Publication
ICASSP 2022
Conference paper

When Does Backdoor Attack Succeed in Image Reconstruction? A Study of Heuristics vs. Bi-Level Solution

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Abstract

Recent studies have demonstrated the lack of robustness of image reconstruction networks to test-time evasion attacks, posing security risks and potential for misdiagnoses. In this paper, we evaluate how vulnerable such networks are to training-time poisoning attacks for the first time. In contrast to image classification, we find that trigger-embedded basic backdoor attacks on these models executed using heuristics lead to poor attack performance. Thus, it is non-trivial to generate backdoor attacks for image reconstruction. To tackle the problem, we propose a bi-level optimization (BLO)-based attack generation method and investigate its effectiveness on image reconstruction. We show that BLO-generated backdoor attacks can yield a significant improvement over the heuristics-based attack strategy.

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ICASSP 2022

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