Vulnerability assessment of chemical facilities to intentional attacks based on Bayesian Network
Francesca Argenti,
Gabriele Landucci,
Genserik Reniers and
Valerio Cozzani
Reliability Engineering and System Safety, 2018, vol. 169, issue C, 515-530
Abstract:
Chemical facilities may be targets of deliberate acts of interference triggering major accidents (fires, explosion, toxic dispersions) in process and storage units. Standard methodologies for vulnerability assessment are based on qualitative or semi-quantitative tools, currently not tailored for this type of facilities and not accounting for the role of physical protection systems. In the present study, a quantitative approach to the probabilistic assessment of vulnerability to external attacks is presented, based on the application of a dedicated Bayesian Network (BN). BN allowed the representation of interactions among attack impact vectors and resistance of process units, which determine the final outcomes of an attack. A specific assessment of protection systems, based on experts’ elicitation of performance data, allowed providing a knowledge support to the evaluation of probabilities. The application to an industrial case study allowed the assessment of the potentialities of the approach, which may support both the evaluation of the vulnerability of a given facility, and the performance assessment of the security physical protection system in place.
Keywords: Security risk; Physical protection systems; Vulnerability; Probabilistic assessment; Bayesian Networks (search for similar items in EconPapers)
Date: 2018
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (16)
Downloads: (external link)
http://www.sciencedirect.com/science/article/pii/S0951832016305208
Full text for ScienceDirect subscribers only
Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.
Export reference: BibTeX
RIS (EndNote, ProCite, RefMan)
HTML/Text
Persistent link: https://EconPapers.repec.org/RePEc:eee:reensy:v:169:y:2018:i:c:p:515-530
DOI: 10.1016/j.ress.2017.09.023
Access Statistics for this article
Reliability Engineering and System Safety is currently edited by Carlos Guedes Soares
More articles in Reliability Engineering and System Safety from Elsevier
Bibliographic data for series maintained by Catherine Liu ().