Probabilistic vulnerability assessment of chemical clusters subjected to external acts of interference

Abstract

Acts of interference against chemical facilities or chemical clusters might result in severe consequences in case of a successful attack (major explosions, fires, toxic dispersions or environmental contamination). Although process facilities implement multiple safety barriers to control process hazards that may result in major accidents and plants are mostly well equipped from a safety point of view, the security attention and resources dedicated to the protection of assets against external adversaries are not at all at the same level. The lack of a consolidated practice in the risk-informed implementation of security countermeasures goes hand in hand with the existence of very few systematic procedures for the quantitative performance evaluation of security systems, particularly physical protection systems (PPSs). Therefore, it is crucial to develop a methodology aimed at supporting the assessment of industrial facilities vulnerability to external attacks. The present contribution addresses the vulnerability assessment using a probabilistic risk analysis approach, supported by a model based on Bayesian Networks (BN). The proposed methodology includes the quantitative performance assessment of the protection systems, intended as both physical protection systems adopted as security countermeasures and safety barriers, in interfering with the progress of a potential attack. A case study is analyzed to exemplify the methodology application.