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Percolation Model of insider threats to assess the optimum number of rules

Author

Listed:
  • Jeremy Kepner

    (MIT Lincoln Laboratory)

  • Vijay Gadepally

    (MIT Lincoln Laboratory)

  • Pete Michaleas

    (MIT Lincoln Laboratory)

Abstract

Rules, regulations, and policies are the basis of civilized society and are used to coordinate the activities of individuals who have a variety of goals and purposes. History has taught that over-regulation (too many rules) makes it difficult to compete and under-regulation (too few rules) can lead to crisis. This implies an optimal number of rules that avoids these two extremes. Rules create boundaries that define the latitude at which an individual has to perform their activities. This paper creates a Toy Model of a work environment and examines it with respect to the latitude provided to a normal individual and the latitude provided to an insider threat. Simulations with the Toy Model illustrate four regimes with respect to an insider threat: under-regulated, possibly optimal, tipping point, and over-regulated. These regimes depend upon the number of rules (N) and the minimum latitude (L min) required by a normal individual to carry out their activities. The Toy Model is then mapped onto the standard 1D Percolation Model from theoretical physics, and the same behavior is observed. This allows the Toy Model to be generalized to a wide array of more complex models that have been well studied by the theoretical physics community and also show the same behavior. Finally, by estimating N and L min, it should be possible to determine the regime of any particular environment.

Suggested Citation

  • Jeremy Kepner & Vijay Gadepally & Pete Michaleas, 2015. "Percolation Model of insider threats to assess the optimum number of rules," Environment Systems and Decisions, Springer, vol. 35(4), pages 504-510, December.
    • Handle: RePEc:spr:envsyd:v:35:y:2015:i:4:d:10.1007_s10669-015-9571-4
    DOI: 10.1007/s10669-015-9571-4
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    References listed on IDEAS

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    1. Barro, Robert J, 1986. "Recent Developments in the Theory of Rules versus Discretion," Economic Journal, Royal Economic Society, vol. 96(380a), pages 23-37, Supplemen.
    2. Joshua Aizenman, 2009. "Financial Crisis and the Paradox of Under- and Over-Regulation," NBER Working Papers 15018, National Bureau of Economic Research, Inc.
    3. Caitlin Casey & Kartik Sheth, 2013. "The ethical grey zone," Nature, Nature, vol. 503(7476), pages 427-428, November.
    4. Elizabeth E. Umphress & John B. Bingham, 2011. "When Employees Do Bad Things for Good Reasons: Examining Unethical Pro-Organizational Behaviors," Organization Science, INFORMS, vol. 22(3), pages 621-640, June.
    5. Barry Shore, 1998. "IT Strategy: The Challenge of Over-regulation, Culture, and Large-scale Collaborations," Journal of Global Information Technology Management, Taylor & Francis Journals, vol. 1(1), pages 1-4, January.
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    Cited by:

    1. Z. A. Collier & J. H. Lambert & I. Linkov, 2015. "Application of systems modeling and risk assessment to address real-world decision-making challenges," Environment Systems and Decisions, Springer, vol. 35(4), pages 425-426, December.
    2. Viktoria Gisladottir & Alexander A. Ganin & Jeffrey M. Keisler & Jeremy Kepner & Igor Linkov, 2017. "Resilience of Cyber Systems with Over‐ and Underregulation," Risk Analysis, John Wiley & Sons, vol. 37(9), pages 1644-1651, September.

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