Autonomous driving is a safety critical application of sensing and decision-making technologies. Communication technologies extend the awareness capabilities of vehicles, beyond what is achievable with the on-board systems only. Nonetheless, issues typically related to wireless networking must be taken into account when designing safe and reliable autonomous systems. The aim of this work is to present a control algorithm and a communication paradigm over 5G networks for negotiating traffic junctions in urban areas. The proposed control framework has been shown to converge in a finite time and the supporting communication software has been designed with the objective of minimizing communication delays. At the same time, the underlying network guarantees reliability of the communication. The proposed framework has been successfully deployed and tested, in partnership with Ericsson AB, at the AstaZero proving ground in Goteborg, Sweden. In our experiments, three heterogeneous autonomous vehicles successfully drove through a 4-way intersection of 235 square meters in an urban scenario.
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. CCS CONCEPTS• Security and privacy → Distributed systems security; Information flow control.
Attacks targeting smart grid infrastructures can result in the disruptions of power supply as well as damages to costly equipment, with significant impact on safety as well as on end-consumers. It is therefore of essence to identify attack paths in the infrastructure that lead to safety violations and to determine critical components that must be protected. In this paper, we introduce a methodology (HA-Grid) that incorporates both safety and security modelling of smart grid infrastructure to analyse the impact of cyber threats on the safety of smart grid infrastructures. HA-Grid is applied on a smart grid testbed to identify attack paths that lead to safety hazards, and to determine the common nodes in these attack paths as critical components that must be protected.
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