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Vulnerability assessment of chemical facilities to intentional attacks based on Bayesian Network
- Source :
- Reliability engineering and system safety
- Publication Year :
- 2018
- Publisher :
- Elsevier BV, 2018.
-
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.
- Subjects :
- Risk
Engineering
Economics
Process (engineering)
020209 energy
Physical protection
Vulnerability
0211 other engineering and technologies
Security risk
02 engineering and technology
Computer security
computer.software_genre
Industrial and Manufacturing Engineering
Vulnerability assessment
Bayesian Network
0202 electrical engineering, electronic engineering, information engineering
Bayesian Networks
Physical protection systems
Probabilistic assessment
Safety, Risk, Reliability and Quality
Representation (mathematics)
Vulnerability (computing)
021110 strategic, defence & security studies
business.industry
Probabilistic logic
Bayesian network
Physical protection system
Work in process
Reliability and Quality
Safety
business
computer
Mathematics
Subjects
Details
- ISSN :
- 09518320
- Volume :
- 169
- Database :
- OpenAIRE
- Journal :
- Reliability Engineering & System Safety
- Accession number :
- edsair.doi.dedup.....3a73a184fc3b4ae8fca5457c7192506f