Intelligent Data Mining in Law Enforcement Analytics

Intelligent Data Mining in Law Enforcement Analytics PDF

Author: Paolo Massimo Buscema

Publisher: Springer Science & Business Media

Published: 2012-11-28

Total Pages: 522

ISBN-13: 9400749147

DOWNLOAD EBOOK →

This book provides a thorough summary of the means currently available to the investigators of Artificial Intelligence for making criminal behavior (both individual and collective) foreseeable, and for assisting their investigative capacities. The volume provides chapters on the introduction of artificial intelligence and machine learning suitable for an upper level undergraduate with exposure to mathematics and some programming skill or a graduate course. It also brings the latest research in Artificial Intelligence to life with its chapters on fascinating applications in the area of law enforcement, though much is also being accomplished in the fields of medicine and bioengineering. Individuals with a background in Artificial Intelligence will find the opening chapters to be an excellent refresher but the greatest excitement will likely be the law enforcement examples, for little has been done in that area. The editors have chosen to shine a bright light on law enforcement analytics utilizing artificial neural network technology to encourage other researchers to become involved in this very important and timely field of study.

Investigative Data Mining for Security and Criminal Detection

Investigative Data Mining for Security and Criminal Detection PDF

Author: Jesus Mena

Publisher: Elsevier

Published: 2003-04-07

Total Pages: 469

ISBN-13: 008050938X

DOWNLOAD EBOOK →

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

Data Mining for Intelligence, Fraud & Criminal Detection

Data Mining for Intelligence, Fraud & Criminal Detection PDF

Author: Christopher Westphal

Publisher: CRC Press

Published: 2008-12-22

Total Pages: 450

ISBN-13: 1420067249

DOWNLOAD EBOOK →

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

Data Mining and Predictive Analysis

Data Mining and Predictive Analysis PDF

Author: Colleen McCue

Publisher: Butterworth-Heinemann

Published: 2014-12-30

Total Pages: 422

ISBN-13: 0128004088

DOWNLOAD EBOOK →

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

Intelligent Data Analytics for Terror Threat Prediction

Intelligent Data Analytics for Terror Threat Prediction PDF

Author: Subhendu Kumar Pani

Publisher: John Wiley & Sons

Published: 2021-01-12

Total Pages: 352

ISBN-13: 1119711517

DOWNLOAD EBOOK →

Intelligent data analytics for terror threat prediction is an emerging field of research at the intersection of information science and computer science, bringing with it a new era of tremendous opportunities and challenges due to plenty of easily available criminal data for further analysis. This book provides innovative insights that will help obtain interventions to undertake emerging dynamic scenarios of criminal activities. Furthermore, it presents emerging issues, challenges and management strategies in public safety and crime control development across various domains. The book will play a vital role in improvising human life to a great extent. Researchers and practitioners working in the fields of data mining, machine learning and artificial intelligence will greatly benefit from this book, which will be a good addition to the state-of-the-art approaches collected for intelligent data analytics. It will also be very beneficial for those who are new to the field and need to quickly become acquainted with the best performing methods. With this book they will be able to compare different approaches and carry forward their research in the most important areas of this field, which has a direct impact on the betterment of human life by maintaining the security of our society. No other book is currently on the market which provides such a good collection of state-of-the-art methods for intelligent data analytics-based models for terror threat prediction, as intelligent data analytics is a newly emerging field and research in data mining and machine learning is still in the early stage of development.

