Sarima-Based Cyber-Risk Assessment and Mitigation Model for A Smart City’s Traffic Management Systems (Scram)

Abstract

ABSTRACT A malicious hacker can compromise the integrated traffic management systems (ITMS) speed sensors in a smart city, causing a vehicle to misread the speed and result in collision or congestion on the pathways. Based on protection-motivation theory (PMT), we propose a Time series-based Cyber-risk Assessment and Mitigation for smart cities (SCRAM) model comprising three modules for the smart city administrator. In line with the threat appraisal component of PMT, our cyber-risk assessment (CRA) module uses a Seasonal time series forecasting method, takes ITMS average speed as an input, and outputs the probability of anomalies in the average speed of vehicles. Subsequently, based on the concepts of risk theory, the cyber-risk quantification (CRQ) module calculates the expected loss for a smart city due to collision or congestion on the pathways. In line with the coping appraisal component of PMT, our cyber-risk mitigation (CRM) module proposes strategies for the smart-city administrator to reduce cyber-risk using technological means and pass the residual risk to third-party cyber-insurer.