STAR-TRANS Modeling Language: Risk Modeling in the STAR-TRANS Risk Assessment Framework

STAR-TRANS Modeling Language: Risk Modeling in the STAR-TRANS Risk Assessment Framework

Dimitris Zisiadis (Centre for Research & Technology Hellas (CERTH), Greece), George Thanos (Centre for Research & Technology Hellas (CERTH), Greece), Spyros Kopsidas (Centre for Research & Technology Hellas (CERTH), Greece) and George Leventakis (Center for Security Studies (KEMEA), Greece)
DOI: 10.4018/978-1-4666-8473-7.ch021
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Transportation networks are open and accessible, by design, and thus vulnerable to malicious attacks. Transportation networks are integral parts of larger systems, where individual transportation networks form a network-of-networks within a defined geographical region. A security incident on an asset can propagate to new security incidents in interconnected assets of the same or different networks, resulting in cascading failures in the overall network-of-networks. The present work introduces the STAR-TRANS Modeling Language (STML) and provides a reference implementation case. STML is a feature-rich, domain specific, high-level modeling language, capable of expressing the concepts and processes of the Strategic Risk Assessment and Contingency Planning in Interconnected Transportation Networks (STAR- TRANS) framework. STAR-TRANS is a comprehensive transportation security risk assessment framework for assessing related risks that provides cohered contingency management procedures for interconnected, interdependent and heterogeneous transport networks. STML has been used to produce the STAR-TRANS Impact Assessment Tool.
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For performing risk assessment, the first and most important step is identifying, as comprehensively as possible, the set of risks involved. In the vast majority of cases the number of such risks is large enough, so that aggregation, filtering and ranking methodologies should be applied. Carr, Konda, Monarch, Walker and Ulrich in “Taxonomy-Based Risk Identification” (1993) followed a field test risk identification process consisting of a series of interviews with groups of selected personnel. Webler et al. (1995) outlined a risk ranking methodology through an extensive survey example dealing with a public utility infrastructure in New Jersey. Morgan et al. (2000) proposed a ranking methodology designed for use by federal risk management agencies, calling for interagency taskforces to define and categorize the risks to be ranked. Berdica (2002) proposed that vulnerability analysis of transport networks should be regarded as an overall framework through which different transport studies could be conducted to determine how well a transport system would perform when exposed to different kinds and intensities of disturbances. Haimes (1998) created a Hierarchical Holographic Model (HHM) for the transportation system and the facilities it supports. Haimes, et al. (2002) offered a methodological framework that identifies, prioritizes, assesses and manages risks to complex, large-scale systems. The risk filtering, ranking, and management (RFRM) methodology captures all six questions of risk assessment and management. Di Gangi (2005) recommended a quantitative method in order to figure out if the infrastructure of an area is strong enough for evacuation procedure.

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