Audio Video Analysis In Digital Forensics

  audio video analysis in digital forensics: Principles of Forensic Audio Analysis Robert C. Maher, 2018-11-07 This book provides an expert introduction to audio forensics, an essential specialty in modern forensic science, equipping readers with the fundamental background necessary to understand and participate in this exciting and important field of study. Modern audio forensic analysis combines skills in digital signal processing, the physics of sound propagation, acoustical phonetics, audio engineering, and many other fields. Scientists and engineers who work in the field of audio forensics are called upon to address issues of authenticity, quality enhancement, and signal interpretation for audio evidence that is important to a criminal law enforcement investigation, an accident investigation board, or an official civil inquiry. Expertise in audio forensics has never been more important. In addition to routine recordings from emergency call centers and police radio dispatchers, inexpensive portable audio/video recording systems are now in widespread use. Forensic evidence from the scene of a civil or criminal incident increasingly involves dashboard recorders in police cars, vest-pocket personal recorders worn by law enforcement officers, smart phone recordings from bystanders, and security surveillance systems in public areas and businesses. Utilizing new research findings and both historical and contemporary casework examples, this book blends audio forensic theory and practice in an informative and readable manner suitable for any scientifically-literate reader. Extensive examples, supplementary material, and authoritative references are also included for those who are interested in delving deeper into the field.
  audio video analysis in digital forensics: Handbook of Digital Forensics and Investigation Eoghan Casey, 2009-10-07 Handbook of Digital Forensics and Investigation builds on the success of the Handbook of Computer Crime Investigation, bringing together renowned experts in all areas of digital forensics and investigation to provide the consummate resource for practitioners in the field. It is also designed as an accompanying text to Digital Evidence and Computer Crime. This unique collection details how to conduct digital investigations in both criminal and civil contexts, and how to locate and utilize digital evidence on computers, networks, and embedded systems. Specifically, the Investigative Methodology section of the Handbook provides expert guidance in the three main areas of practice: Forensic Analysis, Electronic Discovery, and Intrusion Investigation. The Technology section is extended and updated to reflect the state of the art in each area of specialization. The main areas of focus in the Technology section are forensic analysis of Windows, Unix, Macintosh, and embedded systems (including cellular telephones and other mobile devices), and investigations involving networks (including enterprise environments and mobile telecommunications technology). This handbook is an essential technical reference and on-the-job guide that IT professionals, forensic practitioners, law enforcement, and attorneys will rely on when confronted with computer related crime and digital evidence of any kind. *Provides methodologies proven in practice for conducting digital investigations of all kinds*Demonstrates how to locate and interpret a wide variety of digital evidence, and how it can be useful in investigations *Presents tools in the context of the investigative process, including EnCase, FTK, ProDiscover, foremost, XACT, Network Miner, Splunk, flow-tools, and many other specialized utilities and analysis platforms*Case examples in every chapter give readers a practical understanding of the technical, logistical, and legal challenges that arise in real investigations
  audio video analysis in digital forensics: Fundamentals of Digital Forensics Joakim Kävrestad, 2018-07-31 This hands-on textbook provides an accessible introduction to the fundamentals of digital forensics. The text contains thorough coverage of the theoretical foundations, explaining what computer forensics is, what it can do, and also what it can’t. A particular focus is presented on establishing sound forensic thinking and methodology, supported by practical guidance on performing typical tasks and using common forensic tools. Emphasis is also placed on universal principles, as opposed to content unique to specific legislation in individual countries. Topics and features: introduces the fundamental concepts in digital forensics, and the steps involved in a forensic examination in a digital environment; discusses the nature of what cybercrime is, and how digital evidence can be of use during criminal investigations into such crimes; offers a practical overview of common practices for cracking encrypted data; reviews key artifacts that have proven to be important in several cases, highlighting where to find these and how to correctly interpret them; presents a survey of various different search techniques, and several forensic tools that are available for free; examines the functions of AccessData Forensic Toolkit and Registry Viewer; proposes methods for analyzing applications, timelining, determining the identity of the computer user, and deducing if the computer was remote controlled; describes the central concepts relating to computer memory management, and how to perform different types of memory analysis using the open source tool Volatility; provides review questions and practice tasks at the end of most chapters, and supporting video lectures on YouTube. This easy-to-follow primer is an essential resource for students of computer forensics, and will also serve as a valuable reference for practitioners seeking instruction on performing forensic examinations in law enforcement or in the private sector.
  audio video analysis in digital forensics: Digital Forensics with Open Source Tools Harlan Carvey, Cory Altheide, 2011-03-29 Digital Forensics with Open Source Tools is the definitive book on investigating and analyzing computer systems and media using open source tools. The book is a technical procedural guide, and explains the use of open source tools on Mac, Linux and Windows systems as a platform for performing computer forensics. Both well-known and novel forensic methods are demonstrated using command-line and graphical open source computer forensic tools for examining a wide range of target systems and artifacts. Written by world-renowned forensic practitioners, this book uses the most current examination and analysis techniques in the field. It consists of 9 chapters that cover a range of topics such as the open source examination platform; disk and file system analysis; Windows systems and artifacts; Linux systems and artifacts; Mac OS X systems and artifacts; Internet artifacts; and automating analysis and extending capabilities. The book lends itself to use by students and those entering the field who do not have means to purchase new tools for different investigations. This book will appeal to forensic practitioners from areas including incident response teams and computer forensic investigators; forensic technicians from legal, audit, and consulting firms; and law enforcement agencies. - Written by world-renowned forensic practitioners - Details core concepts and techniques of forensic file system analysis - Covers analysis of artifacts from the Windows, Mac, and Linux operating systems
  audio video analysis in digital forensics: Intelligent Multimedia Analysis for Security Applications Husrev T. Sencar, Sergio Velastin, Nikolaos Nikolaidis, Shiguo Lian, 2010-04-22 This is one of the very few books focused on analysis of multimedia data and newly emerging multimedia applications with an emphasis on security. The main objective of this project was to assemble as much research coverage as possible related to the field by defining the latest innovative technologies and providing the most comprehensive list of research references. The book includes sixteen chapters highlighting current concepts, issues and emerging technologies. Distinguished scholars from many prominent research institutions around the world contribute to the book. The book covers various aspects, including not only some fundamental knowledge and the latest key techniques, but also typical applications and open issues. Topics covered include dangerous or abnormal event detection, interaction recognition, person identification based on multiple traits, audiovisual biometric person authentication and liveness verification, emerging biometric technologies, sensitive information filtering for teleradiology, detection of nakedness in images, audio forensics, steganalysis, media content tracking authentication and illegal distributor identification through watermarking and content-based copy detection. We believe that the comprehensive coverage of diverse disciplines in the field of intelligent multimedia analysis for security applications will contribute to a better understanding of all topics, research, and discoveries in this emerging and evolving field and that the included contributions will be instrumental in the expansion of the corresponding body of knowledge, making this book a reference source of information. It is our sincere hope that this publication and its great amount of information and research will assist our research colleagues, faculty members and students, and organization decision makers in enhancing their understanding for the concepts, issues, problems, trends, challenges and opportunities related to this research field. Perhaps this book will even inspire its readers to contribute to the current discoveries in this immense field.
  audio video analysis in digital forensics: Handbook of Digital Forensics of Multimedia Data and Devices, Enhanced E-Book Anthony T. S. Ho, Shujun Li, 2016-05-20 Digital forensics and multimedia forensics are rapidly growing disciplines whereby electronic information is extracted and interpreted for use in a court of law. These two fields are finding increasing importance in law enforcement and the investigation of cybercrime as the ubiquity of personal computing and the internet becomes ever-more apparent. Digital forensics involves investigating computer systems and digital artefacts in general, while multimedia forensics is a sub-topic of digital forensics focusing on evidence extracted from both normal computer systems and special multimedia devices, such as digital cameras. This book focuses on the interface between digital forensics and multimedia forensics, bringing two closely related fields of forensic expertise together to identify and understand the current state-of-the-art in digital forensic investigation. Both fields are expertly attended to by contributions from researchers and forensic practitioners specializing in diverse topics such as forensic authentication, forensic triage, forensic photogrammetry, biometric forensics, multimedia device identification, and image forgery detection among many others. Key features: Brings digital and multimedia forensics together with contributions from academia, law enforcement, and the digital forensics industry for extensive coverage of all the major aspects of digital forensics of multimedia data and devices Provides comprehensive and authoritative coverage of digital forensics of multimedia data and devices Offers not only explanations of techniques but also real-world and simulated case studies to illustrate how digital and multimedia forensics techniques work Includes a companion website hosting continually updated supplementary materials ranging from extended and updated coverage of standards to best practice guides, test datasets and more case studies
