Table of Contents

investigative data mining for security and criminal detection
Investigative Data Mining for Security and Criminal Detection
by Jesus Mena  ISBN:0750676132
Butterworth Heinemann © 2003 (452 pages)

This text introduces security professionals, intelligence and law enforcement analysts, and criminal investigators to the use of data mining as a new kind of investigative tool, and outlines how data mining technologies can be used to combat crime.

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

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 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.

This 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, crime prevention, and national defense. International case studies throughout the book further illustrate how these technologies can be used to aid in crime prevention. The book 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:

  • 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

About the Author

Jesús 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 of experience in the field and is the 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.