Protecting JPEG Images Against Adversarial AttacksProtecting JPEG Images Against Adversarial AttacksPrakash, Aaditya and Moran, Nick and Garber, Solomon and DiLillo, Antonella and Storer, James A.2018
Paper summarydavidstutzMotivated by JPEG compression, Prakash et al. propose an adaptive quantization scheme as defense against adversarial attacks. They argue that JPEG experimentally reduces adversarial noise; however, it is difficult to automatically decide on the level of compression as it also influences a classifier’s performance. Therefore, Prakash et al. use a saliency detector to identify background region, and then apply adaptive quantization – with coarser detail at the background – to reduce the impact of adversarial noise. In experiments, they demonstrate that this approach outperforms simple JPEG compression as defense while having less impact on the image quality.
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Protecting JPEG Images Against Adversarial Attacks
Storer, James A.
arXiv e-Print archive - 2018 via Local Bibsonomy