Investigative Data Mining for Security and Criminal Detection
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.
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