Discover how to detect fraud, biases, or errors in your data using Access or Excel With over 300 images, Forensic Analytics reviews and shows how twenty substantive and rigorous tests can be used to detect fraud, errors, estimates, or biases in your data. For each test, the original data is shown with the steps needed to get to the final result. The tests range from high-level data overviews to assess the reasonableness of data, to highly focused tests that give small samples of highly suspicious transactions. These tests are relevant to your organization, whether small or large, for profit, nonprofit, or government-related. Demonstrates how to use Access, Excel, and PowerPoint in a forensic setting Explores use of statistical techniques such as Benford's Law, descriptive statistics, correlation, and time-series analysis to detect fraud and errors Discusses the detection of financial statement fraud using various statistical approaches Explains how to score locations, agents, customers, or employees for fraud risk Shows you how to become the data analytics expert in your organization Forensic Analytics shows how you can use Microsoft Access and Excel as your primary data interrogation tools to find exceptional, irregular, and anomalous records.

Become the forensic analytics expert in your organization using effective and efficient data analysis tests to find anomalies, biases, and potential fraud—the updated new edition Forensic Analytics reviews the methods and techniques that forensic accountants can use to detect intentional and unintentional errors, fraud, and biases. This updated second edition shows accountants and auditors how analyzing their corporate or public sector data can highlight transactions, balances, or subsets of transactions or balances in need of attention. These tests are made up of a set of initial high-level overview tests followed by a series of more focused tests. These focused tests use a variety of quantitative methods including Benford’s Law, outlier detection, the detection of duplicates, a comparison to benchmarks, time-series methods, risk-scoring, and sometimes simply statistical logic. The tests in the new edition include the newly developed vector variation score that quantifies the change in an array of data from one period to the next. The goals of the tests are to either produce a small sample of suspicious transactions, a small set of transaction groups, or a risk score related to individual transactions or a group of items. The new edition includes over two hundred figures. Each chapter, where applicable, includes one or more cases showing how the tests under discussion could have detected the fraud or anomalies. The new edition also includes two chapters each describing multi-million-dollar fraud schemes and the insights that can be learned from those examples. These interesting real-world examples help to make the text accessible and understandable for accounting professionals and accounting students without rigorous backgrounds in mathematics and statistics. Emphasizing practical applications, the new edition shows how to use either Excel or Access to run these analytics tests. The book also has some coverage on using Minitab, IDEA, R, and Tableau to run forensic-focused tests. The use of SAS and Power BI rounds out the software coverage. The software screenshots use the latest versions of the software available at the time of writing. This authoritative book: Describes the use of statistically-based techniques including Benford’s Law, descriptive statistics, and the vector variation score to detect errors and anomalies Shows how to run most of the tests in Access and Excel, and other data analysis software packages for a small sample of the tests Applies the tests under review in each chapter to the same purchasing card data from a government entity Includes interesting cases studies throughout that are linked to the tests being reviewed. Includes two comprehensive case studies where data analytics could have detected the frauds before they reached multi-million-dollar levels Includes a continually-updated companion website with the data sets used in the chapters, the queries used in the chapters, extra coverage of some topics or cases, end of chapter questions, and end of chapter cases. Written by a prominent educator and researcher in forensic accounting and auditing, the new edition of Forensic Analytics: Methods and Techniques for Forensic Accounting Investigations is an essential resource for forensic accountants, auditors, comptrollers, fraud investigators, and graduate students.

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.

An in-depth text that explores the interface between analytical chemistry and trace evidence Analytical Techniques in Forensic Science is a comprehensive guide written in accessible terms that examines the interface between analytical chemistry and trace evidence in forensic science. With contributions from noted experts on the topic, the text features a detailed introduction analysis in forensic science and then subsequent chapters explore the laboratory techniques grouped by shared operating principles. For each technique, the authors incorporate specific theory, application to forensic analytics, interpretation, forensic specific developments, and illustrative case studies. Forensic techniques covered include UV-Vis and vibrational spectroscopy, mass spectrometry and gas and liquid chromatography. The applications reviewed include evidence types such as fibers, paint, drugs and explosives. The authors highlight data collection, subsequent analysis, what information has been obtained and what this means in the context of a case. The text shows how analytical chemistry and trace evidence can problem solve the nature of much of forensic analysis. This important text: Puts the focus on trace evidence and analytical science Contains case studies that illustrate theory in practice Includes contributions from experts on the topics of instrumentation, theory, and case examples Explores novel and future applications for analytical techniques Written for undergraduate and graduate students in forensic chemistry and forensic practitioners and researchers, Analytical Techniques in Forensic Science offers a text that bridges the gap between introductory textbooks and professional level literature.