  audio video analysis in digital forensics: Digital Image Forensics Husrev Taha Sencar, Nasir Memon, 2012-08-01 Photographic imagery has come a long way from the pinhole cameras of the nineteenth century. Digital imagery, and its applications, develops in tandem with contemporary society’s sophisticated literacy of this subtle medium. This book examines the ways in which digital images have become ever more ubiquitous as legal and medical evidence, just as they have become our primary source of news and have replaced paper-based financial documentation. Crucially, the contributions also analyze the very profound problems which have arisen alongside the digital image, issues of veracity and progeny that demand systematic and detailed response: It looks real, but is it? What camera captured it? Has it been doctored or subtly altered? Attempting to provide answers to these slippery issues, the book covers how digital images are created, processed and stored before moving on to set out the latest techniques for forensically examining images, and finally addressing practical issues such as courtroom admissibility. In an environment where even novice users can alter digital media, this authoritative publication will do much so stabilize public trust in these real, yet vastly flexible, images of the world around us.
  audio video analysis in digital forensics: Computational Intelligence in Digital Forensics: Forensic Investigation and Applications Azah Kamilah Muda, Yun-Huoy Choo, Ajith Abraham, Sargur N. Srihari, 2014-04-01 Computational Intelligence techniques have been widely explored in various domains including forensics. Analysis in forensic encompasses the study of pattern analysis that answer the question of interest in security, medical, legal, genetic studies and etc. However, forensic analysis is usually performed through experiments in lab which is expensive both in cost and time. Therefore, this book seeks to explore the progress and advancement of computational intelligence technique in different focus areas of forensic studies. This aims to build stronger connection between computer scientists and forensic field experts. This book, Computational Intelligence in Digital Forensics: Forensic Investigation and Applications, is the first volume in the Intelligent Systems Reference Library series. The book presents original research results and innovative applications of computational intelligence in digital forensics. This edited volume contains seventeen chapters and presents the latest state-of-the-art advancement of Computational Intelligence in Digital Forensics; in both theoretical and application papers related to novel discovery in intelligent forensics. The chapters are further organized into three sections: (1) Introduction, (2) Forensic Discovery and Investigation, which discusses the computational intelligence technologies employed in Digital Forensic, and (3) Intelligent Forensic Science Applications, which encompasses the applications of computational intelligence in Digital Forensic, such as human anthropology, human biometrics, human by products, drugs, and electronic devices.
  audio video analysis in digital forensics: Digital Forensics for Legal Professionals Larry Daniel, Lars Daniel, 2011-09-02 Section 1: What is Digital Forensics? Chapter 1. Digital Evidence is Everywhere Chapter 2. Overview of Digital Forensics Chapter 3. Digital Forensics -- The Sub-Disciplines Chapter 4. The Foundations of Digital Forensics -- Best Practices Chapter 5. Overview of Digital Forensics Tools Chapter 6. Digital Forensics at Work in the Legal System Section 2: Experts Chapter 7. Why Do I Need an Expert? Chapter 8. The Difference between Computer Experts and Digital Forensic Experts Chapter 9. Selecting a Digital Forensics Expert Chapter 10. What to Expect from an Expert Chapter 11. Approaches by Different Types of Examiners Chapter 12. Spotting a Problem Expert Chapter 13. Qualifying an Expert in Court Sections 3: Motions and Discovery Chapter 14. Overview of Digital Evidence Discovery Chapter 15. Discovery of Digital Evidence in Criminal Cases Chapter 16. Discovery of Digital Evidence in Civil Cases Chapter 17. Discovery of Computers and Storage Media Chapter 18. Discovery of Video Evidence Ch ...
  audio video analysis in digital forensics: 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.
  audio video analysis in digital forensics: Forensic Examination of Digital Evidence U S Department of Justice, 2014-08-01 Developments in the world have shown how simple it is to acquire all sorts of information through the use of computers. This information can be used for a variety of endeavors, and criminal activity is a major one. In an effort to fight this new crime wave, law enforcement agencies, financial institutions, and investment firms are incorporating computer forensics into their infrastructure. From network security breaches to child pornography investiga- tions, the common bridge is the demon- stration that the particular electronic media contained the incriminating evidence. Supportive examination procedures and protocols should be in place in order to show that the electronic media contains the incriminating evidence.
  audio video analysis in digital forensics: File System Forensic Analysis Brian Carrier, 2005-03-17 The Definitive Guide to File System Analysis: Key Concepts and Hands-on Techniques Most digital evidence is stored within the computer's file system, but understanding how file systems work is one of the most technically challenging concepts for a digital investigator because there exists little documentation. Now, security expert Brian Carrier has written the definitive reference for everyone who wants to understand and be able to testify about how file system analysis is performed. Carrier begins with an overview of investigation and computer foundations and then gives an authoritative, comprehensive, and illustrated overview of contemporary volume and file systems: Crucial information for discovering hidden evidence, recovering deleted data, and validating your tools. Along the way, he describes data structures, analyzes example disk images, provides advanced investigation scenarios, and uses today's most valuable open source file system analysis tools—including tools he personally developed. Coverage includes Preserving the digital crime scene and duplicating hard disks for dead analysis Identifying hidden data on a disk's Host Protected Area (HPA) Reading source data: Direct versus BIOS access, dead versus live acquisition, error handling, and more Analyzing DOS, Apple, and GPT partitions; BSD disk labels; and Sun Volume Table of Contents using key concepts, data structures, and specific techniques Analyzing the contents of multiple disk volumes, such as RAID and disk spanning Analyzing FAT, NTFS, Ext2, Ext3, UFS1, and UFS2 file systems using key concepts, data structures, and specific techniques Finding evidence: File metadata, recovery of deleted files, data hiding locations, and more Using The Sleuth Kit (TSK), Autopsy Forensic Browser, and related open source tools When it comes to file system analysis, no other book offers this much detail or expertise. Whether you're a digital forensics specialist, incident response team member, law enforcement officer, corporate security specialist, or auditor, this book will become an indispensable resource for forensic investigations, no matter what analysis tools you use.
  audio video analysis in digital forensics: Learn Computer Forensics William Oettinger, 2020-04-30 Get up and running with collecting evidence using forensics best practices to present your findings in judicial or administrative proceedings Key Features Learn the core techniques of computer forensics to acquire and secure digital evidence skillfully Conduct a digital forensic examination and document the digital evidence collected Perform a variety of Windows forensic investigations to analyze and overcome complex challenges Book DescriptionA computer forensics investigator must possess a variety of skills, including the ability to answer legal questions, gather and document evidence, and prepare for an investigation. This book will help you get up and running with using digital forensic tools and techniques to investigate cybercrimes successfully. Starting with an overview of forensics and all the open source and commercial tools needed to get the job done, you'll learn core forensic practices for searching databases and analyzing data over networks, personal devices, and web applications. You'll then learn how to acquire valuable information from different places, such as filesystems, e-mails, browser histories, and search queries, and capture data remotely. As you advance, this book will guide you through implementing forensic techniques on multiple platforms, such as Windows, Linux, and macOS, to demonstrate how to recover valuable information as evidence. Finally, you'll get to grips with presenting your findings efficiently in judicial or administrative proceedings. By the end of this book, you'll have developed a clear understanding of how to acquire, analyze, and present digital evidence like a proficient computer forensics investigator.What you will learn Understand investigative processes, the rules of evidence, and ethical guidelines Recognize and document different types of computer hardware Understand the boot process covering BIOS, UEFI, and the boot sequence Validate forensic hardware and software Discover the locations of common Windows artifacts Document your findings using technically correct terminology Who this book is for If you're an IT beginner, student, or an investigator in the public or private sector this book is for you. This book will also help professionals and investigators who are new to incident response and digital forensics and interested in making a career in the cybersecurity domain. Individuals planning to pass the Certified Forensic Computer Examiner (CFCE) certification will also find this book useful.
  audio video analysis in digital forensics: 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.
  audio video analysis in digital forensics: Strengthening Forensic Science in the United States National Research Council, Division on Engineering and Physical Sciences, Committee on Applied and Theoretical Statistics, Policy and Global Affairs, Committee on Science, Technology, and Law, Committee on Identifying the Needs of the Forensic Sciences Community, 2009-07-29 Scores of talented and dedicated people serve the forensic science community, performing vitally important work. However, they are often constrained by lack of adequate resources, sound policies, and national support. It is clear that change and advancements, both systematic and scientific, are needed in a number of forensic science disciplines to ensure the reliability of work, establish enforceable standards, and promote best practices with consistent application. Strengthening Forensic Science in the United States: A Path Forward provides a detailed plan for addressing these needs and suggests the creation of a new government entity, the National Institute of Forensic Science, to establish and enforce standards within the forensic science community. The benefits of improving and regulating the forensic science disciplines are clear: assisting law enforcement officials, enhancing homeland security, and reducing the risk of wrongful conviction and exoneration. Strengthening Forensic Science in the United States gives a full account of what is needed to advance the forensic science disciplines, including upgrading of systems and organizational structures, better training, widespread adoption of uniform and enforceable best practices, and mandatory certification and accreditation programs. While this book provides an essential call-to-action for congress and policy makers, it also serves as a vital tool for law enforcement agencies, criminal prosecutors and attorneys, and forensic science educators.
