Adversarial Camera Patch: An Effective and Robust Physical-World Attack on Object Detectors

Kalibinuer Tiliwalidi

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arXiv · 2312.06163

Adversarial Camera Patch: An Effective and Robust Physical-World Attack on Object Detectors

Kalibinuer Tiliwalidi

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Abstract

Nowadays, the susceptibility of deep neural networks (DNNs) has garnered significant attention. Researchers are exploring patch-based physical attacks, yet traditional approaches, while effective, often result in conspicuous patches covering target objects. This leads to easy detection by human observers. Recently, novel camera-based physical attacks have emerged, leveraging camera patches to execute stealthy attacks. These methods circumvent target object modifications by introducing perturbations directly to the camera lens, achieving a notable breakthrough in stealthiness. However, prevailing camera-based strategies necessitate the deployment of multiple patches on the camera lens, which introduces complexity. To address this issue, we propose an Adversarial Camera Patch (ADCP).

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Kalibinuer Tiliwalidi. 2023-12-11. Adversarial Camera Patch: An Effective and Robust Physical-World Attack on Object Detectors. https://arxiv.org/abs/2312.06163

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