INFORMATION UNCERTAINTY TO COMPARE QUALITATIVE REASONING SECURITY RISK ASSESSMENT RESULTS

Gregory M. Chavez, Brian P. Key, David K. Zerkle, Daniel W. Shevitz

Abstract

The security risk associated with malevolent acts such as those of terrorism are often void of the historical data required for a traditional PRA. Most information available to conduct security risk assessments for these malevolent acts is obtained from subject matter experts as subjective judgements. Qualitative reasoning approaches such as approximate reasoning and evidential reasoning are useful for modeling the predicted risk from information provided by subject matter experts. Absent from these approaches is a consistent means to compare the security risk assessment results. This paper explores using entropy measures to quantify the information uncertainty associated with conflict and non-specificity in the predicted reasoning results. Extensions of previous entropy measures are presented here to quantify the non-specificity and conflict associated with security risk assessment results obtained from qualitative reasoning models.

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Paper Citation


in Harvard Style

M. Chavez G., P. Key B., K. Zerkle D. and W. Shevitz D. (2010). INFORMATION UNCERTAINTY TO COMPARE QUALITATIVE REASONING SECURITY RISK ASSESSMENT RESULTS . In Proceedings of the 2nd International Conference on Agents and Artificial Intelligence - Volume 1: ICAART, ISBN 978-989-674-021-4, pages 398-405. DOI: 10.5220/0002748103980405


in Bibtex Style

@conference{icaart10,
author={Gregory M. Chavez and Brian P. Key and David K. Zerkle and Daniel W. Shevitz},
title={INFORMATION UNCERTAINTY TO COMPARE QUALITATIVE REASONING SECURITY RISK ASSESSMENT RESULTS},
booktitle={Proceedings of the 2nd International Conference on Agents and Artificial Intelligence - Volume 1: ICAART,},
year={2010},
pages={398-405},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0002748103980405},
isbn={978-989-674-021-4},
}


in EndNote Style

TY - CONF
JO - Proceedings of the 2nd International Conference on Agents and Artificial Intelligence - Volume 1: ICAART,
TI - INFORMATION UNCERTAINTY TO COMPARE QUALITATIVE REASONING SECURITY RISK ASSESSMENT RESULTS
SN - 978-989-674-021-4
AU - M. Chavez G.
AU - P. Key B.
AU - K. Zerkle D.
AU - W. Shevitz D.
PY - 2010
SP - 398
EP - 405
DO - 10.5220/0002748103980405