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.
* 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
Chapter 2 Investigative Data Warehousing
A Case Study
Techniques and Systems
A Conceptual Architecture
Clustering Case Work
1000 Online Sources for the Investigative Data Miner
Intrusion Detection Systems IDS Products Services Freeware and Projects
Intrusion Detection Glossary
Investigative Data Mining Products and Services
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Acxiom agents alerts analyze applications associated attack automated behavior classified clusters credit-card crimes CRISP-DM data mining data mining techniques data set database of unclaimed decision tree developed documents e-mail encoding entities example extract Figure files Florida forensic fraud detection fraudulent government information identify IDSs individuals information and links information and services Integrator intelligence Internet Intrusion Detection Intrusion Detection System law enforcement License Database link analysis machine-learning algorithms money laundering monitoring multiple neural network Online searchable database patterns perpetrators police predictive Property Records Public Record Links Public records information reports retrieval rules samples Searchable by name self-organizing map servers Sex Offenders software piracy SPSS statistical Teradata terrorist text mining Text Mining Software tion transactions Unclaimed Property Database unclaimed property listings variables visualization Web bugs Web services West Midlands Police