Security vulnerability assessment of gas pipelines using discrete-time Bayesian network

Donya Fakhravar, N. Khakzad, Genserik Reniers, Valerio Cozzani

Research output: Contribution to journalArticleScientificpeer-review

15 Citations (Scopus)
23 Downloads (Pure)

Abstract

Security of chemical and oil & gas facilities became a pressing issue after the terrorist attacks of 9/11, due to relevant quantities of hazardous substances that may be present in these sites. Oil & gas pipelines, connecting such facilities, might be potential targets for intentional attacks. The majority of methods addressing pipeline security are mostly qualitative or semi-quantitative, based on expert judgment and thus potentially subjective. In the present study, an innovative security vulnerability assessment methodology is developed, based on Discrete-time Bayesian network (DTBN) technique to investigate the vulnerability of a hazardous facility (pipeline in this study) considering the performance of security countermeasures in place. The methodology is applied to an illustrative gas pipeline in order to rank order the pipeline segments based upon their criticality.
Original languageEnglish
Pages (from-to)714-725
JournalProcess Safety and Environmental Protection
Volume111
DOIs
Publication statusPublished - 2017

Keywords

  • Security vulnerability assessment
  • Physical countermeasures
  • Relative attractiveness
  • Attack tree
  • Discrete-time Bayesian network
  • Gas pipeline

Fingerprint Dive into the research topics of 'Security vulnerability assessment of gas pipelines using discrete-time Bayesian network'. Together they form a unique fingerprint.

  • Cite this