Singapore Institute of Technology
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Demo: Invisible Adversarial Stripes against Traffic Sign Recognition in Autonomous Driving

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posted on 2025-05-30, 09:17 authored by DONGFANG GUODONGFANG GUO, Yuting Wu, Yimin Dai, Pengfei Zhou, Xin LouXin Lou, Rui Tan

Camera-based computer vision is crucial for autonomous vehicle perception. We demonstrate GhostStripe [5], an attack system that uses light-emitting diodes and exploits the camera’s rolling shutter effect to generate adversarial stripes that are invisible to humans while misleading traffic sign recognition. To maintain stable attack effectiveness, GhostStripe controls the timing of the modulated light emission, adapting to both the camera’s framing operation and the movement of the victim vehicle. Evaluated on real testbeds, GhostStripe can stably spoof traffic sign recognition results for up to 97% of frames to a wrong class when the victim vehicle passes the road section.

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Journal/Conference/Book title

SENSYS '24: Proceedings of the 22nd ACM Conference on Embedded Networked Sensor Systems

Publication date

2024-11-04

Version

  • Published

Rights statement

© Authors, 2025. This is the author's version of the work. It is posted here for your personal use. Not for redistribution. The definitive Version of Record was published in SENSYS '24: Proceedings of the 22nd ACM Conference on Embedded Networked Sensor Systems, http://dx.doi.org/10.1145/3666025.3699401.

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