Pattern recognition projects

There was another indication of a growing federal government interest in technologies for recognizing terror threat-related patterns and relationships in open information sources (such as newspapers, magazines, journals, and public records).

Earlier this month, this blog featured a post on a newly released Intelligence Analysis solutions package from LexisNexis. One of its components ("Open Source Analysis") was designed to help understand national security threats by identifying operational signatures within disparate, multi-sourced data sets.

Last month, the Homeland Security Department awarded a $3 million grant to a consortium of industry and academic research labs led by Rutgers University's Center for Discrete Mathematics and Theoretical Computer Science (DIMACS). As stated in the press release,

"This group will develop computing technologies that find patterns and relationships in data, such as news stories, open-source web logs, and other accessible information, to quickly identify emerging indicators of possible terrorist activity, and rate the consistency and reliability of the sources. Such information could give officials more lead time to investigate and potentially thwart terrorist plans."

Dr. Fred C. Roberts, director of the DIMACS, noted that two key challenges involved in this project are
(1)The massive amount of information to be processed, and
(2)The speed at which both this information and its sources change.

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