Data Mining and Homeland Security: An Overview
Abstract
Data mining has become one of the key features of many homeland security initiatives. Often used to detect fraud and assess risk, data mining involves the use of data analysis tools to discover previously unknown, valid patterns and relationships in large data sets. 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. While data mining represents a significant advance in the type of analytical tools currently available, there are limitations to its capability. One limitation is that although data mining can help reveal patterns and relationships, it does not tell the user the value or significance of these patterns. These types of determinations must be made by the user. A second limitation is that while data mining can identify connections between behaviors and/or variables, it does not necessarily identify a causal relationship. Successful data mining still requires skilled technical and analytical specialists who can structure the analysis and interpret the output. Some homeland security data mining initiatives that have attracted congressional interest include the Terrorism Information Awareness (TIA) Program, (now-discontinued); the Computer-Assisted Passenger Prescreening System II (CAPPS II, now canceled and replaced by Secure Flight); the Multi-State Anti-Terrorism Information Exchange (MATRIX) pilot project; the Able Danger program; the Automated Targeting System (ATS); and data collection and analysis projects being conducted by the National Security Agency (NSA). While technological capabilities are important, there are other implementation and oversight issues that can influence the success of a project's outcome: data quality, software interoperability, mission creep, and privacy.
Document Details
- Document Type
- Technical Report
- Publication Date
- Jan 18, 2007
- Accession Number
- ADA468120
Entities
People
- Jeffrey W. Seifert
Organizations
- Library of Congress