  audio video analysis in digital forensics: Practical Linux Forensics Bruce Nikkel, 2021-12-21 A resource to help forensic investigators locate, analyze, and understand digital evidence found on modern Linux systems after a crime, security incident or cyber attack. Practical Linux Forensics dives into the technical details of analyzing postmortem forensic images of Linux systems which have been misused, abused, or the target of malicious attacks. It helps forensic investigators locate and analyze digital evidence found on Linux desktops, servers, and IoT devices. Throughout the book, you learn how to identify digital artifacts which may be of interest to an investigation, draw logical conclusions, and reconstruct past activity from incidents. You’ll learn how Linux works from a digital forensics and investigation perspective, and how to interpret evidence from Linux environments. The techniques shown are intended to be independent of the forensic analysis platforms and tools used. Learn how to: Extract evidence from storage devices and analyze partition tables, volume managers, popular Linux filesystems (Ext4, Btrfs, and Xfs), and encryption Investigate evidence from Linux logs, including traditional syslog, the systemd journal, kernel and audit logs, and logs from daemons and applications Reconstruct the Linux startup process, from boot loaders (UEFI and Grub) and kernel initialization, to systemd unit files and targets leading up to a graphical login Perform analysis of power, temperature, and the physical environment of a Linux machine, and find evidence of sleep, hibernation, shutdowns, reboots, and crashes Examine installed software, including distro installers, package formats, and package management systems from Debian, Fedora, SUSE, Arch, and other distros Perform analysis of time and Locale settings, internationalization including language and keyboard settings, and geolocation on a Linux system Reconstruct user login sessions (shell, X11 and Wayland), desktops (Gnome, KDE, and others) and analyze keyrings, wallets, trash cans, clipboards, thumbnails, recent files and other desktop artifacts Analyze network configuration, including interfaces, addresses, network managers, DNS, wireless artifacts (Wi-Fi, Bluetooth, WWAN), VPNs (including WireGuard), firewalls, and proxy settings Identify traces of attached peripheral devices (PCI, USB, Thunderbolt, Bluetooth) including external storage, cameras, and mobiles, and reconstruct printing and scanning activity
  audio video analysis in digital forensics: The Basics of Digital Forensics John Sammons, 2014-12-09 The Basics of Digital Forensics provides a foundation for people new to the digital forensics field. This book offers guidance on how to conduct examinations by discussing what digital forensics is, the methodologies used, key tactical concepts, and the tools needed to perform examinations. Details on digital forensics for computers, networks, cell phones, GPS, the cloud and the Internet are discussed. Also, learn how to collect evidence, document the scene, and how deleted data can be recovered. The new Second Edition of this book provides the reader with real-world examples and all the key technologies used in digital forensics, as well as new coverage of network intrusion response, how hard drives are organized, and electronic discovery. This valuable resource also covers how to incorporate quality assurance into an investigation, how to prioritize evidence items to examine (triage), case processing, and what goes into making an expert witness. - Learn what Digital Forensics entails - Build a toolkit and prepare an investigative plan - Understand the common artifacts to look for in an exam - Second Edition features all-new coverage of hard drives, triage, network intrusion response, and electronic discovery; as well as updated case studies and expert interviews
  audio video analysis in digital forensics: Digital Forensics and Cyber Crime Frank Breitinger, Ibrahim Baggili, 2018-12-29 This book constitutes the refereed proceedings of the 10th International Conference on Digital Forensics and Cyber Crime, ICDF2C 2018, held in New Orleans, LA, USA, in September 2018. The 11 reviewed full papers and 1 short paper were selected from 33 submissions and are grouped in topical sections on carving and data hiding, android, forensic readiness, hard drives and digital forensics, artefact correlation.
  audio video analysis in digital forensics: Digital Forensics, Investigation, and Response Chuck Easttom, 2021-08-10 Digital Forensics, Investigation, and Response, Fourth Edition examines the fundamentals of system forensics, addresses the tools, techniques, and methods used to perform computer forensics and investigation, and explores incident and intrusion response,
  audio video analysis in digital forensics: Windows Forensic Analysis DVD Toolkit Harlan Carvey, 2009-06-01 Windows Forensic Analysis DVD Toolkit, Second Edition, is a completely updated and expanded version of Harlan Carvey's best-selling forensics book on incident response and investigating cybercrime on Windows systems. With this book, you will learn how to analyze data during live and post-mortem investigations.New to this edition is Forensic Analysis on a Budget, which collects freely available tools that are essential for small labs, state (or below) law enforcement, and educational organizations. The book also includes new pedagogical elements, Lessons from the Field, Case Studies, and War Stories that present real-life experiences by an expert in the trenches, making the material real and showing the why behind the how. The companion DVD contains significant, and unique, materials (movies, spreadsheet, code, etc.) not available anyplace else because they were created by the author.This book will appeal to digital forensic investigators, IT security professionals, engineers, and system administrators as well as students and consultants. - Best-Selling Windows Digital Forensic book completely updated in this 2nd Edition - Learn how to Analyze Data During Live and Post-Mortem Investigations - DVD Includes Custom Tools, Updated Code, Movies, and Spreadsheets
  audio video analysis in digital forensics: An In-Depth Guide to Mobile Device Forensics Chuck Easttom, 2021-10-21 Mobile devices are ubiquitous; therefore, mobile device forensics is absolutely critical. Whether for civil or criminal investigations, being able to extract evidence from a mobile device is essential. This book covers the technical details of mobile devices and transmissions, as well as forensic methods for extracting evidence. There are books on specific issues like Android forensics or iOS forensics, but there is not currently a book that covers all the topics covered in this book. Furthermore, it is such a critical skill that mobile device forensics is the most common topic the Author is asked to teach to law enforcement. This is a niche that is not being adequately filled with current titles. An In-Depth Guide to Mobile Device Forensics is aimed towards undergraduates and graduate students studying cybersecurity or digital forensics. It covers both technical and legal issues, and includes exercises, tests/quizzes, case studies, and slides to aid comprehension.
  audio video analysis in digital forensics: Computer Forensics For Dummies Carol Pollard, Reynaldo Anzaldua, 2008-10-13 Uncover a digital trail of e-evidence by using the helpful, easy-to-understand information in Computer Forensics For Dummies! Professional and armchair investigators alike can learn the basics of computer forensics, from digging out electronic evidence to solving the case. You won’t need a computer science degree to master e-discovery. Find and filter data in mobile devices, e-mail, and other Web-based technologies. You’ll learn all about e-mail and Web-based forensics, mobile forensics, passwords and encryption, and other e-evidence found through VoIP, voicemail, legacy mainframes, and databases. You’ll discover how to use the latest forensic software, tools, and equipment to find the answers that you’re looking for in record time. When you understand how data is stored, encrypted, and recovered, you’ll be able to protect your personal privacy as well. By the time you finish reading this book, you’ll know how to: Prepare for and conduct computer forensics investigations Find and filter data Protect personal privacy Transfer evidence without contaminating it Anticipate legal loopholes and opponents’ methods Handle passwords and encrypted data Work with the courts and win the case Plus, Computer Forensics for Dummies includes lists of things that everyone interested in computer forensics should know, do, and build. Discover how to get qualified for a career in computer forensics, what to do to be a great investigator and expert witness, and how to build a forensics lab or toolkit. Note: CD-ROM/DVD and other supplementary materials are not included as part of eBook file.
  audio video analysis in digital forensics: Digital Forensics and Cyber Crime Pavel Gladyshev, Marcus K. Rogers, 2012-11-28 This book contains a selection of thoroughly refereed and revised papers from the Third International ICST Conference on Digital Forensics and Cyber Crime, ICDF2C 2011, held October 26-28 in Dublin, Ireland. The field of digital forensics is becoming increasingly important for law enforcement, network security, and information assurance. It is a multidisciplinary area that encompasses a number of fields, including law, computer science, finance, networking, data mining, and criminal justice. The 24 papers in this volume cover a variety of topics ranging from tactics of cyber crime investigations to digital forensic education, network forensics, and the use of formal methods in digital investigations. There is a large section addressing forensics of mobile digital devices.
  audio video analysis in digital forensics: Handbook of Digital and Multimedia Forensic Evidence John J. Barbara, 2007-12-28 This volume presents an overview of computer forensics perfect for beginners. A distinguished group of specialist authors have crafted chapters rich with detail yet accessible for readers who are not experts in the field. Tying together topics as diverse as applicable laws on search and seizure, investigating cybercrime, and preparation for courtroom testimony, Handbook of Digital and Multimedia Evidence is an ideal overall reference for this multi-faceted discipline.
  audio video analysis in digital forensics: A Practical Guide to Computer Forensics Investigations Darren R. Hayes, 2015 A Practical Guide to Computer Forensics Investigations introduces the newest technologies along with detailed information on how the evidence contained on these devices should be analyzed. Packed with practical, hands-on activities, students will learn unique subjects from chapters including Mac Forensics, Mobile Forensics, Cyberbullying, and Child Endangerment. This well-developed book will prepare students for the rapidly-growing field of computer forensics for a career with law enforcement, accounting firms, banks and credit card companies, private investigation companies, or government agencies.
