Fast Object Removal Attacks on Safety-Critical Video-based Perception Systems
By leveraging data from video-based perception systems, intelligent transportation systems (ITS) support safety-critical applications that improve road safety. However, adversaries may manipulate video frames to compromise downstream perception modules, causing failures in safety-critical functions and increasing risks to vulnerable road users. This paper presents a novel attack model and an end-to-end framework for near-real-time targeted object removal attack on a video-based safety-critical system. The end-to-end attack pipeline consists of four stages: localizing targets in each frame, retrieving coherent patches from earlier frames, blending them using context-aware alpha compositing...
| Authors | Mohammad Imtiaz Hasan, M Sabbir Salek, Nathan Jones et al. |
|---|---|
| Primary category | cs.CR |
| Published | 3 August 2026 |
| Last updated at source | 3 August 2026 |
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