Data Mining for Intelligence Fraud Criminal Detection

Author: Christopher Westphal
Publisher: CRC Press
ISBN: 9781420067248
Format: PDF, Mobi
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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: Butterworth-Heinemann
ISBN: 9780750676137
Format: PDF, Mobi
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Data mining has traditionally been used to predict consumer behaviour, but in the wake of 9/11, the same tools and techniques can also be used to detect and validate the identity of threatening and criminal entities for security purposes.

Business Intelligence

Author: Roland M. Müller
Publisher: Springer-Verlag
ISBN: 3642355609
Format: PDF, ePub, Docs
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Das Buch befasst sich mit der Bereitstellung von Daten und Verfahren für analytische Zwecke (Planung, Entscheidung, Controlling sowie Fehlerrückverfolgung) in Unternehmen sowie der notwendigen Rechenleistungen. Die Autoren erläutern die Datenbereitstellung mittels Data Warehouses, Auswertung mittels OLAP-Operationalität und geeignete Verfahren der explorativen Datenanalyse. Bei den Verfahren des Operations Research werden Simulation und Lineare Optimierung dargestellt. Neben erfolgreichen Anwendungen und Fallstudien steht das Verständnis der zugrundeliegenden Algorithmen und Datenstrukturen, die für das Erlernen der BI-Verfahren zwingend notwendig sind, im Vordergrund.

Online Investigation im Due Diligence Prozess von Acquirer Banken

Author: Christian Chmiel
Publisher: BoD – Books on Demand
ISBN: 3839189039
Format: PDF
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In den letzten Jahren hat sich die Art des Kreditkartenbetrugs weltweit schrittweise ver ndert. Der Kreditkartenmissbrauch durch den Online-H ndler wurde eine immer gr ere Bedrohung sowohl f r die Kreditkartenorganisationen an sich als auch f r die angeschlossenen Acquirer- Banken. Das vorliegende Buch ist eine Best-Practice-L sung f r Mitarbeiter von Acquirer-Banken, die im Bereich Betrugs-, Compliance- oder Risikomanagement t tig sind. Es wird auf verschiedene Vorgehensweisen zur Online-Investigation, die dazu notwendigen Werkzeuge sowie die Interpretationsm glichkeiten eingegangen, um potentielle Betrugsabsichten von Online-H ndlern schon vor der dem Anschluss an das Kreditkartennetzwerk identifizieren zu k nnen.

Fraud Detection in White Collar Crime

Author: Rohan Ahmed
Publisher: GRIN Verlag
ISBN: 3668738343
Format: PDF
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Bachelor Thesis from the year 2017 in the subject Computer Science - Commercial Information Technology, grade: 1.3, Heilbronn University, language: English, abstract: White-collar crime is and has always been an urgent issue for the society. In recent years, white-collar crime has increased dramatically by technological advances. The studies show that companies are affected annually by corruption, balance-sheet manipulation, embezzlement, criminal insolvency and other economic crimes. The companies are usually unable to identify the damage caused by fraudulent activities. To prevent fraud, companies have the opportunity to use intelligent IT approaches. The data analyst or the investigator can use the data which is stored digitally in today’s world to detect fraud. In the age of Big Data, digital information is increasing enormously. Storage is cheap today and no longer a limited medium. The estimates assume that today up to 80 percent of all operational information is stored in the form of unstructured text documents. This bachelor thesis examines Data Mining and Text Mining as intelligent IT approaches for fraud detection in white-collar crime. Text Mining is related to Data Mining. For a differentiation, the source of the information and the structure is important. Text Mining is mainly concerned with weak- or unstructured data, while Data Mining often relies on structured sources. At the beginning of this bachelor thesis, an insight is first given on white-collar crime. For this purpose, the three essential tasks of a fraud management are discussed. Based on the fraud triangle of Cressey it is showed which conditions need to come together so that an offender commits a fraudulent act. Following, some well-known types of white-collar crime are considered in more detail. Text Mining approach was used to demonstrate how to extract potentially useful knowledge from unstructured text. For this purpose, two self-generated e-mails were converted into struc-tured format. Moreover, a case study will be conducted on fraud detection in credit card da-taset. The dataset contains legitimate and fraudulent transactions. Based on a literature research, Data Mining techniques are selected and then applied on the dataset by using various sampling techniques and hyperparameter optimization with the goal to identify correctly pre-dicted fraudulent transactions. The CRISP-DM reference model was used as a methodical procedure.

Introduction to Law Enforcement

Author: David H. McElreath
Publisher: CRC Press
ISBN: 1466556323
Format: PDF, ePub, Mobi
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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

Machine Learning Forensics for Law Enforcement Security and Intelligence

Author: Jesus Mena
Publisher: CRC Press
ISBN: 143986070X
Format: PDF, Mobi
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Increasingly, crimes and fraud are digital in nature, occurring at breakneck speed and encompassing large volumes of data. To combat this unlawful activity, knowledge about the use of machine learning technology and software is critical. Machine Learning Forensics for Law Enforcement, Security, and Intelligence integrates an assortment of deductive and instructive tools, techniques, and technologies to arm professionals with the tools they need to be prepared and stay ahead of the game. Step-by-step instructions The book is a practical guide on how to conduct forensic investigations using self-organizing clustering map (SOM) neural networks, text extraction, and rule generating software to "interrogate the evidence." This powerful data is indispensable for fraud detection, cybersecurity, competitive counterintelligence, and corporate and litigation investigations. The book also provides step-by-step instructions on how to construct adaptive criminal and fraud detection systems for organizations. Prediction is the key Internet activity, email, and wireless communications can be captured, modeled, and deployed in order to anticipate potential cyber attacks and other types of crimes. The successful prediction of human reactions and server actions by quantifying their behaviors is invaluable for pre-empting criminal activity. This volume assists chief information officers, law enforcement personnel, legal and IT professionals, investigators, and competitive intelligence analysts in the strategic planning needed to recognize the patterns of criminal activities in order to predict when and where crimes and intrusions are likely to take place.

Pattern Recognition and Machine Intelligence

Author: Ashish Ghosh
Publisher: Springer Science & Business Media
ISBN: 3540770453
Format: PDF, ePub, Docs
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institute's motto "Unity in Diversity." As evidence and justi'cation of the int- disciplinary research comprising statistics and computer science, one may note thatstatistics providesone ofthe bestparadigmsfor learning,andit hasbecome an integralpart of the theories/paradigmsof machine learning, e.g., arti'cial - telligence, neural networks, brain mapping, data mining, and search machines on the Internet. Zadeh, the founder of fuzzy set theory, has observed that there are three essential ingredients for dramatic success in computer applications, namely, a fuzzy model of data, Bayesian inference and genetic algorithms for optimization. Similarly, statistical science will be a part, in many ways, of the validation of the tentative model of the human brain, its functions and prop- ties, including consciousness. As a mark of the signi'cant achievements in these activities in ISI, special mention may be made of the DOE-sponsored KBCS Nodal Center of ISI in the 1980s and the Center for Soft Computing Research of ISI recently established in 2004 by the DST, Government of India. The soft computing center is the ?rst national initiative in the country in this domain, and has many imp- tant objectives like providing a six-month value addition certi'cate course for post-graduates, enriching national institutes, e.g., NITs through funding for - search in soft computing, establishing linkage to premier institutes/industries, organizing specialized courses, apart from conducting fundamental research.