Visible to the public Model-based simulation and threat analysis of in-vehicle networks

TitleModel-based simulation and threat analysis of in-vehicle networks
Publication TypeConference Paper
Year of Publication2019
AuthorsLekidis, Alexios, Barosan, Ion
Conference Name2019 15th IEEE International Workshop on Factory Communication Systems (WFCS)
Keywordsadequate testing, air pollution, Atmospheric modeling, automated controls, automobile industry, automotive systems, computer network security, connectivity interfaces, Controller area network (CAN), controller area network security, Cyber-physical systems, cyber-security risks, driving experience, in-vehicle features, in-vehicle networks, intelligent navigation, Internet of Things, IoT, model-based design, network data, network simulation, operational errors, power control, pubcrawl, rapid pace, Real-time Systems, Resiliency, safety systems, SDN technologies, security assessment, security of data, security risks, security threats, Sensors, software defined networking, software defined networking technologies, threat analysis, Threat Landscape, Time measurement, vehicular ad hoc networks
AbstractAutomotive systems are currently undergoing a rapid evolution through the integration of the Internet of Things (IoT) and Software Defined Networking (SDN) technologies. The main focus of this evolution is to improve the driving experience, including automated controls, intelligent navigation and safety systems. Moreover, the extremely rapid pace that such technologies are brought into the vehicles, necessitates the presence of adequate testing of new features to avoid operational errors. Apart from testing though, IoT and SDN technologies also widen the threat landscape of cyber-security risks due to the amount of connectivity interfaces that are nowadays exposed in vehicles. In this paper we present a new method, based on OMNET++, for testing new in-vehicle features and assessing security risks through network simulation. The method is demonstrated through a case-study on a Toyota Prius, whose network data are analyzed for the detection of anomalies caused from security threats or operational errors.
Citation Keylekidis_model-based_2019