  audio video analysis in digital forensics: Crime Scene Investigation National Institute of Justice (U.S.). Technical Working Group on Crime Scene Investigation, 2000 This is a guide to recommended practices for crime scene investigation. The guide is presented in five major sections, with sub-sections as noted: (1) Arriving at the Scene: Initial Response/Prioritization of Efforts (receipt of information, safety procedures, emergency care, secure and control persons at the scene, boundaries, turn over control of the scene and brief investigator/s in charge, document actions and observations); (2) Preliminary Documentation and Evaluation of the Scene (scene assessment, walk-through and initial documentation); (3) Processing the Scene (team composition, contamination control, documentation and prioritize, collect, preserve, inventory, package, transport, and submit evidence); (4) Completing and Recording the Crime Scene Investigation (establish debriefing team, perform final survey, document the scene); and (5) Crime Scene Equipment (initial responding officers, investigator/evidence technician, evidence collection kits).
  audio video analysis in digital forensics: Presentation Zen Garr Reynolds, 2009-04-15 FOREWORD BY GUY KAWASAKI Presentation designer and internationally acclaimed communications expert Garr Reynolds, creator of the most popular Web site on presentation design and delivery on the Net — presentationzen.com — shares his experience in a provocative mix of illumination, inspiration, education, and guidance that will change the way you think about making presentations with PowerPoint or Keynote. Presentation Zen challenges the conventional wisdom of making slide presentations in today’s world and encourages you to think differently and more creatively about the preparation, design, and delivery of your presentations. Garr shares lessons and perspectives that draw upon practical advice from the fields of communication and business. Combining solid principles of design with the tenets of Zen simplicity, this book will help you along the path to simpler, more effective presentations.
  audio video analysis in digital forensics: CCTV Vlado Damjanovski, 2005-08-04 Closed circuit television (CCTV) is experiencing a leap in technology using digital techniques, networking and the Internet. The new edition of this high-level professional reference retains the particulars that made the first edition a success, including the details of CCD cameras, lenses, coaxial cables, fiber-optics, and system design, but it is expanded to cover all video compression techniques used in the ever increasing assortment of digital video recorders (DVRs) available on the market today. This new edition of the book CCTV demystifies DVR technology. It also serves to clarify the technology of data networking. The theoretical section explains the various compression techniques. Networking is also a new and unknown area for many CCTV installers and this is explained in a brand new section. - New edition more accessible
  audio video analysis in digital forensics: Digital Triage Forensics Stephen Pearson, Richard Watson, 2010-07-13 Digital Triage Forensics: Processing the Digital Crime Scene provides the tools, training, and techniques in Digital Triage Forensics (DTF), a procedural model for the investigation of digital crime scenes including both traditional crime scenes and the more complex battlefield crime scenes. The DTF is used by the U.S. Army and other traditional police agencies for current digital forensic applications. The tools, training, and techniques from this practice are being brought to the public in this book for the first time. Now corporations, law enforcement, and consultants can benefit from the unique perspectives of the experts who coined Digital Triage Forensics. The text covers the collection of digital media and data from cellular devices and SIM cards. It also presents outlines of pre- and post- blast investigations. This book is divided into six chapters that present an overview of the age of warfare, key concepts of digital triage and battlefield forensics, and methods of conducting pre/post-blast investigations. The first chapter considers how improvised explosive devices (IEDs) have changed from basic booby traps to the primary attack method of the insurgents in Iraq and Afghanistan. It also covers the emergence of a sustainable vehicle for prosecuting enemy combatants under the Rule of Law in Iraq as U.S. airmen, marines, sailors, and soldiers perform roles outside their normal military duties and responsibilities. The remaining chapters detail the benefits of DTF model, the roles and responsibilities of the weapons intelligence team (WIT), and the challenges and issues of collecting digital media in battlefield situations. Moreover, data collection and processing as well as debates on the changing role of digital forensics investigators are explored. This book will be helpful to forensic scientists, investigators, and military personnel, as well as to students and beginners in forensics. - Includes coverage on collecting digital media - Outlines pre- and post-blast investigations - Features content on collecting data from cellular devices and SIM cards
  audio video analysis in digital forensics: Digital Evidence and the U.S. Criminal Justice System Sean E. Goodison, Robert Carl Davis, Brian A. Jackson, 2015 This report describes the results of a National Institute of Justice (NIJ)-sponsored research effort to identify and prioritize criminal justice needs related to digital evidence collection, management, analysis, and use. With digital devices becoming ubiquitous, digital evidence is increasingly important to the investigation and prosecution of many types of crimes. These devices often contain information about crimes committed, movement of suspects, and criminal associates. However, there are significant challenges to successfully using digital evidence in prosecutions, including inexperience of patrol officers and detectives in preserving and collecting digital evidence, lack of familiarity with digital evidence on the part of court officials, and an overwhelming volume of work for digital evidence examiners. Through structured interaction with police digital forensic experts, prosecuting attorneys, a privacy advocate, and industry representatives, the effort identified and prioritized specific needs to improve utilization of digital evidence in criminal justice. Several top-tier needs emerged from the analysis, including education of prosecutors and judges regarding digital evidence opportunities and challenges; training for patrol officers and investigators to promote better collection and preservation of digital evidence; tools for detectives to triage analysis of digital evidence in the field; development of regional models to make digital evidence analysis capability available to small departments; and training to address concerns about maintaining the currency of training and technology available to digital forensic examiners.
  audio video analysis in digital forensics: Photoshop CS3 for Forensics Professionals George Reis, 2007-10-08 Digital imaging technology has been used in forensics since at least 1992, yet until now there?has been?no practical instruction available to address the unique issues of image processing in an everyday forensic environment. Photoshop CS3 for Forensics Professionals serves the everyday, real-world needs of law enforcement and legal personnel dealing with digital images (including both photos and video stills). This book is an excellent tool for: Law enforcement personnel, from crime scene and arson investigators, detectives, and patrol officers to forensic photographers, fingerprint examiners, video analysts, tool mark and footwear examiners, and criminalists. Security pros in such fields as private investigation, insurance, fraud detection, and loss prevention. Scientific and technical users of Photoshop with workflows similar to law enforcement, such as medical photographers, research imaging experts, engineering and architecture staff, and industrial photographers. Staff responsible for maintaining a photo archive or printing images for court. Photoshop CS3 for Forensics Professionals is the only book to provide forensics professionals with specific answers to their imaging questions. This is the perfect resource for those who want to move from simple theory to the essential skills needed to be more effective. This resource is dividied into three parts: Part I: The Essentials is about setting up your workflow, archiving your images, and familiarizing yourself with Adobe Photoshop and Adobe Bridge, including the setting up of preferences. Also covered are the best practices in writing reports and providing courtroom testimony. Part II: The Digital Darkroom teaches how to use Photoshop to accomplish what traditionally was done in the darkroom, from correcting color casts to making prints and exhibits for courtroom use. Part III: Image Analysis & Enhancement covers techniques for clarifying images so that details can be better viewed and used for analysis or comparison, from contrast enhancement and pattern removal to even forensic video analysis. The companion CD-ROM provides sample images—including various accident and crime scenes—you can use to practice the techniques from the book while?following along with the tutorials. It also includes several scripts, plug-ins, and actions so you can work more effectively. In addition, instructor's materials are available so you can use book in workshops and training seminars. Order this one-of-a-kind resource today! Note: CD-ROM/DVD and other supplementary materials are not included as part of eBook file.
  audio video analysis in digital forensics: Mobile Forensic Investigations: A Guide to Evidence Collection, Analysis, and Presentation, Second Edition Lee Reiber, 2018-12-06 Master the tools and techniques of mobile forensic investigationsConduct mobile forensic investigations that are legal, ethical, and highly effective using the detailed information contained in this practical guide. Mobile Forensic Investigations: A Guide to Evidence Collection, Analysis, and Presentation, Second Edition fully explains the latest tools and methods along with features, examples, and real-world case studies. Find out how to assemble a mobile forensics lab, collect prosecutable evidence, uncover hidden files, and lock down the chain of custody. This comprehensive resource shows not only how to collect and analyze mobile device data but also how to accurately document your investigations to deliver court-ready documents.•Legally seize mobile devices, USB drives, SD cards, and SIM cards•Uncover sensitive data through both physical and logical techniques•Properly package, document, transport, and store evidence•Work with free, open source, and commercial forensic software•Perform a deep dive analysis of iOS, Android, and Windows Phone file systems•Extract evidence from application, cache, and user storage files•Extract and analyze data from IoT devices, drones, wearables, and infotainment systems•Build SQLite queries and Python scripts for mobile device file interrogation•Prepare reports that will hold up to judicial and defense scrutiny
  audio video analysis in digital forensics: Digital Audio Forensics Fundamentals James Zjalic, 2020-10-29 - Includes case studies offering insight into famous historical cases and contemporary practicing laboratories. - Represents the first publication to offer a comprehensive introduction to the topic for beginners. - Written by an experienced professional working in the field.
