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Authors: Vaughn H. Standley ; Frank G. Nuño and Jacob W. Sharpe

Affiliation: College of Information and Cyberspace, National Defense University, 300 5th Ave., Washington D.C. and U.S.A.

Keyword(s): Complex Systems, Bayesian Minimization, Deterrence, Likelihood Ratio, Power-law, Log-normal, Log-gamma.

Abstract: Strategic deterrence operates in and on a vast interstate network of rational actors seeking to minimize risk. Risk can be minimized by employing a likelihood ratio test (LRT) derived from Bayes’ Theorem. The LRT is comprised of prior, detection, and false-alarm probabilities. The power-law, known for its applicability to complex systems, has been used to model the distribution of combat fatalities. However, it cannot be used as a Bayesian prior for war when its area is unbounded. Analytics applied to Correlates of War data reveals that combat fatalities follow a log-gamma or log-normal probability distribution depending on a state’s escalation strategy. Results are used to show that nuclear war level fatalities pose increasing risk despite decreasing probability, that LRT-based decisions can minimize attack risk if an upper limit of impending fatalities is indicated by the detection system and commensurate with nominal false-alarm maximum, and that only successful defensive strategi es are stable. (More)

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Paper citation in several formats:
Standley, V.; Nuño, F. and Sharpe, J. (2019). Minimization of Attack Risk with Bayesian Detection Criteria. In Proceedings of the 4th International Conference on Complexity, Future Information Systems and Risk - COMPLEXIS; ISBN 978-989-758-366-7; ISSN 2184-5034, SciTePress, pages 17-26. DOI: 10.5220/0007656100170026

@conference{complexis19,
author={Vaughn H. Standley. and Frank G. Nuño. and Jacob W. Sharpe.},
title={Minimization of Attack Risk with Bayesian Detection Criteria},
booktitle={Proceedings of the 4th International Conference on Complexity, Future Information Systems and Risk - COMPLEXIS},
year={2019},
pages={17-26},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0007656100170026},
isbn={978-989-758-366-7},
issn={2184-5034},
}

TY - CONF

JO - Proceedings of the 4th International Conference on Complexity, Future Information Systems and Risk - COMPLEXIS
TI - Minimization of Attack Risk with Bayesian Detection Criteria
SN - 978-989-758-366-7
IS - 2184-5034
AU - Standley, V.
AU - Nuño, F.
AU - Sharpe, J.
PY - 2019
SP - 17
EP - 26
DO - 10.5220/0007656100170026
PB - SciTePress