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

PASS: A System-Driven Evaluation Platform for Autonomous Driving Safety...

Zhisheng Hu (Baidu Security), Junjie Shen (UC Irvine), Shengjian Guo (Baidu Security), Xinyang Zhang (Baidu Security), Zhenyu Zhong (Baidu Security), Qi Alfred Chen (UC Irvine) and Kang Li (Baidu Security)

Read More

PGFUZZ: Policy-Guided Fuzzing for Robotic Vehicles

Hyungsub Kim (Purdue University), Muslum Ozgur Ozmen (Purdue University), Antonio Bianchi (Purdue University), Z. Berkay Celik (Purdue University), Dongyan Xu (Purdue University)

Read More

Practical Blind Membership Inference Attack via Differential Comparisons

Bo Hui (The Johns Hopkins University), Yuchen Yang (The Johns Hopkins University), Haolin Yuan (The Johns Hopkins University), Philippe Burlina (The Johns Hopkins University Applied Physics Laboratory), Neil Zhenqiang Gong (Duke University), Yinzhi Cao (The Johns Hopkins University)

Read More

Bitcontracts: Supporting Smart Contracts in Legacy Blockchains

Karl Wüst (ETH Zurich), Loris Diana (ETH Zurich), Kari Kostiainen (ETH Zurich), Ghassan Karame (NEC Labs), Sinisa Matetic (ETH Zurich), Srdjan Capkun (ETH Zurich)

Read More