Jeremy Daily, David Nnaji, and Ben Ettlinger (Colorado State University)

Diagnostics and maintenance systems create frequent, legitimate, and intermittent connections to a vehicle’s communication network. These connections are typically made with a vehicle diagnostics adapter (VDA), which serves to translate vehicle network communications to a Windows based service computer running diagnostics software. With heavy vehicles, the diagnostic systems are written and maintained by the supplier of the electronic control units. This means there may be multiple different software packages needed to maintain a heavy vehicle. However, all of these software systems use an interface defined by the American Trucking Association (ATA) through their Technology and Maintenance Council (TMC) using Recommended Practice (RP) number 1210, the Windows API for vehicle diagnostics. Therefore, most diagnostics and maintenance communications on a heavy vehicles utilize a thirdparty VDA with little to no cybersecurity controls. The firmware and drivers for the VDA can be entry points for cyber attacks. In this demonstration, a vehicle diagnostics session is attacked using the VDA firmware, VDA PC driver, and a middle-person attack. A proposed secure diagnostics gateway is demonstrated to secure the diagnostics communications between the heavy vehicle network and the diagnostics application, thus defending against attacks on vulnerable VDA components. Furthermore, the maintenance operations are often trusted and an attacker gains physical access to the vehicle with the unknowing technician. Since these diagnostic systems are connected to the Internet and run Windows, the traditional security issues associated with Windows PCs are now part of the heavy vehicle.

View More Papers

Data Poisoning Attacks to Deep Learning Based Recommender Systems

Hai Huang (Tsinghua University), Jiaming Mu (Tsinghua University), Neil Zhenqiang Gong (Duke University), Qi Li (Tsinghua University), Bin Liu (West Virginia University), Mingwei Xu (Tsinghua University)

Read More

Detecting CAN Masquerade Attacks with Signal Clustering Similarity

Pablo Moriano (Oak Ridge National Laboratory), Robert A. Bridges (Oak Ridge National Laboratory) and Michael D. Iannacone (Oak Ridge National Laboratory)

Read More

Processing Dangerous Paths – On Security and Privacy of...

Jens Müller (Ruhr University Bochum), Dominik Noss (Ruhr University Bochum), Christian Mainka (Ruhr University Bochum), Vladislav Mladenov (Ruhr University Bochum), Jörg Schwenk (Ruhr University Bochum)

Read More

Panel – Experiment Artifact Sharing: Challenges and Solutions

Moderator: Laura Tinnel (SRI International) Panelists: Clémentine Maurice (CNRS, IRIS); Martin Rosso (Eindhoven University of Technology); Eric Eide (U. Utah)

Read More