensic analytics, interpretation, forensic specific developments, and illustrative case studies. Forensic techniques covered include UV-Vis and vibrational spectroscopy, mass spectrometry and gas and liquid chromatography. The applications reviewed include evidence types such as fibers, paint, drugs and explosives. The authors highlight data collection, subsequent analysis, what information has been obtained and what this means in the context of a case. The text shows how analytical chemistry and trace evidence can problem solve the nature of much of forensic analysis. This important text: Puts the focus on trace evidence and analytical science Contains case studies that illustrate theory in practice Includes contributions from experts on the topics of instrumentation, theory, and case examples Explores novel and future applications for analytical techniques Written for undergraduate and graduate students in forensic chemistry and forensic practitioners and researchers, Analytical Techniques in Forensic Science offers a text that bridges the gap between introductory textbooks and professional level literature. |
| artificial intelligence in forensic science: Big Data and Edge Intelligence for Enhanced Cyber Defense Chhabi Rani Panigrahi, Victor Hugo C. de Albuquerque, Akash Kumar Bhoi, Hareesha K.S., 2024-07-31 An unfortunate outcome of the growth of the Internet and mobile technologies has been the challenge of countering cybercrime. This book introduces and explains the latest trends and techniques of edge artificial intelligence (EdgeAI) intended to help cyber security experts design robust cyber defense systems (CDS), including host-based and network-based intrusion detection system and digital forensic intelligence. This book discusses the direct confluence of EdgeAI with big data, as well as demonstrating detailed reviews of recent cyber threats and their countermeasure. It provides computational intelligence techniques and automated reasoning models capable of fast training and timely data processing of cyber security big data, in addition to other basic information related to network security. In addition, it provides a brief overview of modern cyber security threats and outlines the advantages of using EdgeAI to counter these threats, as well as exploring various cyber defense mechanisms (CDM) based on detection type and approaches. Specific challenging areas pertaining to cyber defense through EdgeAI, such as improving digital forensic intelligence, proactive and adaptive defense of network infrastructure, and bio-inspired CDM, are also discussed. This book is intended as a reference for academics and students in the field of network and cybersecurity, particularly on the topics of intrusion detection systems, smart grid, EdgeAI, and bio-inspired cyber defense principles. The front-line EdgeAI techniques discussed will also be of use to cybersecurity engineers in their work enhancing cyber defense systems. |
| artificial intelligence in forensic science: Computer Applications for Handling Legal Evidence, Police Investigation and Case Argumentation Ephraim Nissan, 2012-06-15 This book provides an overview of computer techniques and tools — especially from artificial intelligence (AI) — for handling legal evidence, police intelligence, crime analysis or detection, and forensic testing, with a sustained discussion of methods for the modelling of reasoning and forming an opinion about the evidence, methods for the modelling of argumentation, and computational approaches to dealing with legal, or any, narratives. By the 2000s, the modelling of reasoning on legal evidence has emerged as a significant area within the well-established field of AI & Law. An overview such as this one has never been attempted before. It offers a panoramic view of topics, techniques and tools. It is more than a survey, as topic after topic, the reader can get a closer view of approaches and techniques. One aim is to introduce practitioners of AI to the modelling legal evidence. Another aim is to introduce legal professionals, as well as the more technically oriented among law enforcement professionals, or researchers in police science, to information technology resources from which their own respective field stands to benefit. Computer scientists must not blunder into design choices resulting in tools objectionable for legal professionals, so it is important to be aware of ongoing controversies. A survey is provided of argumentation tools or methods for reasoning about the evidence. Another class of tools considered here is intended to assist in organisational aspects of managing of the evidence. Moreover, tools appropriate for crime detection, intelligence, and investigation include tools based on link analysis and data mining. Concepts and techniques are introduced, along with case studies. So are areas in the forensic sciences. Special chapters are devoted to VIRTOPSY (a procedure for legal medicine) and FLINTS (a tool for the police). This is both an introductory book (possibly a textbook), and a reference for specialists from various quarters. |
| artificial intelligence in forensic science: Forensic Science Evgeny Katz, Jan Halámek, 2016-06-27 Concentrating on the natural science aspects of forensics, top international authors from renowned universities, institutes, and laboratories impart the latest information from the field. In doing so they provide the background needed to understand the state of the art in forensic science with a focus on biological, chemical, biochemical, and physical methods. The broad subject coverage includes spectroscopic analysis techniques in various wavelength regimes, gas chromatography, mass spectrometry, electrochemical detection approaches, and imaging techniques, as well as advanced biochemical, DNA-based identification methods. The result is a unique collection of hard-to-get data that is otherwise only found scattered throughout the literature. |
ARTIFICIAL Definition & Meaning - Merriam-Webster
The meaning of ARTIFICIAL is made, produced, or done by humans especially to seem like something natural : man-made. How to use artificial in a sentence.
