Risk assessment of serious crime with fuzzy random theory

This paper presents a novel approach for assessing the potential risk of serious crime events (e.g. terrorist attack). The modelling and assessment of such risk is carried out under uncertain circumstances because of both the randomness and fuzziness inherent in crime data. The approach is based on fuzzy random theory that complements probability theory, with an additional dimension of imprecision. This allows for potential loss caused by a crime to be expressed as a fuzzy random variable. Crime risk is therefore estimated as the mean chance of a fuzzy random event, where the resulting loss reaches a given confidence level. The concept of the average loss per unit of time is also introduced, in order to calculate the rate at which the loss may increase due to possible crime events. The work is compared with typical existing approaches and supported with examples throughout that illustrate its utility.