Marc Roeschlin (ETH Zurich, Switzerland), Giovanni Camurati (ETH Zurich, Switzerland), Pascal Brunner (ETH Zurich, Switzerland), Mridula Singh (CISPA Helmholtz Center for Information Security), Srdjan Capkun (ETH Zurich, Switzerland)

A Controller Area Network (CAN bus) is a message-based protocol for intra-vehicle communication designed mainly with robustness and safety in mind. In real-world deployments, CAN bus does not offer common security features such as message authentication. Due to the fact that automotive suppliers need to guarantee interoperability, most manufacturers rely on a decade-old standard (ISO 11898) and changing the format by introducing MACs is impractical. Research has therefore suggested to address this lack of authentication with CAN bus Intrusion Detection Systems (IDSs) that augment the bus with separate modules. IDSs attribute messages to the respective sender by measuring physical-layer features of the transmitted frame. Those features are based on timings, voltage levels, transients—and, as of recently, Time Difference of Arrival (TDoA) measurements. In this work, we show that TDoA-based approaches presented in prior art are vulnerable to novel spoofing and poisoning attacks. We describe how those proposals can be fixed and present our own method called EdgeTDC. Unlike existing methods, EdgeTDC does not rely on Analog-to-digital converters (ADCs) with high sampling rate and high dynamic range to capture the signals at sample level granularity. Our method uses time-to-digital converters (TDCs) to detect the edges and measure their timings. Despite being inexpensive to implement, TDCs offer low latency, high location precision and the ability to measure every single edge (rising and falling) in a frame. Measuring each edge makes analog sampling redundant and allows the calculation of statistics that can even detect tampering with parts of a message. Through extensive experimentation, we show that EdgeTDC can successfully thwart masquerading attacks in the CAN system of modern vehicles.

View More Papers

Efficient Privacy-Preserved Processing of Multimodal Data for Vehicular Traffic...

Meisam Mohammady (Iowa State University), Reza Arablouei (Data61, CSIRO)

Read More

A Transcontinental Analysis of Account Remediation Protocols of Popular...

Philipp Markert (Ruhr University Bochum), Andrick Adhikari (University of Denver), Sanchari Das (University of Denver)

Read More

MetaWave: Attacking mmWave Sensing with Meta-material-enhanced Tags

Xingyu Chen (University of Colorado Denver), Zhengxiong Li (University of Colorado Denver), Baicheng Chen (University of California San Diego), Yi Zhu (SUNY at Buffalo), Chris Xiaoxuan Lu (University of Edinburgh), Zhengyu Peng (Aptiv), Feng Lin (Zhejiang University), Wenyao Xu (SUNY Buffalo), Kui Ren (Zhejiang University), Chunming Qiao (SUNY at Buffalo)

Read More

WIP: The Feasibility of High-performance Message Authentication in Automotive...

Evan Allen (Virginia Tech), Zeb Bowden (Virginia Tech Transportation Institute), Randy Marchany (Virginia Tech), J. Scot Ransbottom (Virginia Tech)

Read More