Abstract

Modern physical protection systems integrate a number of security systems (including procedures, equipments, and personnel) into a single interface to ensure an adequate level of protection of people and critical assets against malevolent human actions. Due to the critical functions of a protection system, the quantitative evaluation of its effectiveness is an important issue that still raises several challenges. In this paper we propose a model-driven approach to support the design and the evaluation of physical protection systems based on (a) UML models representing threats, protection facilities, assets, and relationships among them, and (b) the automatic construction of a Bayesian Network model to estimate the vulnerability of different system configurations. Hence, the proposed approach is useful both in the context of vulnerability assessment and in designing new security systems as it enables what-if and cost–benefit analyses. A real-world case study is further illustrated in order to validate and demonstrate the potentiality of the approach. Specifically, two attack scenarios are considered against the depot of a mass transit transportation system in Milan, Italy.

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