Machine Learning Forensics for Law Enforcement, Security, and Intelligence

Machine Learning Forensics for Law Enforcement, Security, and Intelligence PDF

Author: Jesus Mena

Publisher: CRC Press

Published: 2016-04-19

Total Pages: 349

ISBN-13: 143986070X

DOWNLOAD EBOOK →

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

Protecting Individual Privacy in the Struggle Against Terrorists

Protecting Individual Privacy in the Struggle Against Terrorists PDF

Author: National Research Council

Publisher: National Academies Press

Published: 2008-10-26

Total Pages: 377

ISBN-13: 0309124883

DOWNLOAD EBOOK →

All U.S. agencies with counterterrorism programs that collect or "mine" personal data-such as phone records or Web sites visited-should be required to evaluate the programs' effectiveness, lawfulness, and impacts on privacy. A framework is offered that agencies can use to evaluate such information-based programs, both classified and unclassified. The book urges Congress to re-examine existing privacy law to assess how privacy can be protected in current and future programs and recommends that any individuals harmed by violations of privacy be given a meaningful form of redress. Two specific technologies are examined: data mining and behavioral surveillance. Regarding data mining, the book concludes that although these methods have been useful in the private sector for spotting consumer fraud, they are less helpful for counterterrorism because so little is known about what patterns indicate terrorist activity. Regarding behavioral surveillance in a counterterrorist context, the book concludes that although research and development on certain aspects of this topic are warranted, there is no scientific consensus on whether these techniques are ready for operational use at all in counterterrorism.

URBAN COASTAL AREA CONFLICTS ANALYSIS METHODOLOGY

URBAN COASTAL AREA CONFLICTS ANALYSIS METHODOLOGY PDF

Author: Armando Montanari

Publisher: Sapienza Università Editrice

Published: 2013-12-18

Total Pages: 415

ISBN-13: 8898533012

DOWNLOAD EBOOK →

This volume is the completed section of the process of analytical research and methodological comparisons undertaken by SECOA, a 48-month research project selected and funded by the EU under the FP7 program. Hence, while scientifically autonomous, the volume is a natural link between the different phases of analysis within SECOA, i.e. Work Packages (WPs) 1-5, and the interpretive and predictive values that are being drawn up by WPs 7 and 8. Within the overall scope of SECOA's research activity, this volume's task was to supply answers to questions that will undergo further study by research groups. These groups will subsequently have to create methods and tools to identify the most suitable policies to effectively manage environmental conflicts, use fragile and rare resources more efficiently, and develop administrative structures capable of dealing with the needs of a continuously evolving society (the wisdom stage). It was also deemed necessary to construct possible alternative scenarios in order to contribute to an enhanced vision of sustainable urban development in coastal areas (the understanding stage). The findings of the research discussed in this volume are to be used to understand the relationships between the variables collected in the previous phases (WPs 1, 2, 3 and 4) of SECOA.

The Rise of Big Data Policing

The Rise of Big Data Policing PDF

Author: Andrew Guthrie Ferguson

Publisher: NYU Press

Published: 2019-11-15

Total Pages: 267

ISBN-13: 147986997X

DOWNLOAD EBOOK →

Winner, 2018 Law & Legal Studies PROSE Award The consequences of big data and algorithm-driven policing and its impact on law enforcement In a high-tech command center in downtown Los Angeles, a digital map lights up with 911 calls, television monitors track breaking news stories, surveillance cameras sweep the streets, and rows of networked computers link analysts and police officers to a wealth of law enforcement intelligence. This is just a glimpse into a future where software predicts future crimes, algorithms generate virtual “most-wanted” lists, and databanks collect personal and biometric information. The Rise of Big Data Policing introduces the cutting-edge technology that is changing how the police do their jobs and shows why it is more important than ever that citizens understand the far-reaching consequences of big data surveillance as a law enforcement tool. Andrew Guthrie Ferguson reveals how these new technologies —viewed as race-neutral and objective—have been eagerly adopted by police departments hoping to distance themselves from claims of racial bias and unconstitutional practices. After a series of high-profile police shootings and federal investigations into systemic police misconduct, and in an era of law enforcement budget cutbacks, data-driven policing has been billed as a way to “turn the page” on racial bias. But behind the data are real people, and difficult questions remain about racial discrimination and the potential to distort constitutional protections. In this first book on big data policing, Ferguson offers an examination of how new technologies will alter the who, where, when and how we police. These new technologies also offer data-driven methods to improve police accountability and to remedy the underlying socio-economic risk factors that encourage crime. The Rise of Big Data Policing is a must read for anyone concerned with how technology will revolutionize law enforcement and its potential threat to the security, privacy, and constitutional rights of citizens. Read an excerpt and interview with Andrew Guthrie Ferguson in The Economist.