Cross-jurisdictional activity networks to support criminal investigations

  • Authors:
  • Byron Marshall;Siddharth Kaza;Jennifer Xu;Homa Atabakhsh;Tim Petersen;Chuck Violette;Hsinchun Chen

  • Affiliations:
  • University of Arizona;University of Arizona;University of Arizona;University of Arizona;University of Arizona;University of Arizona;University of Arizona

  • Venue:
  • dg.o '04 Proceedings of the 2004 annual national conference on Digital government research
  • Year:
  • 2004

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Abstract

Border and transportation security is a critical part of the Department of Homeland Security's (DHS) national strategy. DHS strategy calls for the creation of "smart borders" where information from local, state, federal, and international sources can be combined to support risk-based management tools for border-management agencies. Sharing cross-jurisdictional law enforcement data is important because criminals take advantage of the fact that information sharing between law enforcement jurisdictions is very limited. Challenges to information integration in this important domain include policy and privacy concerns, data security requirements, semantic or schema-level matching of legacy system data, and identity matching. The BorderSafe project leverages the skills and experiences of a diverse group of researchers, law enforcement officials, and government agencies to address data sharing needs in the Southwest United States. Our demo presents a framework for combining law enforcement data across jurisdictions to support criminal investigation and describes how that framework was used in combining three large, overlapping datasets to produce an integrated system for visualizing criminal activity networks.