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Journal Article

Cybersecurity Considerations for Heavy Vehicle Event Data Recorders

2018-12-14
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.
Journal Article

Chip and Board Level Digital Forensics of Cummins Heavy Vehicle Event Data Recorders

2020-04-14
2020-01-1326
Crashes involving Cummins powered heavy vehicles can damage the electronic control module (ECM) containing heavy vehicle event data recorder (HVEDR) records. When ECMs are broken and data cannot be extracted using vehicle diagnostics tools, more invasive and low-level techniques are needed to forensically preserve and decode HVEDR data. A technique for extracting non-volatile memory contents using non-destructive board level techniques through the available in-circuit debugging port is presented. Additional chip level data extraction techniques can also provide access to the HVEDR data. Once the data is obtained and preserved in a forensically sound manner, the binary record is decoded to reveal typical HVDER data like engine speed, vehicle speed, accelerator pedal position, and other status data. The memory contents from the ECM can be written to a surrogate and decoded with traditional maintenance and diagnostic software.
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