Deliberate attacks (security attacks) pose a significant threat to offshore Oil&Gas critical infrastructures as they have the potential of triggering major event scenarios with severe consequences on people, property, and the surrounding environment. The standards API RP 70 and API RP 70I address security issues in the offshore Oil&Gas sector, providing a semi-quantitative approach to evaluate the actual level of security risk. However, as the credibility of security attacks grows, security risk assessments should be approached in a more systematic and quantitative way to measure vulnerabilities and determine the level of protection available in the site. In this context, the present study introduces a systematic quantitative procedure using Bayesian Network (BN) to calculate the probability of success of physical attacks and the role of preventive and mitigative response strategies. The procedure is applied to a case study allowing to show its potential for improving security in the offshore Oil&Gas industry.@en

Offshore Oil&Gas facilities are attractive targets of intentional malicious attacks (security attacks) that may trigger cascading events (e.g., the release and dispersion of hazardous material and/or energy, fires, explosions) with consequences on people, environment, and assets. The severity of these consequences is potentially similar to those arising from major accident scenarios originated by conventional safety-related causes. Current practice in managing the risk of security attacks mostly relies on qualitative or semi-quantitative procedures developed over the years in the offshore Oil&Gas industry. In the present study, a systematic quantitative procedure is developed, based on a Bayesian Network (BN) approach, for calculating the probability of success of physical security attacks, taking into account both preventive and mitigative security intervention strategies. The procedure addresses the specific framework of the offshore Oil&Gas industry. A case study concerning an offshore fixed Oil&Gas platform allowed us to demonstrate the quality of the results that can be achieved and their potential towards the improvement of the security of the installations considered.@en

Industrial infrastructures, in particular those where hazardous substances are stored or handled, may be the target of malicious acts aiming at the disruption of normal operations. In the present study a toolbox of complementary and synergic techniques (Correspondence Analysis (CA), Fishbone Diagrams, Cause-Consequence Chains, Adversary Sequence Diagram, Root Cause Analysis) was applied to the in-depth analysis of physical security- and cybersecurity-related events that affected the process industry. The unprecedented original set of information obtained provides novel insights concerning these events. Clear correlations among security threats, including cyber-threats, and specific industrial sectors, as well as among the final scenarios and the different security threats from which they originate were identified by CA. In particular, vandalism resulted strongly correlated with the transportation of hazardous substances, and theft of materials with oil and gas pipelines. When considering chemical and petrochemical sites, cyber-attacks and the use of improvised explosives resulted to be the most common attack modes performed by the threat actors. Personnel and vehicle gateways resulted key elements when designing the Physical Protection System (PPS) of a facility. Insiders having the permission to enter the site bypass such controls, and were responsible of several successful attacks. Overall, the results confirm the concreteness of security-related events in the process industry and provide an original structured and detailed insight on the attack patterns experienced to date. Moreover, the results and the data obtained provide a novel set of baseline information for the application of SVA (Security Vulnerability Assessment) or SRA (Security Risk Assessment) methodologies in facilities where hazardous substances are stored or processed.

@en