Statistical methods provide a logical, coherent framework in which data from experimental science can be analyzed. However, many researchers lack the statistical skills or resources that would allow them to explore their data to its full potential. Introduction to Data Analysis with R for Forensic Sciences minimizes theory and mathematics and focus

The Handbook of Forensic Drug Analysis is a comprehensive chemical and analytic reference for the forensic analysis of illicit drugs. With chapters written by leading researchers in the field, the book provides in-depth, up-to-date methods and results of forensic drug analyses. This Handbook discusses various forms of the drug as well as the origin and nature of samples. It explains how to perform various tests, the use of best practices, and the analysis of results. Numerous forensic and chemical analytic techniques are covered including immunoassay, gas chromatography, and mass spectrometry. Topics range from the use of immunoassay technologies for drugs-of-abuse testing, to methods of forensic analysis for cannabis, hallucinogens, cocaine, opioids, and amphetamine. The book also looks at synthetic methods and law enforcement concerns regarding the manufacture of illicit drugs, with an emphasis on clandestine methamphetamine production. This Handbook should serve as a widely used reference for forensic scientists, toxicologists, pharmacologists, drug companies, and professionals working in toxicology testing labs, libraries, and poison control centers. It may also be used by chemists, physicians and those in legal and regulatory professions, and students of graduate courses in forensic science. - Contributed to by leading scientists from around the world - The only analysis book dedicated to illicit drugs of abuse - Comprehensive coverage of sampling methods and various forms of analysis

A powerful new tool for all forensic accountants, or anyone whoanalyzes data that may have been altered Benford's Law gives the expected patterns of the digits in thenumbers in tabulated data such as town and city populations orMadoff's fictitious portfolio returns. Those digits, in unaltereddata, will not occur in equal proportions; there is a large biastowards the lower digits, so much so that nearly one-half of allnumbers are expected to start with the digits 1 or 2. Thesepatterns were originally discovered by physicist Frank Benford inthe early 1930s, and have since been found to apply to alltabulated data. Mark J. Nigrini has been a pioneer in applyingBenford's Law to auditing and forensic accounting, even before hisgroundbreaking 1999 Journal of Accountancy article introducing thisuseful tool to the accounting world. In Benford's Law, Nigrinishows the widespread applicability of Benford's Law and itspractical uses to detect fraud, errors, and other anomalies. Explores primary, associated, and advanced tests, all describedwith data sets that include corporate payments data and electiondata Includes ten fraud detection studies, including vendor fraud,payroll fraud, due diligence when purchasing a business, and taxevasion Covers financial statement fraud, with data from Enron, AIG,and companies that were the target of hedge fund short sales Looks at how to detect Ponzi schemes, including data on Madoff,Waxenberg, and more Examines many other applications, from the Clinton tax returnsand the charitable gifts of Lehman Brothers to tax evasion andnumber invention Benford's Law has 250 figures and uses 50 interestingauthentic and fraudulent real-world data sets to explain boththeory and practice, and concludes with an agenda and directionsfor future research. The companion website adds additionalinformation and resources.

The volume on Data Management, Analytics and Innovations presents the latest high-quality technical contributions and research results in the areas of data management and smart computing, big data management, artificial intelligence and data analytics along with advances in network technologies. It deals with the state-of-the-art topics and provides challenges and solutions for future development. Original, unpublished research work highlighting specific research domains from all viewpoints are contributed from scientists throughout the globe. This volume is mainly designed for professional audience, composed of researchers and practitioners in academia and industry.

Digital forensics has recently gained a notable development and become the most demanding area in today’s information security requirement. This book investigates the areas of digital forensics, digital investigation and data analysis procedures as they apply to computer fraud and cybercrime, with the main objective of describing a variety of digital crimes and retrieving potential digital evidence. Big Data Analytics and Computing for Digital Forensic Investigations gives a contemporary view on the problems of information security. It presents the idea that protective mechanisms and software must be integrated along with forensic capabilities into existing forensic software using big data computing tools and techniques. Features Describes trends of digital forensics served for big data and the challenges of evidence acquisition Enables digital forensic investigators and law enforcement agencies to enhance their digital investigation capabilities with the application of data science analytics, algorithms and fusion technique This book is focused on helping professionals as well as researchers to get ready with next-generation security systems to mount the rising challenges of computer fraud and cybercrimes as well as with digital forensic investigations. Dr Suneeta Satpathy has more than ten years of teaching experience in different subjects of the Computer Science and Engineering discipline. She is currently working as an associate professor in the Department of Computer Science and Engineering, College of Bhubaneswar, affiliated with Biju Patnaik University and Technology, Odisha. Her research interests include computer forensics, cybersecurity, data fusion, data mining, big data analysis and decision mining. Dr Sachi Nandan Mohanty is an associate professor in the Department of Computer Science and Engineering at ICFAI Tech, ICFAI Foundation for Higher Education, Hyderabad, India. His research interests include data mining, big data analysis, cognitive science, fuzzy decision-making, brain–computer interface, cognition and computational intelligence.

This book provides a line of communication between academia and end users/practitioners to advance forensic science and boost its contribution to criminal investigations and court cases. By covering the state of the art of promising technologies for the analysis of trace evidence using a controlled vocabulary, this book targets the forensics community as well as, crucially, informing the end users on novel and potential forensic opportunities for the fight against crime. By reporting end users commentaries at the end of each chapter, the relevant academic community is provided with clear indications on where to direct further technological developments in order to meet the law requirements for operational deployment, as well as the specific needs of the end users. Promising chemistry based technologies and analytical techniques as well as techniques that have already shown to various degrees an operational character are covered. The majority of the techniques covered have imaging capabilities, that is the ability to visualize the distribution of the target molecules within the trace evidence recovered. This feature enhances intelligibility of the information making it also accessible to a lay audience such as that typically found with a court jury. Trace evidence discussed in this book include fingermarks, bodily fluids, hair, gunshot residues, soil, ink and questioned documents thus covering a wide range of possible evidence recovered at crime scenes.