Data Mining for Intelligence Fraud Criminal Detection

Author: Christopher Westphal
Publisher: CRC Press
ISBN: 9781420067248
Format: PDF, ePub
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In 2004, the Government Accountability Office provided a report detailing approximately 200 government-based data-mining projects. While there is comfort in knowing that there are many effective systems, that comfort isn’t worth much unless we can determine that these systems are being effectively and responsibly employed. Written by one of the most respected consultants in the area of data mining and security, Data Mining for Intelligence, Fraud & Criminal Detection: Advanced Analytics & Information Sharing Technologies reviews the tangible results produced by these systems and evaluates their effectiveness. While CSI-type shows may depict information sharing and analysis that are accomplished with the push of a button, this sort of proficiency is more fiction than reality. Going beyond a discussion of the various technologies, the author outlines the issues of information sharing and the effective interpretation of results, which are critical to any integrated homeland security effort. Organized into three main sections, the book fully examines and outlines the future of this field with an insider’s perspective and a visionary’s insight. Section 1 provides a fundamental understanding of the types of data that can be used in current systems. It covers approaches to analyzing data and clearly delineates how to connect the dots among different data elements Section 2 provides real-world examples derived from actual operational systems to show how data is used, manipulated, and interpreted in domains involving human smuggling, money laundering, narcotics trafficking, and corporate fraud Section 3 provides an overview of the many information-sharing systems, organizations, and task forces as well as data interchange formats. It also discusses optimal information-sharing and analytical architectures Currently, there is very little published literature that truly defines real-world systems. Although politics and other factors all play into how much one agency is willing to support the sharing of its resources, many now embrace the wisdom of that path. This book will provide those individuals with an understanding of what approaches are currently available and how they can be most effectively employed.

Investigative Data Mining for Security and Criminal Detection

Author: Jesus Mena
Publisher: Elsevier
ISBN: 008050938X
Format: PDF, Kindle
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Investigative Data Mining for Security and Criminal Detection is the first book to outline how data mining technologies can be used to combat crime in the 21st century. It introduces security managers, law enforcement investigators, counter-intelligence agents, fraud specialists, and information security analysts to the latest data mining techniques and shows how they can be used as investigative tools. Readers will learn how to search public and private databases and networks to flag potential security threats and root out criminal activities even before they occur. The groundbreaking book reviews the latest data mining technologies including intelligent agents, link analysis, text mining, decision trees, self-organizing maps, machine learning, and neural networks. Using clear, understandable language, it explains the application of these technologies in such areas as computer and network security, fraud prevention, law enforcement, and national defense. International case studies throughout the book further illustrate how these technologies can be used to aid in crime prevention. Investigative Data Mining for Security and Criminal Detection will also serve as an indispensable resource for software developers and vendors as they design new products for the law enforcement and intelligence communities. Key Features: * Covers cutting-edge data mining technologies available to use in evidence gathering and collection * Includes numerous case studies, diagrams, and screen captures to illustrate real-world applications of data mining * Easy-to-read format illustrates current and future data mining uses in preventative law enforcement, criminal profiling, counter-terrorist initiatives, and forensic science * Introduces cutting-edge technologies in evidence gathering and collection, using clear non-technical language * Illustrates current and future applications of data mining tools in preventative law enforcement, homeland security, and other areas of crime detection and prevention * Shows how to construct predictive models for detecting criminal activity and for behavioral profiling of perpetrators * Features numerous Web links, vendor resources, case studies, and screen captures illustrating the use of artificial intelligence (AI) technologies

Fraud Analytics

Author: Delena D. Spann
Publisher: John Wiley & Sons
ISBN: 1118282736
Format: PDF, ePub
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Proven guidance for expertly using analytics in fraud examinations, financial analysis, auditing and fraud prevention Fraud Analytics thoroughly reveals the elements of analysis that are used in today's fraud examinations, fraud investigations, and financial crime investigations. This valuable resource reviews the types of analysis that should be considered prior to beginning an investigation and explains how to optimally use data mining techniques to detect fraud. Packed with examples and sample cases illustrating pertinent concepts in practice, this book also explores the two major data analytics providers: ACL and IDEA. Looks at elements of analysis used in today's fraud examinations Reveals how to use data mining (fraud analytic) techniques to detect fraud Examines ACL and IDEA as indispensable tools for fraud detection Includes an abundance of sample cases and examples Written by Delena D Spann, Board of Regent (Emeritus) for the Association of Certified Fraud Examiners (ACFE), who currently serves as Advisory Board Member of the Association of Certified Fraud Examiners, Board Member of the Education Task Force of the Association of Certified Anti-Money Laundering Specialists ASIS International (Economic Crime Council) and Advisory Board Member of the Robert Morris University (School of Business), Fraud Analytics equips you with authoritative fraud analysis techniques you can put to use right away.

