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.

摘要

恶意黑客可以破坏智慧城市中的集成交通管理系统 (ITMS) 速度传感器，导致车辆误读速度并导致道路上发生碰撞或拥堵。基于保护动机理论（PMT），我们提出了一种基于时间序列的智慧城市网络风险评估和缓解（SCRAM）模型，该模型包含三个模块，用于智慧城市管理员。与PMT的威胁评估部分相一致，我们的网络风险评估（CRA）模块采用季节性时间序列预测方法，以ITMS平均速度为输入，输出车辆平均速度异常的概率。随后，基于风险理论的概念，网络风险量化 (CRQ) 模块计算智慧城市由于路径上的碰撞或拥堵而导致的预期损失。