Capturing the uncertainty in adversary attack simulations.

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Description

This work provides a comprehensive uncertainty technique to evaluate uncertainty, resulting in a more realistic evaluation of PI, thereby requiring fewer resources to address scenarios and allowing resources to be used across more scenarios. For a given set of dversary resources, two types of uncertainty are associated with PI for a scenario: (1) aleatory (random) uncertainty for detection probabilities and time delays and (2) epistemic (state of knowledge) uncertainty for the adversary resources applied during an attack. Adversary esources consist of attributes (such as equipment and training) and knowledge about the security system; to date, most evaluations have assumed an ... continued below

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37 p.

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Darby, John L.; Brooks, Traci N. & Berry, Robert Bruce September 1, 2008.

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Description

This work provides a comprehensive uncertainty technique to evaluate uncertainty, resulting in a more realistic evaluation of PI, thereby requiring fewer resources to address scenarios and allowing resources to be used across more scenarios. For a given set of dversary resources, two types of uncertainty are associated with PI for a scenario: (1) aleatory (random) uncertainty for detection probabilities and time delays and (2) epistemic (state of knowledge) uncertainty for the adversary resources applied during an attack. Adversary esources consist of attributes (such as equipment and training) and knowledge about the security system; to date, most evaluations have assumed an adversary with very high resources, adding to the conservatism in the evaluation of PI. The aleatory uncertainty in PI is ddressed by assigning probability distributions to detection probabilities and time delays. A numerical sampling technique is used to evaluate PI, addressing the repeated variable dependence in the equation for PI.

Physical Description

37 p.

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  • Report No.: SAND2008-5730
  • Grant Number: AC04-94AL85000
  • DOI: 10.2172/983673 | External Link
  • Office of Scientific & Technical Information Report Number: 983673
  • Archival Resource Key: ark:/67531/metadc1014316

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Office of Scientific & Technical Information Technical Reports

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  • September 1, 2008

Added to The UNT Digital Library

  • Oct. 14, 2017, 8:36 a.m.

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  • Oct. 19, 2017, 12:46 p.m.

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Darby, John L.; Brooks, Traci N. & Berry, Robert Bruce. Capturing the uncertainty in adversary attack simulations., report, September 1, 2008; United States. (digital.library.unt.edu/ark:/67531/metadc1014316/: accessed September 21, 2018), University of North Texas Libraries, Digital Library, digital.library.unt.edu; crediting UNT Libraries Government Documents Department.