COPLINK center: social network analysis and identity deception detection for law enforcement and homeland security intelligence and security informatics: a crime data mining approach to developing border safe research

ABSTRACT

In this paper, we describe the highlights of the COPLINK Center for law enforcement and homeland security project. Two new components of the project are described, namely, identity resolution and mutual information.

REFERENCES

• 1: Hsinchun Chen , Daniel Zeng , Homa Atabakhsh , Wojciech Wyzga , Jenny Schroeder, COPLINK: managing law enforcement data and knowledge, Communications of the ACM, v.46 n.1, January 2003 [doi>10.1145/602421.602441]
• 2: G. Wang, "A Multi-Layer Graphical Model for Approximate Identity Matching," In Proceedings of the AIS Americas Conference on Information Systems (AMCIS 2005), Omaha, NE, USA, August 11--14, 2005.
• 3: Kaza, S., Wang, T., Gowda, H. and Chen, H. Target Vehicle Identification using Mutual Information. In Proceedings of the 8th International IEEE Conference on Intelligent Transportation Systems, Vienna, Austria, 2005.

INDEX TERMS

Primary Classification:
  H. Information Systems
  H.2 DATABASE MANAGEMENT
      H.2.8 Database applications
          Subjects: Data mining

Additional Classification:
  G. Mathematics of Computing
  G.3 PROBABILITY AND STATISTICS
      Subjects: Probabilistic algorithms (including Monte Carlo)

General Terms:
Algorithms, Security

Keywords:
border safety, data mining, homeland security, identity matching, intelligence and security informatics, law enforcement, mutual information, naïve bayes model, semi-supervised learning