Investigative Data Mining For Security And Criminal Detection / Edition 1

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Overview

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

Audience: Government data analysts, law enforcement, investigators, counter-intelligence agents, IT security professionals, fraud specialists in government and private industry.

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Editorial Reviews

From the Publisher
“This work is one of the first books to show security professionals the power of data mining as an investigative tool. It is itself a powerful tool for the industry.”
— Security Management

“…an eye-opening and powerful book on the newest weapons in criminal and terrorist detection and deterrence.”
— The Chicago Sun

“More detail-minded and technical readers will enjoy the challenging complexity found in follow-up case studies.”
— The Chicago Sun

“The book is cleanly presented and includes screenshots of software used for data mining and analysis ... Charts are used to explain how pieces of information link together in a descriptive manner ...”
— Security Forums

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Product Details

  • ISBN-13: 9780750676137
  • Publisher: Elsevier Science
  • Publication date: 12/1/2002
  • Edition description: New Edition
  • Edition number: 1
  • Pages: 470
  • Product dimensions: 0.95 (w) x 7.00 (h) x 10.00 (d)

Meet the Author

Jesứs Mena is a data mining consultant and a former artificial intelligence specialist for the Internal Revenue Service (IRS) in the U.S. He has over 15 years experience in the field and is author of the best-selling Data Mining Your Website and WebMining for Profit. His articles have been widely published in key publications in the information technology, Internet, marketing, and artificial intelligence fields. He can be contacted at mail@jesusmena.com.

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Table of Contents

1) Pre-Crime Data Mining
2) Investigative Data Warehousing
3) Link Analysis: Visualizing Associations
4) Intelligent Agents: Software Detectives
5) Text Mining: Clustering Concepts
6) Neural Networks: Classifying Patterns
7) Machine Learning: Developing Profiles
8) NetFraud: A Case Study
9) Criminal Patterns: Detection Techniques
10) Intrusion Detection: Techniques and Systems
11) An Entity Validation System (EVS): A Conceptual Architecture
12) Mapping Crime: Clustering CaseWork
Appendix A: 1,000 Online Sources for the Forensic Data Miner
Appendix B: Intrusion Detection Systems (IDS) Products, Services, Freeware and Projects
Glossary

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