Rainbow Artifacts from Electromagnetic Signal Injection Attacks on Image Sensors
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arXiv
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| Auteurs principaux: | , , , |
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| Format: | Preprint |
| Publié: |
2025
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| _version_ | 1866911049377120256 |
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| author | Zhang, Youqian Ji, Xinyu Wang, Zhihao Jiang, Qinhong |
| author_facet | Zhang, Youqian Ji, Xinyu Wang, Zhihao Jiang, Qinhong |
| contents | Image sensors are integral to a wide range of safety- and security-critical systems, including surveillance infrastructure, autonomous vehicles, and industrial automation. These systems rely on the integrity of visual data to make decisions. In this work, we investigate a novel class of electromagnetic signal injection attacks that target the analog domain of image sensors, allowing adversaries to manipulate raw visual inputs without triggering conventional digital integrity checks. We uncover a previously undocumented attack phenomenon on CMOS image sensors: rainbow-like color artifacts induced in images captured by image sensors through carefully tuned electromagnetic interference. We further evaluate the impact of these attacks on state-of-the-art object detection models, showing that the injected artifacts propagate through the image signal processing pipeline and lead to significant mispredictions. Our findings highlight a critical and underexplored vulnerability in the visual perception stack, highlighting the need for more robust defenses against physical-layer attacks in such systems. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2507_07773 |
| institution | arXiv |
| publishDate | 2025 |
| record_format | arxiv |
| spellingShingle | Rainbow Artifacts from Electromagnetic Signal Injection Attacks on Image Sensors Zhang, Youqian Ji, Xinyu Wang, Zhihao Jiang, Qinhong Cryptography and Security Computer Vision and Pattern Recognition B.8; I.4 Image sensors are integral to a wide range of safety- and security-critical systems, including surveillance infrastructure, autonomous vehicles, and industrial automation. These systems rely on the integrity of visual data to make decisions. In this work, we investigate a novel class of electromagnetic signal injection attacks that target the analog domain of image sensors, allowing adversaries to manipulate raw visual inputs without triggering conventional digital integrity checks. We uncover a previously undocumented attack phenomenon on CMOS image sensors: rainbow-like color artifacts induced in images captured by image sensors through carefully tuned electromagnetic interference. We further evaluate the impact of these attacks on state-of-the-art object detection models, showing that the injected artifacts propagate through the image signal processing pipeline and lead to significant mispredictions. Our findings highlight a critical and underexplored vulnerability in the visual perception stack, highlighting the need for more robust defenses against physical-layer attacks in such systems. |
| title | Rainbow Artifacts from Electromagnetic Signal Injection Attacks on Image Sensors |
| topic | Cryptography and Security Computer Vision and Pattern Recognition B.8; I.4 |
| url | https://arxiv.org/abs/2507.07773 |