TY - CHAP
T1 - Security management of process plants by a Bayesian network methodology
AU - Misuri, Alessio
AU - Khakzad, Nima
AU - Reniers, Genserik
AU - Cozzani, Valerio
PY - 2018
Y1 - 2018
N2 - Before the tragedy of 9/11, the perception of risk in process plants was mainly focused on accidental events caused by technical failures, human errors or natural events. However, since then, the risk of deliberate actions against process facilities - also known as security risk - has also become a concern. Security risk assessment of engineering systems and infrastructures constitutes a complex task since a significant multitude of technical and socio-political information is needed to reasonably predict the risk of intentional malevolent acts. In the present study, a methodology based on Bayesian network (BN) has been applied to increase the security of critical infrastructures via cost-effective allocation of security measures. Using the probability updating feature of BN, the proposed methodology can be employed to investigate the effect of vulnerabilities on adversaries' preferences while planning security scenarios. Moreover, the proposed methodology is capable of efficiently identifying an optimal defensive strategy given a security scenario (i.e., an attack) through maximizing defenders' expected utility.
AB - Before the tragedy of 9/11, the perception of risk in process plants was mainly focused on accidental events caused by technical failures, human errors or natural events. However, since then, the risk of deliberate actions against process facilities - also known as security risk - has also become a concern. Security risk assessment of engineering systems and infrastructures constitutes a complex task since a significant multitude of technical and socio-political information is needed to reasonably predict the risk of intentional malevolent acts. In the present study, a methodology based on Bayesian network (BN) has been applied to increase the security of critical infrastructures via cost-effective allocation of security measures. Using the probability updating feature of BN, the proposed methodology can be employed to investigate the effect of vulnerabilities on adversaries' preferences while planning security scenarios. Moreover, the proposed methodology is capable of efficiently identifying an optimal defensive strategy given a security scenario (i.e., an attack) through maximizing defenders' expected utility.
UR - http://resolver.tudelft.nl/uuid:6674d108-82d3-4c23-a893-84bf01c432f0
UR - http://www.scopus.com/inward/record.url?scp=85054074995&partnerID=8YFLogxK
U2 - 10.3303/CET1867042
DO - 10.3303/CET1867042
M3 - Chapter
AN - SCOPUS:85054074995
SN - 9788895608648
VL - 67
SP - 247
EP - 252
BT - Chemical Engineering Transactions
PB - Italian Association of Chemical Engineering
ER -