Intelligent Data Mining In Law Enforcement Analytics
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| Author | : Paolo Massimo Buscema |
| Publisher | : Springer Science & Business Media |
| Total Pages | : 522 |
| Release | : 2012-11-28 |
| Genre | : Social Science |
| ISBN | : 9400749147 |
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.
| Author | : Jesus Mena |
| Publisher | : Butterworth-Heinemann |
| Total Pages | : 476 |
| Release | : 2003 |
| Genre | : Business & Economics |
| ISBN | : 9780750676137 |
| Author | : Andrew Guthrie Ferguson |
| Publisher | : NYU Press |
| Total Pages | : 267 |
| Release | : 2019-11-15 |
| Genre | : Law |
| ISBN | : 147986997X |
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.
| Author | : Subhendu Kumar Pani |
| Publisher | : John Wiley & Sons |
| Total Pages | : 352 |
| Release | : 2021-01-12 |
| Genre | : Computers |
| ISBN | : 1119711517 |
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.
| Author | : Deepak Gupta |
| Publisher | : John Wiley & Sons |
| Total Pages | : 455 |
| Release | : 2020-04-27 |
| Genre | : Technology & Engineering |
| ISBN | : 1119544467 |
This book focuses on methods and tools for intelligent data analysis, aimed at narrowing the increasing gap between data gathering and data comprehension, and emphasis will also be given to solving of problems which result from automated data collection, such as analysis of computer-based patient records, data warehousing tools, intelligent alarming, effective and efficient monitoring, and so on. This book aims to describe the different approaches of Intelligent Data Analysis from a practical point of view: solving common life problems with data analysis tools.
| Author | : National Research Council |
| Publisher | : National Academies Press |
| Total Pages | : 376 |
| Release | : 2008-09-26 |
| Genre | : Computers |
| ISBN | : 0309134447 |
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.
| Author | : Izzat M Alsmadi |
| Publisher | : Springer |
| Total Pages | : 379 |
| Release | : 2016-10-21 |
| Genre | : Technology & Engineering |
| ISBN | : 3319442570 |
This book highlights several gaps that have not been addressed in existing cyber security research. It first discusses the recent attack prediction techniques that utilize one or more aspects of information to create attack prediction models. The second part is dedicated to new trends on information fusion and their applicability to cyber security; in particular, graph data analytics for cyber security, unwanted traffic detection and control based on trust management software defined networks, security in wireless sensor networks & their applications, and emerging trends in security system design using the concept of social behavioral biometric. The book guides the design of new commercialized tools that can be introduced to improve the accuracy of existing attack prediction models. Furthermore, the book advances the use of Knowledge-based Intrusion Detection Systems (IDS) to complement existing IDS technologies. It is aimed towards cyber security researchers.
| Author | : Tamara Rice Lave |
| Publisher | : Cambridge University Press |
| Total Pages | : 615 |
| Release | : 2019-07-04 |
| Genre | : Law |
| ISBN | : 1108420559 |
A comprehensive collection on police and policing, written by experts in political theory, sociology, criminology, economics, law, public health, and critical theory.
| Author | : Petra Perner |
| Publisher | : Springer |
| Total Pages | : 602 |
| Release | : 2006-07-13 |
| Genre | : Computers |
| ISBN | : 3540360379 |
This book constitutes the refereed proceedings of the 6th Industrial Conference on Data Mining, ICDM 2006, held in Leipzig, Germany in July 2006. Presents 45 carefully reviewed and revised full papers organized in topical sections on data mining in medicine, Web mining and logfile analysis, theoretical aspects of data mining, data mining in marketing, mining signals and images, and aspects of data mining, and applications such as intrusion detection, and more.
| Author | : Da Ruan |
| Publisher | : Springer Science & Business Media |
| Total Pages | : 536 |
| Release | : 2005-08-24 |
| Genre | : Mathematics |
| ISBN | : 9783540262565 |
"Intelligent Data Mining – Techniques and Applications" is an organized edited collection of contributed chapters covering basic knowledge for intelligent systems and data mining, applications in economic and management, industrial engineering and other related industrial applications. The main objective of this book is to gather a number of peer-reviewed high quality contributions in the relevant topic areas. The focus is especially on those chapters that provide theoretical/analytical solutions to the problems of real interest in intelligent techniques possibly combined with other traditional tools, for data mining and the corresponding applications to engineers and managers of different industrial sectors. Academic and applied researchers and research students working on data mining can also directly benefit from this book.
