Cybersecurity Considerations for Heavy Vehicle Event Data Recorders
Abstract Trust in the digital data from heavy vehicle event data recorders (HVEDRs) is paramount to using the data in legal contests. Ensuring the trust in the HVEDR data requires an examination of the ways the digital information can be attacked, both purposefully and inadvertently. The goal or objective of an attack on HVEDR data will be to have the data omitted in a case. To this end, we developed an attack tree and establish a model for violating the trust needed for HVEDR data. The attack tree provides context for mitigations and also for functional requirements. A trust model is introduced as well as a discussion on what constitutes forensically sound data. The main contribution of this article is an attack tree-based model of both malicious and accidental events contributing to compromised event data recorder (EDR) data. A comprehensive list of mitigations for HVEDR systems results from this analysis.