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

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.