Bank Fraud

Author: Revathi Subramanian
Publisher: John Wiley & Sons
ISBN: 0470494395
Format: PDF, Kindle
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"Capitalize on technology to halt bank fraudExamining the technology that is needed to combat bank fraud, Bank Fraud: Using Technology to Combat Losses equips corporate security and loss prevention managers with the necessary tools to determine an organization's unique technology needs. Looks at the technology needed to handle data intelligence Provides guidance to assess the technology necessary to battle fraud Features unique coverage of the history of fraud detection and prevention in banking Explores the challenges of fraud detection in a financial services environment; understanding corporate risk exposure; losses per assets; trending over time; benefits of technology Focusing on the financial crimes and insider frauds in operation nationally and internationally, Bank Fraud: Using Technology to Combat Losses arms fraud prevention professionals with authoritative guidance to detect and prevent such crimes in future"--

Data mining solutions

Author: Christopher Ralph Westphal
Publisher: John Wiley & Sons Inc
ISBN:
Format: PDF, Docs
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Cutting-edge data mining techniques and tools for solving your toughest analytical problems Data Mining Solutions In down-to-earth language, data mining experts Christopher Westphal and Teresa Blaxton introduce a brand new approach to data mining analysis. Through their extensive real-world experience, they have developed and documented many practical and proven techniques to make your own data mining efforts more successful. You'll get a refreshing "out-of-the-box" approach to data mining that will help you maximize your time and problem-solving resources, and prepare for the next wave of data mining-visualization. You will read about ways in which data mining has been used to: * Discover patterns of insider trading in the stock market * Evaluate the utility of marketing campaigns * Analyze retail sales patterns across geographic regions * Identify money laundering operations * Target DNA sequences for pharmaceutical testing and development The book is accompanied by a CD-ROM that contains: * Demo and trial versions of numerous visual data mining tools * Active web-page links for each of the products profiled * GIF files corresponding to all book images

Knowledge Management in Emerging Economies Social Organizational and Cultural Implementation

Author: Al-Shammari, Minwir
Publisher: IGI Global
ISBN: 1616928883
Format: PDF, Mobi
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Knowledge Management in Emerging Economies: Social, Organizational and Cultural Implementation seeks focuses on knowledge management theoretical models and empirical research findings for developing economies. This book specifically seeks to understand the social, organizational, and cultural implementation aspects of knowledge management in the context of developing economies, and to discuss issues, challenges, and trends surrounding this implementation.

Applied Predictive Modeling

Author: Max Kuhn
Publisher: Springer Science & Business Media
ISBN: 1461468493
Format: PDF, ePub
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Applied Predictive Modeling covers the overall predictive modeling process, beginning with the crucial steps of data preprocessing, data splitting and foundations of model tuning. The text then provides intuitive explanations of numerous common and modern regression and classification techniques, always with an emphasis on illustrating and solving real data problems. The text illustrates all parts of the modeling process through many hands-on, real-life examples, and every chapter contains extensive R code for each step of the process. This multi-purpose text can be used as an introduction to predictive models and the overall modeling process, a practitioner’s reference handbook, or as a text for advanced undergraduate or graduate level predictive modeling courses. To that end, each chapter contains problem sets to help solidify the covered concepts and uses data available in the book’s R package. This text is intended for a broad audience as both an introduction to predictive models as well as a guide to applying them. Non-mathematical readers will appreciate the intuitive explanations of the techniques while an emphasis on problem-solving with real data across a wide variety of applications will aid practitioners who wish to extend their expertise. Readers should have knowledge of basic statistical ideas, such as correlation and linear regression analysis. While the text is biased against complex equations, a mathematical background is needed for advanced topics.

Introduction to Law Enforcement

Author: David H. McElreath
Publisher: CRC Press
ISBN: 1466556234
Format: PDF
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Modern perspectives of law enforcement are both complex and diverse. They integrate management and statistical analysis functions, public and business administration functions, and applications of psychology, natural science, physical fitness, and marksmanship. They also assimilate theories of education, organizational behavior, economics, law and public policy, and many others. Modern law enforcement is a blend of both theoretical knowledge and applied practice that continuously changes through time. With contributions by nine authors offering a diverse presentation, Introduction to Law Enforcement goes beyond the linear perspective found in most law enforcement texts and offers multiple perspectives and discussions regarding both private and public entities. Through this approach, readers gain an understanding of several dimensions of the subject matter. Topics discussed include: Contemporary crime trends Policing ethics Law enforcement history The functions of modern law enforcement agencies Homeland security Public service Human resources The path of a case from arrest through incarceration and post-release Local, state, regional, federal, and tribal law enforcement agencies Private enforcement organizations Adaptable across a wide range of learning environments, the book uses a convenient format organized by agency type. Pedagogical features include learning objectives, case studies, and discussion questions to facilitate reader assimilation of the material. Comprehensive in scope, the text presents a robust consideration of the law enforcement domain.

Data Mining and Predictive Analysis

Author: Colleen McCue
Publisher: Butterworth-Heinemann
ISBN: 0128004088
Format: PDF
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Data Mining and Predictive Analysis: Intelligence Gathering and Crime Analysis, 2nd Edition, describes clearly and simply how crime clusters and other intelligence can be used to deploy security resources most effectively. Rather than being reactive, security agencies can anticipate and prevent crime through the appropriate application of data mining and the use of standard computer programs. Data Mining and Predictive Analysis offers a clear, practical starting point for professionals who need to use data mining in homeland security, security analysis, and operational law enforcement settings. This revised text highlights new and emerging technology, discusses the importance of analytic context for ensuring successful implementation of advanced analytics in the operational setting, and covers new analytic service delivery models that increase ease of use and access to high-end technology and analytic capabilities. The use of predictive analytics in intelligence and security analysis enables the development of meaningful, information based tactics, strategy, and policy decisions in the operational public safety and security environment. Discusses new and emerging technologies and techniques, including up-to-date information on predictive policing, a key capability in law enforcement and security Demonstrates the importance of analytic context beyond software Covers new models for effective delivery of advanced analytics to the operational environment, which have increased access to even the most powerful capabilities Includes terminology, concepts, practical application of these concepts, and examples to highlight specific techniques and approaches in crime and intelligence analysis