  audio video analysis in digital forensics: OPTICAL FLOW ANALYSIS AND MOTION ESTIMATION IN DIGITAL VIDEO WITH PYTHON AND TKINTER Vivian Siahaan, Rismon Hasiholan Sianipar, 2024-04-11 The first project, the GUI motion analysis tool gui_motion_analysis_fsbm.py, employs the Full Search Block Matching (FSBM) algorithm to analyze motion in videos. It imports essential libraries like tkinter, PIL, imageio, cv2, and numpy for GUI creation, image manipulation, video reading, computer vision tasks, and numerical computations. The script organizes its functionalities within the VideoFSBMOpticalFlow class, managing GUI elements through methods like create_widgets() for layout management, open_video() for video selection, and toggle_play_pause() for video playback control. It employs the FSBM algorithm for optical flow estimation, utilizing methods like full_search_block_matching() for motion vector calculation and show_optical_flow() for displaying motion patterns. Ultimately, by combining user-friendly controls with powerful analytical capabilities, the script facilitates efficient motion analysis in videos. The second project gui_motion_analysis_fsbm_dsa.py aims to provide a comprehensive solution for optical flow analysis through a user-friendly graphical interface. Leveraging the Full Search Block Matching (FSBM) algorithm with the Diamond Search Algorithm (DSA) optimization, it enables users to estimate motion patterns within video sequences efficiently. By integrating these algorithms into a GUI environment built with Tkinter, the script facilitates intuitive exploration and analysis of motion dynamics in various applications such as object tracking, video compression, and robotics. Key features include video file input, playback control, parameter adjustment, zooming capabilities, and optical flow visualization. Users can interactively analyze videos frame by frame, adjust algorithm parameters to tailor performance, and zoom in on specific regions of interest for detailed examination. Error handling mechanisms ensure robustness, while support for multiple instances enables simultaneous analysis of multiple videos. In essence, the project empowers users to gain insights into motion behaviors within video content, enhancing their ability to make informed decisions in diverse fields reliant on optical flow analysis. The third project Optical Flow Analysis with Three-Step Search (TSS) is dedicated to offering a user-friendly graphical interface for motion analysis in video sequences through the application of the Three-Step Search (TSS) algorithm. Optical flow analysis, pivotal in computer vision, facilitates tasks like video surveillance and object tracking. The implementation of TSS within the GUI environment allows users to efficiently estimate motion, empowering them with tools for detailed exploration and understanding of motion dynamics. Through its intuitive graphical interface, the project enables users to interactively engage with video content, from opening and previewing video files to controlling playback and navigating frames. Furthermore, it facilitates parameter customization, allowing users to fine-tune settings such as zoom scale and block size for tailored optical flow analysis. By overlaying visualizations of motion vectors on video frames, users gain insights into motion patterns, fostering deeper comprehension and analysis. Additionally, the project promotes community collaboration, serving as an educational resource and a platform for benchmarking different optical flow algorithms, ultimately advancing the field of computer vision technology. The fourth project gui_motion_analysis_bgds.py is developed with the primary objective of providing a user-friendly graphical interface (GUI) application for analyzing optical flow within video sequences, utilizing the Block-based Gradient Descent Search (BGDS) algorithm. Its purpose is to facilitate comprehensive exploration and understanding of motion patterns in video data, catering to diverse domains such as computer vision, video surveillance, and human-computer interaction. By offering intuitive controls and interactive functionalities, the application empowers users to delve into the intricacies of motion dynamics, aiding in research, education, and practical applications. Through the GUI interface, users can seamlessly open and analyze video files, spanning formats like MP4, AVI, or MKV, thus enabling thorough examination of motion behaviors within different contexts. The application supports essential features such as video playback control, zoom adjustment, frame navigation, and parameter customization. Leveraging the BGDS algorithm, motion vectors are computed at the block level, furnishing users with detailed insights into motion characteristics across successive frames. Additionally, the GUI facilitates real-time visualization of computed optical flow fields alongside original video frames, enhancing users' ability to interpret and analyze motion information effectively. With support for multiple instances and configurable parameters, the application caters to a broad spectrum of users, serving as a versatile tool for motion analysis endeavors in various professional and academic endeavors. The fifth project gui_motion_analysis_hbm2.py serves as a comprehensive graphical user interface (GUI) application tailored for optical flow analysis in video files. Leveraging the Tkinter library, it provides a user-friendly platform for scrutinizing the apparent motion of objects between consecutive frames, essential for various applications like object tracking and video compression. The algorithm of choice for optical flow analysis is the Hierarchical Block Matching (HBM) technique enhanced with the Three-Step Search (TSS) optimization, renowned for its effectiveness in motion estimation tasks. Primarily, the GUI layout encompasses a video display panel alongside control buttons facilitating actions such as video file opening, playback control, frame navigation, and parameter specification for optical flow analysis. Users can seamlessly open supported video files (e.g., MP4, AVI, MKV) and adjust parameters like zoom scale, step size, block size, and search range to tailor the analysis according to their needs. Through interactive features like zooming, panning, and dragging to manipulate the optical flow visualization, users gain insights into motion patterns with ease. Furthermore, the application supports additional functionalities such as time-based navigation, parallel analysis through multiple instances, ensuring a versatile and user-centric approach to optical flow analysis. The sixth project object_tracking_fsbm.py is designed to showcase object tracking capabilities using the Full Search Block Matching Algorithm (FSBM) within a user-friendly graphical interface (GUI) developed with Tkinter. By integrating this algorithm with a robust GUI, the project aims to offer a practical demonstration of object tracking techniques commonly utilized in computer vision applications. Upon execution, the script initializes a Tkinter window and sets up essential widgets for video display, playback control, and parameter adjustment. Users can seamlessly open video files in various formats and navigate through frames with intuitive controls, facilitating efficient analysis and tracking of objects. Leveraging the FSBM algorithm, object tracking is achieved by comparing pixel blocks between consecutive frames to estimate motion vectors, enabling real-time visualization of object movements within the video stream. The GUI provides interactive features like bounding box initialization, parameter adjustment, and zoom functionality, empowering users to fine-tune the tracking process and analyze objects with precision. Overall, the project serves as a comprehensive platform for object tracking, combining algorithmic prowess with an intuitive interface for effective analysis and visualization of object motion in video streams. The seventh project showcases an object tracking application seamlessly integrated with a graphical user interface (GUI) developed using Tkinter. Users can effortlessly interact with video files of various formats (MP4, AVI, MKV, WMV) through intuitive controls such as play, pause, and stop for video playback, as well as frame-by-frame navigation. The GUI further enhances user experience by providing zoom functionality for detailed examination of video content, contributing to a comprehensive and user-friendly environment. Central to the application is the implementation of the Diamond Search Algorithm (DSA) for object tracking, enabling the calculation of motion vectors between consecutive frames. These motion vectors facilitate the dynamic adjustment of a bounding box around the tracked object, offering visual feedback to users. Leveraging event handling mechanisms like mouse wheel scrolling and button press-and-drag, along with error handling for smooth operation, the project demonstrates the practical fusion of computer vision techniques with GUI development, exemplifying the real-world application of algorithms like DSA in object tracking scenarios. The eight project aims to provide an interactive graphical user interface (GUI) application for object tracking, employing the Three-Step Search (TSS) algorithm for motion estimation. The ObjectTrackingFSBM_TSS class defines the GUI layout, featuring essential widgets for video display, control buttons, and parameter inputs for block size and search range. Users can effortlessly interact with the application, from opening video files to controlling video playback and adjusting tracking parameters, facilitating seamless exploration of object motion within video sequences. Central to the application's functionality are the full_search_block_matching_tss() and track_object() methods, responsible for implementing the TSS algorithm and object tracking process, respectively. The full_search_block_matching_tss() method iterates over blocks in consecutive frames, utilizing TSS to calculate motion vectors. These vectors are then used in the track_object() method to update the bounding box around the object of interest, enabling real-time tracking. The GUI dynamically displays video frames and updates the bounding box position, providing users with a comprehensive tool for interactive object tracking and motion analysis. The ninth project encapsulates an object tracking application utilizing the Block-based Gradient Descent Search (BGDS) algorithm, providing users with a user-friendly interface developed using the Tkinter library for GUI and OpenCV for video processing. Upon initialization, the class orchestrates the setup of GUI components, offering intuitive controls for video manipulation and parameter configuration to enhance the object tracking process. Users can seamlessly open video files, control video playback, and adjust algorithm parameters such as block size, search range, iteration limit, and learning rate, empowering them with comprehensive tools for efficient motion estimation. The application's core functionality lies in the block_based_gradient_descent_search() method, implementing the BGDS algorithm for motion estimation by iteratively optimizing motion vectors over blocks in consecutive frames. Leveraging these vectors, the track_object() method dynamically tracks objects within a bounding box, computing mean motion vectors to update bounding box coordinates in real-time. Additionally, interactive features enable users to define bounding boxes around objects of interest through mouse events, facilitating seamless object tracking visualization. Overall, the ObjectTracking_BGDS class offers a versatile and user-friendly platform for object tracking, showcasing the practical application of the BGDS algorithm in real-world scenarios with enhanced ease of use and efficiency.
