Benchmarking container port security risks by applying a FIS methodology

Abstract

This paper presents a fuzzy inference approach to estimate the security level of a port in a manner that it provides essential information to the stakeholders when evaluating security risks under uncertainty. A fuzzy inference system (FIS) methodology is developed on account to four predefined security factors. A team of experts is used to rank and survey potential port security risks whereas the experts' ordinal preferences were combined using the Cook and Seiford method to come up with a consensus risks' ranking. To validate the model, results are compared with those from an established fuzzy evidential reasoning approach given the same security risk inputs. The verified FIS can provide useful insights for security analysts to conduct security risk quantification under high uncertainty in data in the maritime sector as well as a wider range of other industries (e.g., aerospace and process) facing high terrorism threats with appropriate tailor and adaptation.