Advertisement

Strategic Deterrence of Terrorist Attacks

  • Marcus Wiens
  • Sascha Meng
  • Frank Schultmann
Conference paper
Part of the Operations Research Proceedings book series (ORP)

Abstract

Protection against terrorist threats has become an integral part of organisational and national security strategies. But research on adversarial risks is still dominated by approaches which focus too much on historical frequencies and which do not sufficiently account for the terrorists motives and the strategic component of the interaction. In this paper we model the classical risk analysis approach using a specific variant of adaptive play and compare it with a direct implementation approach. We find that the latter allows for a more purposeful use of security measures as defenders avoid to get caught in a “hare-tortoise-trap”. We specify the conditions under which the direct implementation outperforms adaptive play in the sense that it lowers the cost of defence at a given rate of deterrence. We analyse the robustness of our results and discuss the implications and requirements for practical application.

Keywords

Attack Rate Direct Implementation Adversarial Risk Average Damage Fictitious Play 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

References

  1. 1.
    Anthony Jr. Cox, L.: Game theory and risk analysis. Risk Anal. 29(8), 1062–1068 (2009b)Google Scholar
  2. 2.
    Anthony Jr. Cox, L.: Improving risk-based decision making for terrorism applications. Risk Anal. 29(3), 336–341 (2009a)Google Scholar
  3. 3.
    Brown, G.W.: Iterative solution of games by fictious play. In: Koopmans, T.C. (ed.) Activity analysis of production and allocation, pp. 374–376. Wiley, New York (1951)Google Scholar
  4. 4.
    Crawford, Vincent P.: Learning behavior and mixed-strategy Nash equilibria. J. Econ. Behav. Organ. 6(1), 69–78 (1985)CrossRefGoogle Scholar
  5. 5.
    Deisler, Paul F.: A perspective: risk analysis as a tool for reducing the risks of terrorism. Risk Anal. 22(3), 405–413 (2002)CrossRefGoogle Scholar
  6. 6.
    Dillon, Robin L., Liebe, Robert M., Bestafka, Thomas: Risk-based decision making for terrorism applications. Risk Anal. 29(3), 321–335 (2009)CrossRefGoogle Scholar
  7. 7.
    Meng, S., Wiens, M., Schultmann, F.: A game theoretic approach to assess adversarial risks. In: Brebbia, C.A. (ed.) Risk Anal. IX. WIT Transactions on Information and Communication Technologies, vol. 47, pp. 141–152. WIT Press, Southampton (2014)CrossRefGoogle Scholar

Copyright information

© Springer International Publishing Switzerland 2016

Authors and Affiliations

  1. 1.KITKarlsruheGermany

Personalised recommendations