  audio video analysis in digital forensics: THE MOST BRUTAL AND BARBARIC CASE OF DIGITAL TAMPERING EVER, Unveiling the Truth Behind Jessica Wongso CCTV Footage Manipulation by Indonesian Police Officers: Tito Karnavian, Krishna Murti, Muhammad Nuh Al-Azhar, and Christopher Hariman Rianto RISMON HASIHOLAN SIANIPAR, 2024-09-14 The case of Jessica Kumala Wongso garnered significant attention due to its complex and contentious nature. It began with the mysterious death of Mirna Salihin, who collapsed and died shortly after consuming a coffee at a café in Jakarta, Indonesia, in January 2016. Jessica Kumala Wongso, a close friend of Mirna, was accused of poisoning her with cyanide-laced coffee, leading to her arrest and subsequent trial. The trial unfolded with intense scrutiny from the media and the public, as well as heated debates surrounding the evidence presented. The prosecution argued that Jessica had a motive to harm Mirna due to personal conflicts, while the defense contended that there was insufficient evidence to prove Jessica's guilt beyond a reasonable doubt. The case delved into various aspects, including forensic analysis of CCTV footage, witness testimonies, and expert opinions, further complicating the legal proceedings. After a lengthy trial spanning several months, Jessica Kumala Wongso was ultimately convicted of premeditated murder and sentenced to 20 years in prison in October 2016. The case sparked widespread discussions about the reliability of forensic evidence, the integrity of legal proceedings, and the role of the media in shaping public perception. Despite the verdict, the case continues to be a subject of controversy and debate, with many questioning the fairness and transparency of the trial process. The manipulation of Café Olivier's CCTV footage through downscaling played a pivotal role in the legal proceedings of Jessica Wongso's case. Downscaling refers to the deliberate reduction of the video's resolution, from a higher resolution 1920x1080 pixels (1080P) to a lower one 960x576 pixels (960H). Throughout the trial, forensic experts, including those appointed by Wongso's defense team, revealed how this manipulation technique obscured crucial details and compromised the integrity of the evidence presented. As the trial unfolded, it became evident that the downscaling of CCTV footage significantly impacted the perception of events. The reduced resolution made it challenging for the court to discern specific actions or movements, leading to debates over the accuracy and reliability of the footage. Moreover, the discrepancies introduced by downscaling raised doubts about the prosecution's narrative and highlighted the need for comprehensive forensic analysis to uncover the truth. Ultimately, the revelation of digital tampering through downscaling became a focal point of Wongso's defense strategy. By exposing the manipulation of evidence, Wongso's legal team aimed to cast doubt on the prosecution's case and challenge the credibility of the allegations against her. The downscaling of CCTV footage emerged as a critical factor in the trial's proceedings, underscoring the importance of technological expertise and forensic scrutiny in the pursuit of justice. From my perspective, addressing an international audience, it is paramount to shed light on one of the most egregious instances of digital manipulation and tampering witnessed in recent history. This pertains to the CCTV footage from Café Olivier, which has been subjected to a series of calculated alterations by two individuals acting as digital forensic experts within the Indonesian police force: Muhammad Nuh Al-Azhar and Christopher Hariman Rianto. Their actions constitute a flagrant disregard for truth and justice, warranting a comprehensive examination to uncover the extent of their deceit and the repercussions thereof. The manipulation of CCTV footage from Café Olivier represents a brazen attempt to distort reality and obfuscate the truth. Through their purported expertise in digital forensics, Muhammad Nuh Al-Azhar and Christopher Hariman Rianto orchestrated a meticulous campaign of alteration, wherein crucial details and events within the footage were systematically tampered with or omitted altogether. This manipulation extends beyond mere technical adjustments; it undermines the integrity of the entire legal process and threatens the very foundation of justice.
  audio video analysis in digital forensics: AIRLINE PASSENGER SATISFACTION Analysis and Prediction Using Machine Learning and Deep Learning with Python Vivian Siahaan, Rismon Hasiholan Sianipar, 2023-08-08 In the project Airline Passenger Satisfaction Analysis and Prediction Using Machine Learning and Deep Learning with Python, the aim was to analyze and predict passenger satisfaction in the airline industry. The project began with an extensive data exploration phase, wherein the dataset containing various features related to passenger experiences was thoroughly examined. The dataset was then preprocessed, ensuring data cleanliness and preparing it for further analysis. One of the initial steps involved understanding the distribution of categorized features within the dataset. By visualizing the distribution of these features, insights were gained into the prevalence of different categories, providing a preliminary understanding of passenger preferences and experiences. For the prediction aspect, machine learning models were employed, and a Grid Search approach was implemented to fine-tune hyperparameters and optimize model performance. This process allowed the identification of the best-performing model configuration, enhancing the accuracy of passenger satisfaction predictions. The models used are Logistic Regression, Support Vector Machines, K-Nearest Neighbors, Decision Trees, Random Forests, Gradient Boosting, Extreme Gradient Boosting, Light Gradient Boosting. Going beyond traditional machine learning, a Deep Learning approach was introduced using an Artificial Neural Network (ANN). This model, designed to capture intricate patterns and relationships within the data, showcased the potential of deep learning for improving predictive accuracy. The evaluation of both machine learning and deep learning models was centered around key metrics. The accuracy score was a primary indicator of model performance, reflecting the ratio of correctly predicted passenger satisfaction outcomes. Additionally, the Classification Report provided a comprehensive overview of precision, recall, and F1-score for each category, shedding light on the model's ability to classify passenger satisfaction levels accurately. Visualizing the results played a pivotal role in the project. The plotted Training and Validation Accuracy and Loss graphs offered insights into the convergence and generalization capabilities of the models. These visualizations helped in understanding potential overfitting or underfitting issues and guided the fine-tuning process. To assess the models' predictive performance, a Confusion Matrix was constructed. This matrix presented a clear breakdown of correct and incorrect predictions, facilitating an understanding of where the model excelled and where it struggled. Furthermore, scatter plots were utilized to visually compare the predicted values against the actual true values, offering a tangible representation of the models' effectiveness. Throughout the project, rigorous data preprocessing and feature engineering were integral to improving model accuracy. Features were appropriately scaled, and categorical variables were transformed using techniques like one-hot encoding, enabling models to efficiently learn from the data. The project also focused on the interpretability of the models, enabling stakeholders to comprehend the factors influencing passenger satisfaction predictions. This interpretability was essential for making informed business decisions based on the model insights. In conclusion, the project showcased a comprehensive approach to analyzing and predicting airline passenger satisfaction. Through meticulous data exploration, feature distribution analysis, machine learning model selection, hyperparameter tuning, and deep learning implementation, the project provided valuable insights for the airline industry. By utilizing a combination of machine learning and deep learning techniques, the project demonstrated a holistic approach to understanding and enhancing passenger experiences and satisfaction levels.
  audio video analysis in digital forensics: Credit Card Churning Customer Analysis and Prediction Using Machine Learning and Deep Learning with Python Vivian Siahaan, Rismon Hasiholan Sianipar, 2023-07-18 The project Credit Card Churning Customer Analysis and Prediction Using Machine Learning and Deep Learning with Python involved a comprehensive analysis and prediction task focused on understanding customer attrition in a credit card churning scenario. The objective was to explore a dataset, visualize the distribution of features, and predict the attrition flag using both machine learning and artificial neural network (ANN) techniques. The project began by loading the dataset containing information about credit card customers, including various features such as customer demographics, transaction details, and account attributes. The dataset was then explored to gain a better understanding of its structure and contents. This included checking the number of records, identifying the available features, and inspecting the data types. To gain insights into the data, exploratory data analysis (EDA) techniques were employed. This involved examining the distribution of different features, identifying any missing values, and understanding the relationships between variables. Visualizations were created to represent the distribution of features. These visualizations helped identify any patterns, outliers, or potential correlations in the data. The target variable for prediction was the attrition flag, which indicated whether a customer had churned or not. The dataset was split into input features (X) and the target variable (y) accordingly. Machine learning algorithms were then applied to predict the attrition flag. Various classifiers such as Logistic Regression, Decision Trees, Random Forests, Support Vector Machines (SVM), K-Nearest Neighbors (NN), Gradient Boosting, Extreme Gradient Boosting, Light Gradient Boosting, were utilized. These models were trained using the training dataset and evaluated using appropriate performance metrics. Model evaluation involved measuring the accuracy, precision, recall, and F1-score of each classifier. These metrics provided insights into how well the models performed in predicting customer attrition. Additionally, a confusion matrix was created to analyze the true positive, true negative, false positive, and false negative predictions. This matrix allowed for a deeper understanding of the classifier's performance and potential areas for improvement. Next, a deep learning approach using an artificial neural network (ANN) was employed for attrition flag prediction. The dataset was preprocessed, including features normalization, one-hot encoding of categorical variables, and splitting into training and testing sets. The ANN model architecture was defined, consisting of an input layer, one or more hidden layers, and an output layer. The number of nodes and activation functions for each layer were determined based on experimentation and best practices. The ANN model was compiled by