基于像素的隐私保护深度神经网络图像加密安全性研究

Warit Sirichotedumrong, Yuma Kinoshita, H. Kiya
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引用次数: 10

摘要

本文旨在评估基于像素的图像加密方法的安全性,该方法已被提出将无视觉信息的图像应用于深度神经网络(DNN),在抗纯密文攻击(COA)方面具有鲁棒性。此外,我们提出了一种新的基于dnn的COA,旨在重建加密图像的视觉信息。在同一加密密钥和不同加密密钥两种加密密钥条件下,对所提攻击的有效性进行了评估。结果表明,如果使用相同的加密密钥对图像进行加密,所提出的攻击可以恢复加密图像的视觉信息。此外,基于像素的图像加密方法对COA具有鲁棒性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
On the Security of Pixel-Based Image Encryption for Privacy-Preserving Deep Neural Networks
This paper aims to evaluate the safety of a pixel-based image encryption method, which has been proposed to apply images with no visual information to deep neural networks (DNN), in terms of robustness against ciphertext-only attacks (COA). In addition, we propose a novel DNN-based COA that aims to reconstruct the visual information of encrypted images. The effectiveness of the proposed attack is evaluated under two encryption key conditions: same encryption key, and different encryption keys. The results show that the proposed attack can recover the visual information of the encrypted images if images are encrypted under same encryption key. Otherwise, the pixel-based image encryption method has robustness against COA.
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