Take a look at the new version of this page: [ beta version ]. Tell us what you think.

ABSTRACT

Combating identity fraud is prominent and urgent since false identity has become the common denominator of all serious crime. Among many identified identity attributes, personal names are commonly falsified or aliased by most criminals and terrorists. Typical approaches to such name disambiguation rely on the text-based similarity measures, which are efficient to some extent, but severely fail to handle highly deceptive and unknown identities. In light of aforementioned shortcoming, this paper presents an intelligent hybrid approach that proficiently combines both content-based and link-based measures of examined names to refine the justification of their similarity. In particular, a new link-based method that exploits multiple link properties is introduced and deployed within the proposed hybrid mechanism. The experimental evaluation of this measure and the hybrid model against other link-based and text-based techniques, over a terrorist-related dataset, significantly indicates their great potentials towards an effective verification system.

REFERENCES

• 1: R. Angheluta and M-F. Moens. Cross-document entity tracking. In European Conference on IR Research, pages 670--673, 2007.
• 2: A. Badia and M. M. Kantardzic. Link analysis tools for intelligence and counterterrorism. In Proceedings of IEEE International Conference on Intelligence and Security Informatics, Atlanta, pages 49--59, 2005.
• 3: Mikhail Bilenko , Raymond J. Mooney, Adaptive duplicate detection using learnable string similarity measures, Proceedings of the ninth ACM SIGKDD international conference on Knowledge discovery and data mining, August 24-27, 2003, Washington, D.C. [doi>10.1145/956750.956759]
• 4: T. Boongoen and Q. Shen. Detecting false identity through behavioural patterns. In Proceedings of Int. Crime Science Conference, London, 2008.
• 5: L. Karl Branting, A comparative evaluation of name-matching algorithms, Proceedings of the 9th international conference on Artificial intelligence and law, June 24-28, 2003, Scotland, United Kingdom [doi>10.1145/1047788.1047837]
• 6: Sergey Brin , Lawrence Page, The anatomy of a large-scale hypertextual Web search engine, Computer Networks and ISDN Systems, v.30 n.1-7, p.107-117, April 1, 1998
• 7: Pável Calado , Marco Cristo , Marcos André Gonçalves , Edleno S. de Moura , Berthier Ribeiro-Neto , Nivio Ziviani, Link-based similarity measures for the classification of Web documents, Journal of the American Society for Information Science and Technology, v.57 n.2, p.208-221, January 2006 [doi>10.1002/asi.v57:2]
• 8: R. Clarke. Human identification in information systems: Management challenges and public policy issues. IT and People, 7(4): 6--37, 1994.
• 9: Francois Fouss , Alain Pirotte , Jean-Michel Renders , Marco Saerens, Random-Walk Computation of Similarities between Nodes of a Graph with Application to Collaborative Recommendation, IEEE Transactions on Knowledge and Data Engineering, v.19 n.3, p.355-369, March 2007 [doi>10.1109/TKDE.2007.46]
• 10: Lise Getoor , Christopher P. Diehl, Link mining: a survey, ACM SIGKDD Explorations Newsletter, v.7 n.2, p.3-12, December 2005 [doi>10.1145/1117454.1117456]
• 11: Jingyu Hou , Yanchun Zhang, Effectively Finding Relevant Web Pages from Linkage Information, IEEE Transactions on Knowledge and Data Engineering, v.15 n.4, p.940-951, July 2003 [doi>10.1109/TKDE.2003.1209010]
• 12: P. Hsiung, A. Moore, D. Neill, and J. Schneider. Alias detection in link data sets. In Proceedings of International Conference on Intelligence Analysis, 2005.
• 13: M. A. Jaro. Probabilistic linkage of large public health data files. Statistics in Medicine, 14(5--7): 491--498, 1995.
• 14: Glen Jeh , Jennifer Widom, SimRank: a measure of structural-context similarity, Proceedings of the eighth ACM SIGKDD international conference on Knowledge discovery and data mining, July 23-26, 2002, Edmonton, Alberta, Canada [doi>10.1145/775047.775126]
• 15: Dmitri V. Kalashnikov , Sharad Mehrotra, Domain-independent data cleaning via analysis of entity-relationship graph, ACM Transactions on Database Systems (TODS), v.31 n.2, p.716-767, June 2006 [doi>10.1145/1138394.1138401]