ARTIFICIAL | English meaning - Cambridge Dictionary
ARTIFICIAL definition: 1. made by people, often as a copy of something natural: 2. not sincere: 3. made by people, often…. Learn more.
ARTIFICIAL Definition & Meaning | Dictionary.com
Artificial is used to describe things that are made or manufactured as opposed to occurring naturally. Artificial is often used as the opposite of natural. A close synonym of artificial is …
Artificial - definition of artificial by The Free Dictionary
1. produced by man; not occurring naturally: artificial materials of great strength. 2. made in imitation of a natural product, esp as a substitute; not genuine: artificial cream. 3. pretended; …
ARTIFICIAL definition and meaning | Collins English Dictionary
Artificial objects, materials, or processes do not occur naturally and are created by human beings, for example using science or technology.
artificial adjective - Definition, pictures, pronunciation and usage ...
Definition of artificial adjective in Oxford Advanced Learner's Dictionary. Meaning, pronunciation, picture, example sentences, grammar, usage notes, synonyms and more.
Artificial - Definition, Meaning & Synonyms - Vocabulary.com
While artificial can simply mean “made by humans,” it’s often used in a negative sense, conveying the idea that an artificial product is inferior to the real thing. If you remark that your friend’s new …
What does artificial mean? - Definitions.net
Artificial refers to something that is made or produced by human beings rather than occurring naturally or in the environment. It often implies an imitation of something natural or a real …
5 No-Brainer Artificial intelligence (AI) Stocks to Buy Right Now
1 day ago · Palantir is quickly becoming one of the biggest artificial intelligence (AI) winners. Nvidia, AMD, and TSMC are all set up to be big AI infrastructure spending beneficiaries. …
How Artificial Intelligence Is Reshaping Industries—And What
2 days ago · Artificial intelligence has long since left the confines of research labs and entered our everyday lives. What was once the domain of science fiction is now a rapidly evolving reality. …
ARTIFICIAL Definition & Meaning - Merriam-Webster
The meaning of ARTIFICIAL is made, produced, or done by humans especially to seem like something natural : man-made. How to use artificial in a sentence.
ARTIFICIAL | English meaning - Cambridge Dictionary
ARTIFICIAL definition: 1. made by people, often as a copy of something natural: 2. not sincere: 3. made by people, often…. Learn more.
ARTIFICIAL Definition & Meaning | Dictionary.com
Artificial is used to describe things that are made or manufactured as opposed to occurring naturally. Artificial is often used as the opposite of natural. A close synonym of artificial is …
Artificial - definition of artificial by The Free Dictionary
1. produced by man; not occurring naturally: artificial materials of great strength. 2. made in imitation of a natural product, esp as a substitute; not genuine: artificial cream. 3. pretended; …
ARTIFICIAL definition and meaning | Collins English Dictionary
Artificial objects, materials, or processes do not occur naturally and are created by human beings, for example using science or technology.
artificial adjective - Definition, pictures, pronunciation and usage ...
Definition of artificial adjective in Oxford Advanced Learner's Dictionary. Meaning, pronunciation, picture, example sentences, grammar, usage notes, synonyms and more.
Artificial - Definition, Meaning & Synonyms - Vocabulary.com
While artificial can simply mean “made by humans,” it’s often used in a negative sense, conveying the idea that an artificial product is inferior to the real thing. If you remark that your friend’s new …
What does artificial mean? - Definitions.net
Artificial refers to something that is made or produced by human beings rather than occurring naturally or in the environment. It often implies an imitation of something natural or a real …
5 No-Brainer Artificial intelligence (AI) Stocks to Buy Right Now
1 day ago · Palantir is quickly becoming one of the biggest artificial intelligence (AI) winners. Nvidia, AMD, and TSMC are all set up to be big AI infrastructure spending beneficiaries. …
How Artificial Intelligence Is Reshaping Industries—And What
2 days ago · Artificial intelligence has long since left the confines of research labs and entered our everyday lives. What was once the domain of science fiction is now a rapidly evolving reality. …
