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International Conference on Intelligence and Security Informatics

ISI 2005: Intelligence and Security Informatics pp 561–566Cite as

Forecasting Terrorism: Indicators and Proven Analytic Techniques

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

Abstract

This forecasting methodology identifies 68 indicators of terrorism and employs proven analytic techniques in a systematic process that safeguards against 36 of the 42 common warning pitfalls that experts have identified throughout history. The complete version of this research provides: 1) a step-by-step explanation of how to forecast terrorism, 2) an evaluation of the forecasting system against the 42 common warning pitfalls that have caused warning failures in the past, and 3) recommendations for implementation. The associated CD has the website interface to this methodology to forecast terrorist attacks. This methodology could be applied to any intelligence topic (not just terrorism) by simply changing the list of indicators. The complete version of this research is available in Forecasting Terrorism: Indicators and Proven Analytic Techniques, Scarecrow Press, Inc., ISBN 0-8108-5017-6.

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References

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Author information

Authors and Affiliations

  1.  , PO BOX 5124, Alameda, CA, 94501

    Sundri K. Khalsa

Authors
  1. Sundri K. Khalsa
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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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Cite this paper

Khalsa, S.K. (2005). Forecasting Terrorism: Indicators and Proven Analytic Techniques. 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_59

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  • DOI: https://doi.org/10.1007/11427995_59

  • 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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