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A Bayesian network methodology for optimal security management of critical infrastructures. / Misuri, Alessio; Khakzad, Nima; Reniers, Genserik; Cozzani, Valerio.

In: Reliability Engineering and System Safety, Vol. 191, 106112, 2019.

Research output: Contribution to journalArticleScientificpeer-review

Harvard

Misuri, A, Khakzad, N, Reniers, G & Cozzani, V 2019, 'A Bayesian network methodology for optimal security management of critical infrastructures' Reliability Engineering and System Safety, vol. 191, 106112. https://doi.org/10.1016/j.ress.2018.03.028

APA

Misuri, A., Khakzad, N., Reniers, G., & Cozzani, V. (2019). A Bayesian network methodology for optimal security management of critical infrastructures. Reliability Engineering and System Safety, 191, [106112]. https://doi.org/10.1016/j.ress.2018.03.028

Vancouver

Author

Misuri, Alessio ; Khakzad, Nima ; Reniers, Genserik ; Cozzani, Valerio. / A Bayesian network methodology for optimal security management of critical infrastructures. In: Reliability Engineering and System Safety. 2019 ; Vol. 191.

BibTeX

@article{b56dbc8b2adb43d6a5da8b26ca60fefc,
title = "A Bayesian network methodology for optimal security management of critical infrastructures",
abstract = "Security management of critical infrastructures is a complex task as a great variety of technical and socio-political information is needed to realistically predict the risk of intentional malevolent acts. In the present study, a methodology based on Limited Memory Influence Diagram (LIMID) has been developed for the protection of critical infrastructures via cost-effective allocation of security measures. LIMID is an extension of Bayesian network (BN) intended for decision-making, allowing for efficient modelling of complex systems while accounting for interdependencies and interaction of system components. The probability updating feature of BN has been used to investigate the effect of vulnerabilities on adversaries’ preferences when planning attacks. Moreover, the proposed methodology has been shown to be able to identify an optimal defensive strategy given an attack through maximizing defenders’ expected utility. Despite being demonstrated via a chemical facility, the methodology can easily be tailored to a wide variety of critical infrastructures.",
keywords = "Cost-effectiveness analysis, Critical infrastructures, Decision support systems, Limited memory influence diagram, Security management",
author = "Alessio Misuri and Nima Khakzad and Genserik Reniers and Valerio Cozzani",
year = "2019",
doi = "10.1016/j.ress.2018.03.028",
language = "English",
volume = "191",
journal = "Reliability Engineering & System Safety",
issn = "0951-8320",
publisher = "Elsevier",

}

RIS

TY - JOUR

T1 - A Bayesian network methodology for optimal security management of critical infrastructures

AU - Misuri, Alessio

AU - Khakzad, Nima

AU - Reniers, Genserik

AU - Cozzani, Valerio

PY - 2019

Y1 - 2019

N2 - Security management of critical infrastructures is a complex task as a great variety of technical and socio-political information is needed to realistically predict the risk of intentional malevolent acts. In the present study, a methodology based on Limited Memory Influence Diagram (LIMID) has been developed for the protection of critical infrastructures via cost-effective allocation of security measures. LIMID is an extension of Bayesian network (BN) intended for decision-making, allowing for efficient modelling of complex systems while accounting for interdependencies and interaction of system components. The probability updating feature of BN has been used to investigate the effect of vulnerabilities on adversaries’ preferences when planning attacks. Moreover, the proposed methodology has been shown to be able to identify an optimal defensive strategy given an attack through maximizing defenders’ expected utility. Despite being demonstrated via a chemical facility, the methodology can easily be tailored to a wide variety of critical infrastructures.

AB - Security management of critical infrastructures is a complex task as a great variety of technical and socio-political information is needed to realistically predict the risk of intentional malevolent acts. In the present study, a methodology based on Limited Memory Influence Diagram (LIMID) has been developed for the protection of critical infrastructures via cost-effective allocation of security measures. LIMID is an extension of Bayesian network (BN) intended for decision-making, allowing for efficient modelling of complex systems while accounting for interdependencies and interaction of system components. The probability updating feature of BN has been used to investigate the effect of vulnerabilities on adversaries’ preferences when planning attacks. Moreover, the proposed methodology has been shown to be able to identify an optimal defensive strategy given an attack through maximizing defenders’ expected utility. Despite being demonstrated via a chemical facility, the methodology can easily be tailored to a wide variety of critical infrastructures.

KW - Cost-effectiveness analysis

KW - Critical infrastructures

KW - Decision support systems

KW - Limited memory influence diagram

KW - Security management

UR - http://www.scopus.com/inward/record.url?scp=85054054002&partnerID=8YFLogxK

U2 - 10.1016/j.ress.2018.03.028

DO - 10.1016/j.ress.2018.03.028

M3 - Article

VL - 191

JO - Reliability Engineering & System Safety

T2 - Reliability Engineering & System Safety

JF - Reliability Engineering & System Safety

SN - 0951-8320

M1 - 106112

ER -

ID: 57396707