Investigative Data Mining for Security and Criminal Detection

Jesus Mena

Elsevier, Apr 7, 2003 - Computers - 272 pages

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

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Contents

• Chapter 1 Precrime Data Mining: 1
• Chapter 2 Investigative Data Warehousing: 39
• Visualizing Associations: 75
• Software Detectives: 107
• Clustering Concepts: 125
• Classifying Patterns: 159
• Developing Profiles: 205
• A Case Study: 249
• Detection Techniques: 275
• Techniques and Systems: 301
• A Conceptual Architecture: 327
• Clustering Case Work: 343
• 1000 Online Sources for the Investigative Data Miner: 379
• Intrusion Detection Systems IDS Products Services Freeware and Projects: 415
• Intrusion Detection Glossary: 419
• Investigative Data Mining Products and Services: 431
• Index: 435

About 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 [e-mail].

Bibliographic information

• Title: Investigative Data Mining for Security and Criminal Detection
• Author: Jesus Mena
• Publisher: Elsevier, 2003
• ISBN: 008050938X, 9780080509389
• Length: 272 pages
• Subjects: Computers / Databases / General; Computers / Intelligence (AI) & Semantics; Social Science / Criminology