• 16: S. Klink, P. Reuther, A. Weber, B. Walter, and M. Ley. Analysing social networks within bibliographical data. In Proceedings of International Conference on Database and Expert Systems Applications, Poland, pages 234--243, 2006.
• 17: David Liben-Nowell , Jon Kleinberg, The link-prediction problem for social networks, Journal of the American Society for Information Science and Technology, v.58 n.7, p.1019-1031, May 2007 [doi>10.1002/asi.v58:7]
• 18: Zhenjiang Lin , Irwin King , Michael R. Lyu, PageSim: A Novel Link-Based Similarity Measure for the World Wide Web, Proceedings of the 2006 IEEE/WIC/ACM International Conference on Web Intelligence, p.687-693, December 18-22, 2006 [doi>10.1109/WI.2006.127]
• 19: Einat Minkov , William W. Cohen , Andrew Y. Ng, Contextual search and name disambiguation in email using graphs, Proceedings of the 29th annual international ACM SIGIR conference on Research and development in information retrieval, August 06-11, 2006, Seattle, Washington, USA [doi>10.1145/1148170.1148179]
• 20: Gonzalo Navarro, A guided tour to approximate string matching, ACM Computing Surveys (CSUR), v.33 n.1, p.31-88, March 2001 [doi>10.1145/375360.375365]
• 21: G. C. Oatley , J. Zeleznikow , B. W. Ewart, Criminal networks and spatial density, Proceedings of the 10th international conference on Artificial intelligence and law, June 06-11, 2005, Bologna, Italy [doi>10.1145/1165485.1165531]
• 22: P. Pantel. Alias detection in malicious environments. In Proceedings of AAAI Fall Symposium on Capturing and Using Patterns for Evidence Detection, Washington, D.C., pages 14--20, 2006.
• 23: G. Porter. Crying (iranian) wolf in argentina. Asia Times Online (www.atimes.com), Jan 25, 2008.
• 24: Q. Shen, J. Keppens, C. Aitken, B. Schafer, and M. Lee. A scenario-driven decision support system for serious crime investigation. Law, Probability and Risk, 5(2): 87--117, 2006.
• 25: H. Small. Co-citation in the scientific literature: A new measure of the relationship between two documents. Journal of the American Society for Information Science, 24: 265--269, 1973.
• 26: Jimeng Sun , Huiming Qu , Deepayan Chakrabarti , Christos Faloutsos, Relevance search and anomaly detection in bipartite graphs, ACM SIGKDD Explorations Newsletter, v.7 n.2, p.48-55, December 2005 [doi>10.1145/1117454.1117461]
• 27: Hanghang Tong , Christos Faloutsos , Jia-Yu Pan, Fast Random Walk with Restart and Its Applications, Proceedings of the Sixth International Conference on Data Mining, p.613-622, December 18-22, 2006 [doi>10.1109/ICDM.2006.70]
• 28: Vetle I. Torvik , Marc Weeber , Don R. Swanson , Neil R. Smalheiser, A probabilistic similarity metric for Medline records: A model for author name disambiguation: Research Articles, Journal of the American Society for Information Science and Technology, v.56 n.2, p.140-158, January 2005 [doi>10.1002/asi.v56:2]
• 29: A. G. Wang, H. Atabakhsh, T. Petersen, and H. Chen. Discovering identity problems: A case study. In Proceedings of IEEE International Conference on Intelligence and Security Informatics, Atlanta, pages 368--373, 2005.
• 30: G. A. Wang, H. Chen, J. J. Xu, and H. Atabakhsh. Automatically detecting criminal identity deception: an adaptive detection algorithm. IEEE Transactions on Systems, Man and Cybernetics, Part A, 36(5): 988--999, 2006.
• 31: Paul Zhang , Lavanya Koppaka, Semantics-based legal citation network, Proceedings of the 11th international conference on Artificial intelligence and law, June 04-08, 2007, Stanford, California [doi>10.1145/1276318.1276342]

INDEX TERMS

Primary Classification:
  J. Computer Applications
  J.m MISCELLANEOUS

Additional Classification:
  I. Computing Methodologies
  I.5 PATTERN RECOGNITION
      I.5.4 Applications
          Subjects: Text processing

  K. Computing Milieux
  K.4 COMPUTERS AND SOCIETY
      K.4.1 Public Policy Issues
          Subjects: Abuse and crime involving computers

General Terms:
Algorithms, Security

Keywords:
false identity detection, hybrid algorithm, link analysis, terrorist data