Hazard Driven Threat Modelling for Cyber Physical Systems
Luca Maria Castiglione and Emil C. Lupu. 2020. Hazard Driven Threat Modelling for Cyber Physical Systems. In Proceedings of the 2020 Joint Workshop on CPS&IoT Security and Privacy(CPSIOTSEC’20). Association for Computing Machinery, New York, NY, USA, 13–24.
Adversarial actors have shown their ability to infiltrate enterprise networks deployed around Cyber Physical Systems (CPSs) through social engineering, credential stealing and file-less infections. When inside, they can gain enough privileges to maliciously call legitimate APIs and apply unsafe control actions to degrade the system performance and undermine its safety. Our work lies at the intersection of security and safety, and aims to understand dependencies among security, reliability and safety in CPS/IoT. We present a methodology to perform hazard driven threat modelling and impact assessment in the context of CPSs. The process starts from the analysis of behavioural, functional and architectural models of the CPS. We then apply System Theoretic Process Analysis (STPA) on the functional model to highlight high-level abuse cases. We leverage a mapping between the architectural and the system theoretic(ST) models to enumerate those components whose impairment provides the attacker with enough privileges to tamper with or disrupt the data-flows. This enables us to find a causal connection between the attack surface (in the architectural model) and system level losses. We then link the behavioural and system theoretic representations of the CPS to quantify the impact of the attack. Using our methodology it is possible to compute a comprehensive attack graph of the known attack paths and to perform both a qualitative and quantitative impact assessment of the exploitation of vulnerabilities affecting target nodes. The framework and methodology are illustrated using a small scale example featuring a Communication Based Train Control (CBTC) system. Aspects regarding the scalability of our methodology and its application in real world scenarios are also considered. Finally, we discuss the possibility of using the results obtained to engineer both design time and real time defensive mechanisms.