Data Analysis In Forensic Science
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Big Data Analytics And Computing For Digital Forensic Investigations
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Author : Suneeta Satpathy
language : en
Publisher: CRC Press
Release Date : 2020-03-17
Big Data Analytics And Computing For Digital Forensic Investigations written by Suneeta Satpathy and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020-03-17 with Computers categories.
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.
Statistical Analysis In Forensic Science
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Author : Grzegorz Zadora
language : en
Publisher: John Wiley & Sons
Release Date : 2014-02-03
Statistical Analysis In Forensic Science written by Grzegorz Zadora and has been published by John Wiley & Sons this book supported file pdf, txt, epub, kindle and other format this book has been release on 2014-02-03 with Mathematics categories.
A practical guide for determining the evidential value of physicochemical data Microtraces of various materials (e.g. glass, paint, fibres, and petroleum products) are routinely subjected to physicochemical examination by forensic experts, whose role is to evaluate such physicochemical data in the context of the prosecution and defence propositions. Such examinations return various kinds of information, including quantitative data. From the forensic point of view, the most suitable way to evaluate evidence is the likelihood ratio. This book provides a collection of recent approaches to the determination of likelihood ratios and describes suitable software, with documentation and examples of their use in practice. The statistical computing and graphics software environment R, pre-computed Bayesian networks using Hugin Researcher and a new package, calcuLatoR, for the computation of likelihood ratios are all explored. Statistical Analysis in Forensic Science will provide an invaluable practical guide for forensic experts and practitioners, forensic statisticians, analytical chemists, and chemometricians. Key features include: Description of the physicochemical analysis of forensic trace evidence. Detailed description of likelihood ratio models for determining the evidential value of multivariate physicochemical data. Detailed description of methods, such as empirical cross-entropy plots, for assessing the performance of likelihood ratio-based methods for evidence evaluation. Routines written using the open-source R software, as well as Hugin Researcher and calcuLatoR. Practical examples and recommendations for the use of all these methods in practice.
Data Analysis In Forensic Science
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Author : Franco Taroni
language : en
Publisher: Wiley
Release Date : 2010-05-17
Data Analysis In Forensic Science written by Franco Taroni and has been published by Wiley this book supported file pdf, txt, epub, kindle and other format this book has been release on 2010-05-17 with Mathematics categories.
This is the first text to examine the use of statistical methods in forensic science and bayesian statistics in combination. The book is split into two parts: Part One concentrates on the philosophies of statistical inference. Chapter One examines the differences between the frequentist, the likelihood and the Bayesian perspectives, before Chapter Two explores the Bayesian decision-theoretic perspective further, and looks at the benefits it carries. Part Two then introduces the reader to the practical aspects involved: the application, interpretation, summary and presentation of data analyses are all examined from a Bayesian decision-theoretic perspective. A wide range of statistical methods, essential in the analysis of forensic scientific data is explored. These include the comparison of allele proportions in populations, the comparison of means, the choice of sampling size, and the discrimination of items of evidence of unknown origin into predefined populations. Throughout this practical appraisal there are a wide variety of examples taken from the routine work of forensic scientists. These applications are demonstrated in the ever-more popular R language. The reader is taken through these applied examples in a step-by-step approach, discussing the methods at each stage.
Introduction To Data Analysis With R For Forensic Scientists
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Author : James Michael Curran
language : en
Publisher: CRC Press
Release Date : 2010-07-30
Introduction To Data Analysis With R For Forensic Scientists written by James Michael Curran and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2010-07-30 with Law categories.
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
Statistical Dna Forensics
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Author : Wing Kam Fung
language : en
Publisher: John Wiley & Sons
Release Date : 2008-04-15
Statistical Dna Forensics written by Wing Kam Fung and has been published by John Wiley & Sons this book supported file pdf, txt, epub, kindle and other format this book has been release on 2008-04-15 with Mathematics categories.
Statistical methodology plays a key role in ensuring that DNA evidence is collected, interpreted, analyzed and presented correctly. With the recent advances in computer technology, this methodology is more complex than ever before. There are a growing number of books in the area but none are devoted to the computational analysis of evidence. This book presents the methodology of statistical DNA forensics with an emphasis on the use of computational techniques to analyze and interpret forensic evidence.
Forensic Analytics
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Author : Mark J. Nigrini
language : en
Publisher: John Wiley & Sons
Release Date : 2020-05-12
Forensic Analytics written by Mark J. Nigrini and has been published by John Wiley & Sons this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020-05-12 with Business & Economics categories.
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.
Technology In Forensic Science
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Author : Deepak Rawtani
language : en
Publisher: John Wiley & Sons
Release Date : 2020-11-02
Technology In Forensic Science written by Deepak Rawtani and has been published by John Wiley & Sons this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020-11-02 with Medical categories.
The book "Technology in Forensic Science" provides an integrated approach by reviewing the usage of modern forensic tools as well as the methods for interpretation of the results. Starting with best practices on sample taking, the book then reviews analytical methods such as high-resolution microscopy and chromatography, biometric approaches, and advanced sensor technology as well as emerging technologies such as nanotechnology and taggant technology. It concludes with an outlook to emerging methods such as AI-based approaches to forensic investigations.
Big Digital Forensic Data
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Author : Darren Quick
language : en
Publisher: Springer
Release Date : 2018-06-12
Big Digital Forensic Data written by Darren Quick and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2018-06-12 with Computers categories.
This book provides an in-depth understanding of big data challenges to digital forensic investigations, also known as big digital forensic data. It also develops the basis of using data mining in big forensic data analysis, including data reduction, knowledge management, intelligence, and data mining principles to achieve faster analysis in digital forensic investigations. By collecting and assembling a corpus of test data from a range of devices in the real world, it outlines a process of big digital forensic data analysis for evidence and intelligence. It includes the results of experiments on vast volumes of real digital forensic data. The book is a valuable resource for digital forensic practitioners, researchers in big data, cyber threat hunting and intelligence, data mining and other related areas.
Analytical Techniques In Forensic Science
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Author : Rosalind Wolstenholme
language : en
Publisher: John Wiley & Sons
Release Date : 2021-01-26
Analytical Techniques In Forensic Science written by Rosalind Wolstenholme and has been published by John Wiley & Sons this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021-01-26 with Medical categories.
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.
Big Digital Forensic Data
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Author : Darren Quick
language : en
Publisher: Springer
Release Date : 2018-04-24
Big Digital Forensic Data written by Darren Quick and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2018-04-24 with Computers categories.
This book provides an in-depth understanding of big data challenges to digital forensic investigations, also known as big digital forensic data. It also develops the basis of using data mining in big forensic data analysis, including data reduction, knowledge management, intelligence, and data mining principles to achieve faster analysis in digital forensic investigations. By collecting and assembling a corpus of test data from a range of devices in the real world, it outlines a process of big data reduction, and evidence and intelligence extraction methods. Further, it includes the experimental results on vast volumes of real digital forensic data. The book is a valuable resource for digital forensic practitioners, researchers in big data, cyber threat hunting and intelligence, data mining and other related areas.