Data Mining in Homeland Security
DATA MINING IN HOMELAND SECURITY Abstract
Data Mining is an analytical process that primarily involves searching through vast amounts of data to spot useful, but initially undiscovered, patterns. The data mining process typically involves three major stepsexploration, model building and validation and finally, deployment.
Data mining is used in numerous applications, particularly business related endeavors such as market segmentation, customer churn, fraud detection, direct marketing, interactive marketing, market basket analysis and trend analysis. However, since the 1993 World Trade Center bombing and the terrorist attacks of September 11, data mining has increasingly been used in homeland security efforts.
Two of the earlier homeland security programs were the Total Information Awareness Program (TIA) and the Computer-Assisted Passenger Prescreening System (CAPPS II). Privacy and other concerns led to the eventual demise of these programs.
In addition to efforts by the federal government, state programs are also being implemented. The Texas Fusion Center is a prime example of state agencies data mining data in efforts to thwart attacks against our populace.
Data mining is not difficult to implement, as an example of detecting potential subversives using Amazon.com wishlists is presented.
The primary negatives of data mining are concerns related to privacy. False positives whereby individuals are wrongly identified as "terrorists" and inadequate government control over data are prime examples.
In conclusion, data mining can be enormously beneficial in homeland security efforts, however, until privacy and other concerns are adequately addressed, it will be difficult for the government to get approval from its citizens for many programs.
Introduction
This technical paper is intended to introduce to the reader to the analytical process known as data mining and its growing application in homeland security endeavors. In doing so,
Data Mining is an analytical process that primarily involves searching through vast amounts of data to spot useful, but initially undiscovered, patterns. The data mining process typically involves three major stepsexploration, model building and validation and finally, deployment.
Data mining is used in numerous applications, particularly business related endeavors such as market segmentation, customer churn, fraud detection, direct marketing, interactive marketing, market basket analysis and trend analysis. However, since the 1993 World Trade Center bombing and the terrorist attacks of September 11, data mining has increasingly been used in homeland security efforts.
Two of the earlier homeland security programs were the Total Information Awareness Program (TIA) and the Computer-Assisted Passenger Prescreening System (CAPPS II). Privacy and other concerns led to the eventual demise of these programs.
In addition to efforts by the federal government, state programs are also being implemented. The Texas Fusion Center is a prime example of state agencies data mining data in efforts to thwart attacks against our populace.
Data mining is not difficult to implement, as an example of detecting potential subversives using Amazon.com wishlists is presented.
The primary negatives of data mining are concerns related to privacy. False positives whereby individuals are wrongly identified as "terrorists" and inadequate government control over data are prime examples.
In conclusion, data mining can be enormously beneficial in homeland security efforts, however, until privacy and other concerns are adequately addressed, it will be difficult for the government to get approval from its citizens for many programs.
Introduction
This technical paper is intended to introduce to the reader to the analytical process known as data mining and its growing application in homeland security endeavors. In doing so,
References: http://www.eco.utexas.edu/~norman/BUS.FOR/course.mat/Alex/ Data Mining Techniques (2003) http://www.statsoft.com/textbook/stdatmin.html Dempsey, James & Rosenzweig, Paul (May 26, 2004) http://www.heritage.org/Research/HomelandDefense/loader.cfm?url=/commonspot/security/getfile.cfm&PageID=63976 DeRosa, Mary (2004) http://www.cdt.org/security/usapatriot/20040300csis.pdf Mittelstadt, Michelle (November 1, 2005) http://www.kvue.com/news/state/stories/110105cccakvuehomeland.1c6e2abc.html Owad, Tom (January 4, 2006) http://www.fas.org/sgp/crs/intel/RL31798.pdf Sternstein, Aliya (August 29, 2005)