specifying the loss function, optimizer, and evaluation metrics. Common choices for binary classification problems include binary cross-entropy loss and the Adam optimizer. The model was then trained using the training dataset. The training process involved feeding the input features and target variable through the network, updating the weights and biases using backpropagation, and repeating this process for multiple epochs. During training, the model's performance on both the training and validation sets was monitored. This allowed for the detection of overfitting or underfitting and the adjustment of hyperparameters, such as the learning rate or the number of hidden layers, if necessary. The accuracy and loss values were plotted over the epochs to visualize the training and validation performance of the ANN. These plots provided insights into the model's convergence and potential areas for improvement. After training, the model was used to make predictions on the test dataset. A threshold of 0.5 was applied to the predicted probabilities to classify the predictions as either churned or not churned customers. The accuracy score was calculated by comparing the predicted labels with the true labels from the test dataset. Additionally, a classification report was generated, including metrics such as precision, recall, and F1-score for both churned and not churned customers. To further evaluate the model's performance, a confusion matrix was created. This matrix visualized the true positive, true negative, false positive, and false negative predictions, allowing for a more detailed analysis of the model's predictive capabilities. Finally, a custom function was utilized to create a plot comparing the predicted values to the true values for the attrition flag. This plot visualized the accuracy of the model and provided a clear understanding of how well the predictions aligned with the actual values. Through this comprehensive analysis and prediction process, valuable insights were gained regarding customer attrition in credit card churning scenarios. The machine learning and ANN models provided predictions and performance metrics that can be used for decision-making and developing strategies to mitigate attrition. Overall, this project demonstrated the power of machine learning and deep learning techniques in understanding and predicting customer behavior. By leveraging the available data, it was possible to uncover patterns, make accurate predictions, and guide business decisions aimed at retaining customers and reducing attrition in credit card churning scenarios.
  audio video analysis in digital forensics: The Global Practice of Forensic Science Douglas H. Ubelaker, 2015-02-16 The Global Practice of Forensic Science presents histories, issues, patterns, and diversity in the applications of international forensic science. Written by 64 experienced and internationally recognized forensic scientists, the volume documents the practice of forensic science in 28 countries from Africa, the Americas, Asia, Australia and Europe. Each country’s chapter explores factors of political history, academic linkages, the influence of individual cases, facility development, types of cases examined, integration within forensic science, recruitment, training, funding, certification, accreditation, quality control, technology, disaster preparedness, legal issues, research and future directions. Aimed at all scholars interested in international forensic science, the volume provides detail on the diverse fields within forensic science and their applications around the world.
  audio video analysis in digital forensics: COVID-19: Analysis, Classification, and Detection Using Scikit-Learn, Keras, and TensorFlow with Python GUI Vivian Siahaan, Rismon Hasiholan Sianipar, 2023-08-11 In this comprehensive project, COVID-19: Analysis, Classification, and Detection Using Scikit-Learn, Keras, and TensorFlow with Python GUI, the primary objective is to leverage various machine learning and deep learning techniques to analyze and classify COVID-19 cases based on numerical data and medical image data. The project begins by exploring the dataset, gaining insights into its structure and content. This initial data exploration aids in understanding the distribution of categorized features, providing valuable context for subsequent analysis. With insights gained from data exploration, the project delves into predictive modeling using machine learning. It employs Scikit-Learn to build and fine-tune predictive models, harnessing grid search for hyperparameter optimization. This meticulous process ensures that the machine learning models, such as Naïve Bayes, K-Nearest Neighbors, Decision Trees, Random Forests, Gradient Boosting, Extreme Gradient Boosting, Multi-Layer Perceptron, AdaBoost, and Logistic Regression, are optimized to accurately predict the risk of COVID-19 based on the input features. Transitioning to the realm of deep learning, the project employs Convolutional Neural Networks (CNNs) to perform intricate image classification tasks. Leveraging Keras and TensorFlow, the CNN architecture is meticulously crafted, comprising convolutional and pooling layers, dropout regularization, and dense layers. The project also extends its deep learning capabilities by utilizing the VGG16 pre-trained model, harnessing its powerful feature extraction capabilities for COVID-19 image classification. To gauge the effectiveness of the trained models, an array of performance metrics is utilized. In this project, a range of metrics are used to evaluate the performance of machine learning and deep learning models employed for COVID-19 classification. These metrics include Accuracy, which measures the overall correctness of predictions; Precision, emphasizing the accuracy of positive predictions; Recall (Sensitivity), assessing the model's ability to identify positive instances; and F1-Score, a balanced measure of accuracy. The Mean Squared Error (MSE) quantifies the magnitude of errors in regression tasks, while the Confusion Matrix summarizes classification results by showing counts of true positives, true negatives, false positives, and false negatives. These metrics together provide a comprehensive understanding of model performance. They help gauge the model's accuracy, the balance between precision and recall, and its proficiency in classifying both positive and negative instances. In the medical context of COVID-19 classification, these metrics play a vital role in evaluating the models' reliability and effectiveness in real-world applications. The project further enriches its analytical capabilities by developing an interactive Python GUI. This graphical user interface streamlines the user experience, facilitating data input, model training, and prediction. Users are empowered to input medical images for classification, leveraging the trained machine learning and deep learning models to assess COVID-19 risk. The culmination of the project lies in the accurate prediction of COVID-19 risk through a combined approach of machine learning and deep learning techniques. The Python GUI using PyQt5 provides a user-friendly platform for clinicians and researchers to interact with the models, fostering informed decision-making based on reliable and data-driven predictions. In conclusion, this project represents a comprehensive endeavor to harness the power of machine learning and deep learning for the vital task of COVID-19 classification. Through rigorous data exploration, model training, and performance evaluation, the project yields a robust framework for risk prediction, contributing to the broader efforts to combat the ongoing pandemic.
  audio video analysis in digital forensics: HATE SPEECH DETECTION AND SENTIMENT ANALYSIS USING MACHINE LEARNING AND DEEP LEARNING WITH PYTHON GUI Vivian Siahaan, Rismon Hasiholan Sianipar, 2023-08-04 The purpose of this project is to develop a comprehensive Hate Speech Detection and Sentiment Analysis system using both Machine Learning and Deep Learning techniques. The project aims to create a robust and accurate system that can automatically identify hate speech in text data and perform sentiment analysis to determine the emotions and opinions expressed in the text. The project is designed to address the growing concern over the spread of hate speech and offensive content online. By implementing an automated detection system, it can help social media platforms, content moderators, and online communities to proactively identify and remove harmful content, fostering a safer and more inclusive online environment. Additionally, sentiment analysis plays a crucial role in understanding public opinions, customer feedback, and social media trends. By accurately predicting sentiment, businesses can make data-driven decisions, improve customer satisfaction, and gain valuable insights into consumer preferences. This project focuses on Hate Speech Detection and Sentiment Analysis using both Machine Learning and Deep Learning techniques. It begins with exploring the dataset, analyzing feature distributions, and predicting sentiment using Machine Learning models like Logistic Regression, Support Vector Machines, K-Nearest Neighbors, Decision Trees, Random Forests, Gradient Boosting, Extreme Gradient Boosting, Light Gradient Boosting, and AdaBoost, while optimizing their performance through Grid Search for hyperparameter tuning. Subsequently, Deep Learning LSTM and 1D CNN models are implemented for sentiment analysis to capture long-term dependencies and local patterns in the text data. The project starts with exploring the dataset, understanding its structure, and analyzing the distribution of classes for hate speech and sentiment labels. This initial step allows us to gain insights into the dataset and potential challenges. After exploring the data, the distribution of text features, such as word frequency and sentiment scores, is analyzed to identify any patterns or biases that could impact the model's performance. The dataset is then divided into training, validation, and testing sets to evaluate the models' generalization capabilities. Early stopping techniques are utilized during training to prevent overfitting and enhance model generalization. Performance evaluation involves calculating metrics like accuracy, precision, recall, and F1-score to gauge the models' effectiveness. Confusion matrices and visualizations provide further insights into model predictions and potential areas for improvement. A graphical user interface (GUI) is developed using PyQt to facilitate user interaction with the Hate Speech Detection and Sentiment Analysis system. Before training the Deep Learning models, the text data is tokenized and padded for uniform input sequences. The dataset is split into training and validation sets for model evaluation, and early stopping is used to prevent overfitting during training. The final system combines predictions from both Machine Learning and Deep Learning models to provide robust sentiment analysis results. The PyQt GUI allows users to input text and receive real-time sentiment analysis predictions. The LSTM and 1D CNN models, along with their optimized hyperparameters, are saved and deployed for future sentiment analysis tasks. Users can interact with the GUI, analyze sentiment in different texts, and provide feedback for continuous improvement of the Hate Speech Detection and Sentiment Analysis system.
A Simplified Guide To Forensic Audio and Video Analysis
To assist in an investigation, forensic experts can repair, recover, enhance and analyze audio and video recordings using an array of scientific tools and techniques.

