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Digging in the Details: A Case Study in Network Data Mining

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Intelligence and Security Informatics (ISI 2005)

Part of the book series: Lecture Notes in Computer Science ((LNISA,volume 3495))

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Abstract

Network Data Mining builds network linkages (network models) between myriads of individual data items and utilizes special algorithms that aid visualization of ‘emergent’ patterns and trends in the linkage. It complements conventional and statistically based data mining methods. Statistical approaches typically flag, alert or alarm instances or events that could represent anomalous behavior or irregularities because of a match with pre-defined patterns or rules. They serve as ‘exception detection’ methods where the rules or definitions of what might constitute an exception are able to be known and specified ahead of time. Many problems are suited to this approach. Many problems however, especially those of a more complex nature, are not well suited. The rules or definitions simply cannot be specified; there are no known suspicious transactions. This paper presents a human-centered network data mining methodology. A case study from the area of security illustrates the application of the methodology and corresponding data mining techniques. The paper argues that for many problems, a ‘discovery’ phase in the investigative process based on visualization and human cognition is a logical precedent to, and complement of, more automated ‘exception detection’ phases.

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Author information

Authors and Affiliations

  1. Complex Systems Research Centre, University of Technology Sydney, PO Box 123, Broadway, NSW, 2007, Australia

    John Galloway

  2. Chief Scientist, NetMap Analytics Pty Ltd, 52 Atchison Street, St Leonards, NSW, 2065, Australia

    John Galloway

  3. Faculty of Information Technology, University of Technology Sydney, PO Box 123, Broadway, NSW, 2007, Australia

    Simeon J. Simoff

  4. Electronic Markets Group, Institute for Information and Communication Technologies, University of Technology Sydney, PO Box 123, Broadway, NSW, 2007, Australia

    Simeon J. Simoff

Authors
  1. John Galloway
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  2. Simeon J. Simoff
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Editor information

Editors and Affiliations

  1. Department of Library and Information Science, Rutgers University,  

    Paul Kantor

  2. School of Communication, Information and Library Studies, Rutgers University, 4 Huntington Street, 08901-1071, New Brunswick, NJ, USA

    Gheorghe Muresan

  3. Artificial Solutions, Altonaer Poststraße 13b, 22767, Hamburg, Germany

    Fred Roberts

  4. MIS Department, University of Arizona, 85721, Tucson, AZ, USA

    Daniel D. Zeng

  5. Institute of Automation, Chinese Academy of Sciences, Beijing, China

    Fei-Yue Wang

  6. Department of Management Information Systems, Eller College of Management, The University of Arizona, 85721, AZ, USA

    Hsinchun Chen

  7. College of Computing, Georgia Tech Information Security Center, Georgia Institute of Technology, 801 Atlantic Drive, 30332-0280, Atlanta, GA, USA

    Ralph C. Merkle

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© 2005 Springer-Verlag Berlin Heidelberg

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Galloway, J., Simoff, S.J. (2005). Digging in the Details: A Case Study in Network Data Mining. In: Kantor, P., et al. Intelligence and Security Informatics. ISI 2005. Lecture Notes in Computer Science, vol 3495. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11427995_2

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  • DOI: https://doi.org/10.1007/11427995_2

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-25999-2

  • Online ISBN: 978-3-540-32063-0

  • eBook Packages: Computer ScienceComputer Science (R0)

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