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COPLINK Center: Social Network Analysis and Identity Deception Detection for Law Enforcement and Homeland Security      (Back to Search Results)

Grant Number: 429364

  • Description: Continuing grant
  • Associated Project:
  • Award Date:
  • Award Period: 2004-10-01 to 2005-09-30
  • Amount: $ 194632.00

Primary Investigator:
Hsinchun Chen

Hsinchun Chen


Government Domain:

Primary Institution:
U of Arizona

Project Home Page:

Latest Project Highlight:

To deter any future terrorist attacks, law enforcement and intelligence agencies are making every effort to enhance national security. It becomes the top priority to develop and implement advanced technologies for information gathering, sharing, and analysis in all levels of law enforcement and intelligence agencies. Criminal information is the central element in all types of crime data. However, we find ourselves lacking techniques to both identifying a criminal's identity effectively and to recognizing relationships among criminals promptly. The motivation of this research is to address these criminal identity management challenges by developing a comprehensive framework for applying data mining, deception detection, and social network analysis to help identify criminal identities and relationships among criminals. These technologies will be evaluated with real users and law enforcement organizations; related technology adoption and policy issues will also be examined. The primary intellectual merit of this research is four-fold: (a) developing new data mining and knowledge discovery models and techniques that are appropriate for law enforcement applications but can also be applied in other domains demonstrating similar characteristics, (b) developing a theoretic basis for the formation and the representation of criminal identity deception, (c) developing a framework for automated criminal network generation and analysis, and (d) studying the acceptance and adoption of the developed technologies in real-world settings. The broader impacts of this research include: reducing cognitive and information overload in law enforcement applications; improving intelligence and law enforcement agencies' abilities to detect, prevent, and respond to crimes and terrorism events; and providing techniques that foster information sharing and collaboration among law enforcement and intelligence agencies. Several partnerships with law enforcement agencies will ensure impact.