Privacy-preserving deep neural networks (DNNs) have been proposed for protecting data privacy in the cloud server. Although several encryption schemes for visually protection have been proposed for privacy-preserving DNNs, several attacks enable to restore visual information from encrypted images. On the other hand, it has been confirmed that the block-wise image encryption scheme which utilizes block and pixel shuffling is robust against several attacks. In this paper, we propose a jigsaw puzzle solver-based attack to restore visual information from encrypted images including block and pixel shuffling. In experiments, images encrypted by using the block-wise image encryption are mostly restored by using the proposed attack.

翻译：为保护云层服务器的数据隐私,已提议建立保护深度神经网络(DNNs),以保护云层服务器中的数据隐私。虽然提出了若干保护隐私DNS的视觉加密方案,但若干次攻击能够从加密图像中恢复视觉信息。另一方面,已证实使用块状和像素转换的块状图像加密方案对几次攻击十分有力。在本文件中,我们提议采用拼图解答器攻击,以从加密图像中恢复视觉信息,包括块状和像素转换。在实验中,使用块状图像加密的图像大多通过使用拟议攻击来恢复。