University of North Texas Digital Library (University of North Texas) · 2004 · 97 citations · 0 references
Open access
ComputingCybersecurityData ScienceData AnalyticsData ManagementData MiningData PreprocessingFrequent Pattern MiningPattern EvaluationAssociation Rule MiningCyber TerrorismData DiscoveryPrivacy-preserving Data Mining
Data mining, a key component of homeland security initiatives, uses data analysis tools to uncover unknown patterns and relationships in large datasets for fraud detection, risk assessment, and retailing. The report examines data mining applications in the Terrorism Information Awareness program, addresses issues such as data quality, interoperability, and privacy, and outlines its limitations.
Data mining is emerging as one of the key features of many homeland security initiatives. Often used as a means for detecting fraud, assessing risk, and product retailing, data mining involves the use of data analysis tools to discover previously unknown, valid patterns and relationships in large data sets. This report discusses the data mining uses (i.e. Terrorism Information Awareness (TIA) Program) and issues (i.e. data quality, interoperability, privacy), as well as the limitations of data mining.