Literature Database Entry

so2019physical


Steven So, Jonathan Petit and David Starobinski, "Physical Layer Plausibility Checks for Misbehavior Detection in V2X Networks," Proceedings of Proceedings of the 12th Conference on Security and Privacy in Wireless and Mobile Networks, Miami, FL, May 2019, pp. 84–93.

Abstract

Location spoofing is a proven and powerful attack against Vehicle-to-everything (V2X) communication systems that can cause traffic congestion and other safety hazards. Recent work also demonstrates practical spoofing attacks that can circumvent application layer sanity checks. In this paper, we propose three novel physical layer plausibility checks that leverage the received signal strength indicator (RSSI) of basic safety messages (BSMs). These plausibility checks have multi-step mechanisms to improve not only the detection rate, but also to decrease false positives. These checks can be run independently by each vehicle and do not rely on the assumption that the majority of vehicles is honest. We comprehensively evaluate the performance of these plausibility checks using the VeReMi dataset (which we enhance along the way) for several types of attacks. We show that the best performing physical layer plausibility check among the three considered achieves an overall detection rate of 83.73% and a precision of 95.91%, far outperforming recently proposed machine learning-based misbehavior detection methods operating at the application layer.

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Steven So
Jonathan Petit
David Starobinski

BibTeX reference

@inproceedings{so2019physical,
    address = {Miami, FL},
    author = {So, Steven and Petit, Jonathan and Starobinski, David},
    booktitle = {Proceedings of the 12th Conference on Security and Privacy in Wireless and Mobile Networks},
    doi = {10.1145/3317549.3323406},
    isbn = {978-1-4503-6726-4},
    month = {5},
    pages = {84--93},
    publisher = {ACM},
    series = {WiSec '19},
    title = {{Physical Layer Plausibility Checks for Misbehavior Detection in V2X Networks}},
    year = {2019},
   }
   
   

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