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A Decision Support System for the Assessment of Seaports’ Security Under Fuzzy Environment

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Modeling, Computing and Data Handling Methodologies for Maritime Transportation

Part of the book series: Intelligent Systems Reference Library ((ISRL,volume 131))

Abstract

Today’s maritime environments are characterized by high uncertainties due to the diverse risks associated with seaports’ operations. Although much effort has been made in developing new methods to prevent incidents in seaports, yet security breaches still occur largely because of the complex interactions of the multiplicity of stakeholders involved in their operations such as the terminal operators, seafarers and law enforcement agencies which often lead to the disruption of their systems. Experience has shown that complexities in seaports’ systems do not allow for flexible response to security incidents. In order to address the numerous risks associated with seaport operations, a subjective security risk analysis is developed to enhance the security of the system. In the analysis process, security systems/measures are identified and described, their performance is measured based on three risk parameters; the likelihood of threat (l), vulnerability of the system (v) and consequence or impact (c) resulting from a successful threat exercise of a flaw in the system. A Fuzzy Analytical Hierarchy Process (FAHP) is utilized to analyse the complex structure of the system and determine the weights of security systems/measures while evidential reasoning (ER) is used to synthesize the risk analysis. It is envisaged that the proposed approach could provide analysts with a flexible tool to understand the importance of developing robust resilience strategies that aim at enhancing seaport security in a systematic manner.

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John, A., Yang, Z., Riahi, R., Wang, J. (2018). A Decision Support System for the Assessment of Seaports’ Security Under Fuzzy Environment. In: Konstantopoulos, C., Pantziou, G. (eds) Modeling, Computing and Data Handling Methodologies for Maritime Transportation. Intelligent Systems Reference Library, vol 131. Springer, Cham. https://doi.org/10.1007/978-3-319-61801-2_6

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  • DOI: https://doi.org/10.1007/978-3-319-61801-2_6

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  • Print ISBN: 978-3-319-61800-5

  • Online ISBN: 978-3-319-61801-2

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