Scientific Working Group on Digital Evidence - Swgde
Mar 22, 2024 · Forensic Video Analysis (FVA) is defined as the scientific examination, comparison, and/or evaluation of video in legal matters. Organizations may utilize different …

FORENSIC SPEECH AND AUDIO ANALYSIS WORKING GROUP …
The purpose of this document is to provide the Forensic Speech and Audio Analysis Working Group (FSAAWG) members, guidelines for ENF analysis in the area of forensic authentication …

Robert C. Maher Principles of Forensic Audio Analysis
Audio forensics is an essential specialty in modern forensic science. This book pro - vides the fundamental background necessary to understand and participate in this exciting and …

Audio Video Analysis In Digital Forensics (book)
Audio Video Analysis In Digital Forensics: Principles of Forensic Audio Analysis Robert C. Maher,2018-11-07 This book provides an expert introduction to audio forensics an essential …

WORKING PROCEDURE MANUAL SPEAKER IDENTIFICATION …
to be followed by forensic practitioners for speaker identification. The document also covers making direct and enhanced copy of the original evidence, preparation of speech exemplars, …

Forensic Analysis of Video File Formats - DFRWS
Forensic Analysis of Video File Formats By Thomas Gloe, Andre Fischer and Matthias Kirchner Presented At The Digital Forensic Research Conference DFRWS 2014 EU Amsterdam, NL …

Best Practices for the Acquisition of Digital Multimedia Evidence
Forensic Video Analysis is the scientific examination, comparison and/or evaluation of video in legal matters. DME is produced using processes of varying quality and reliability and requires …

Digital multimedia audio forensics: past, present and future
current state-of-the-art (SOA) in digital audio forensics and highlights some open research problems and future challenges in this active area of research. The paper categorizes the …

Audio Video Analysis In Digital Forensics Copy - bubetech.com
Audio Video Analysis In Digital Forensics Principles of Forensic Audio Analysis Robert C. Maher,2018-11-07 This book provides an expert introduction to audio forensics an essential …

Audio & Video Forensics – A new direction for electronic …
Audio and Video Forensics. Video evidence within the justice system is an ever-growing phenomenon, encapsulating different types of recordings such as from, mobile phones, …

Best Practices for the Retrieval of Video Evidence from Digital …
These best practices, guidelines and recommendations are intended to provide responding Law Enforcement personnel guidance in securing and collecting video data from DCCTV systems. …

Overview of Audio Forensics - Montana State University
Audio forensics applies the tools and techniques of audio engineering and digital signal processing to study audio data as part of a legal proceeding or an official investigation of some …

Audio Video Analysis In Digital Forensics - new.frcog.org
Audio Video Analysis In Digital Forensics: Principles of Forensic Audio Analysis Robert C. Maher,2018-11-07 This book provides an expert introduction to audio forensics an essential …

Forensic analysis of video file formats - DFRWS
help to authenticate digital video files in forensic settings by distinguishing between original and post-processed videos, verifying the purported source of a file, or identifying the true …

Best Practice Manual - ENFSI
This BPM addresses the forensic authenticity analysis of digital audio recordings. It provides recommendations concerning required resources, available scientifically validated methods

Audio enhancement and application of digital filters for …
This research focuses on the forensic expert analysis the “Forensic Work of Audio Enhancement” developed in the Forensic Digital Analysis Laboratory of the Bureau of Forensic Expert …

Audio Forensic Examination - Montana State University
There is potentially much to be gained by applying modern DSP theory to problems of interest to the forensics community, and this article is written to give the DSP audience some insight into …

Forensic Analysis and Enhancement of Digital Audio
Specifically, hands-on practice will include: digital evidence tools that can aid in the recovery of digital audio, spectral tools for forensic analysis including the FFT spectrum and spectrogram, …

A Simplified Guide To Forensic Audio and Video Analysis
To assist in an investigation, forensic experts can repair, recover, enhance and analyze audio and video recordings using an array of scientific tools and techniques.

Scientific Working Group on Digital Evidence - Swgde
Mar 22, 2024 · Forensic Video Analysis (FVA) is defined as the scientific examination, comparison, and/or evaluation of video in legal matters. Organizations may utilize different …

Video Evidence A Law Enforcement Guide to Resources and …
The purpose of this guide is to provide the best methods for the retrieval of video data evidence from digital closed circuit television (DCCTV) recording systems and to aid in the development …

FORENSIC SPEECH AND AUDIO ANALYSIS WORKING …
The purpose of this document is to provide the Forensic Speech and Audio Analysis Working Group (FSAAWG) members, guidelines for ENF analysis in the area of forensic authentication …

Robert C. Maher Principles of Forensic Audio Analysis
Audio forensics is an essential specialty in modern forensic science. This book pro - vides the fundamental background necessary to understand and participate in this exciting and …

Audio Video Analysis In Digital Forensics (book)
Audio Video Analysis In Digital Forensics: Principles of Forensic Audio Analysis Robert C. Maher,2018-11-07 This book provides an expert introduction to audio forensics an essential …

WORKING PROCEDURE MANUAL SPEAKER IDENTIFICATION …
to be followed by forensic practitioners for speaker identification. The document also covers making direct and enhanced copy of the original evidence, preparation of speech exemplars, …

Forensic Analysis of Video File Formats - DFRWS
Forensic Analysis of Video File Formats By Thomas Gloe, Andre Fischer and Matthias Kirchner Presented At The Digital Forensic Research Conference DFRWS 2014 EU Amsterdam, NL …

Best Practices for the Acquisition of Digital Multimedia Evidence
Forensic Video Analysis is the scientific examination, comparison and/or evaluation of video in legal matters. DME is produced using processes of varying quality and reliability and requires …

Digital multimedia audio forensics: past, present and future …
current state-of-the-art (SOA) in digital audio forensics and highlights some open research problems and future challenges in this active area of research. The paper categorizes the …

Audio Video Analysis In Digital Forensics Copy
Audio Video Analysis In Digital Forensics Principles of Forensic Audio Analysis Robert C. Maher,2018-11-07 This book provides an expert introduction to audio forensics an essential …

Audio & Video Forensics – A new direction for electronic …
Audio and Video Forensics. Video evidence within the justice system is an ever-growing phenomenon, encapsulating different types of recordings such as from, mobile phones, …

Best Practices for the Retrieval of Video Evidence from …
These best practices, guidelines and recommendations are intended to provide responding Law Enforcement personnel guidance in securing and collecting video data from DCCTV systems. …

Overview of Audio Forensics - Montana State University
Audio forensics applies the tools and techniques of audio engineering and digital signal processing to study audio data as part of a legal proceeding or an official investigation of some …

Audio Video Analysis In Digital Forensics - new.frcog.org
Audio Video Analysis In Digital Forensics: Principles of Forensic Audio Analysis Robert C. Maher,2018-11-07 This book provides an expert introduction to audio forensics an essential …

Forensic analysis of video file formats - DFRWS
help to authenticate digital video files in forensic settings by distinguishing between original and post-processed videos, verifying the purported source of a file, or identifying the true …

Best Practice Manual - ENFSI
This BPM addresses the forensic authenticity analysis of digital audio recordings. It provides recommendations concerning required resources, available scientifically validated methods

Audio enhancement and application of digital filters for …
This research focuses on the forensic expert analysis the “Forensic Work of Audio Enhancement” developed in the Forensic Digital Analysis Laboratory of the Bureau of Forensic Expert …

Audio Forensic Examination - Montana State University
There is potentially much to be gained by applying modern DSP theory to problems of interest to the forensics community, and this article is written to give the DSP audience some insight into …

Forensic Analysis and Enhancement of Digital Audio
Specifically, hands-on practice will include: digital evidence tools that can aid in the recovery of digital audio, spectral tools for forensic analysis including the FFT spectrum and spectrogram, …