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Data Mining and Homeland Security: An Overview
Title: Data Mining and Homeland Security: An Overview
Date: April 3, 2008
Author: Jeffrey W. Seifert
Institution: Congressional Research Reports for the People
Bibliographic Entry: Seifert, Jeffery W. “Data Mining and Homeland Security: An Overview.” April 3, 2008. Congressional Research Reports for the People
http://assets.opencrs.com/rpts/RL31798_20080403.pdf (Accessed July 17, 2008)
Electronic Link: http://assets.opencrs.com/rpts/RL31798_20080403.pdf
Key Words: data mining, fraud
Summary of Key Points, Issues, Conclusions: Data mining has become one of the key features of many homeland security initiatives. It is often used as a means for detecting fraud, assessing risk, and product retailing. In the context of homeland security, data mining can be a potential means to identify terrorist activities, such as money transfers and communications, and to identify and track individual terrorists themselves, such as through travel and immigration records. Limitations exist to data mining’s capabilities. One limitation is that it does not tell the user the significance of patterns and relationships. Another limitation is that while data mining can identify connections between behaviors or variables, it does not identify a causal relationship. To be successful, data mining requires skilled technical and analytical specialists who can structure the analysis and interpret the output. We see data mining in the public sector as a means to measure and improve program performance and also to detect fraud and waste. Private sector industries such as banks, insurance companies, and medical facilities have utilized data mining to progress research, escalate sales, and lower costs. Four issues that should be taken into consideration when applying data mining are privacy, interoperability of the data mining software, alternate and unauthorized use of the data, and the accuracy of the data being analyzed. With the evolution of data mining efforts, it is expected that congressional supervision of data mining projects will continue to grow.
Name of Researcher: Ashanti Z. Corey
Institution: Integrative Center for Homeland Security, Texas A&M University
Date Posted: July 18, 2008