Modeling Approaches for Vehicular ECUs Networks for Synthetic Data Generation.

This master’s thesis is dedicated to an in-depth examination of Battery Electric Vehicles (BEVs), with a pronounced emphasis on constructing a detailed systematic model of BEVs and seamlessly integrating the Controller Area Network (CAN) platform. Utilizing Simscape within the Simulink environment as the foundational framework, the primary objective is to simulate cybersecurity attacks on vehicular systems. This approach allows the generation of attack scenarios common to BEVs, providing invaluable insights into the resultant behaviors and vulnerabilities exposed by these cybersecurity breaches. Central to this thesis is the development and application of a BEV model in Simulink, designed specifically to facilitate the emulation of CAN injection attacks. This innovative methodology enables the study to not only generate data but also to directly observe the effects of various cyber threats on the BEV’s operational integrity and safety. By conducting a series of simulated attacks, the research offers a unique perspective on the potential impacts these security breaches may have on BEVs, thereby underscoring the critical need for advanced protective measures in the automotive domain. Further exploration within the thesis encompasses a comprehensive review of the existing literature on CAN injection attacks, alongside a detailed investigation into the deployment and analysis of such attacks on the developed BEV model. This investigation aims to assess the effectiveness of different cyberattacks and their consequent effects on the BEV system, thus highlighting the importance of implementing robust cybersecurity strategies. In conclusion, the thesis reiterates the essential findings and stresses the imperative for enhanced cybersecurity protocols in BEVs. It advocates for future research directions, including the implementation of sophisticated intrusion detection systems and the adoption of secure communication frameworks, to mitigate the risks associated with CAN injection attacks. This study significantly contributes to the ongoing discourse on safeguarding BEVs against cyber threats, advocating for proactive and advanced measures to maintain the vehicles’ reliability and integrity in an interconnected automotive landscape.