论文标题
针对隐私的图像分类的可压缩图像加密的安全评估针对仅密文的攻击
Security Evaluation of Compressible Image Encryption for Privacy-Preserving Image Classification against Ciphertext-only Attacks
论文作者
论文摘要
已经讨论了使用深层神经网络针对多次攻击进行图像分类的可学习图像加密方案的安全性。另一方面，已经提出了使用视觉变压器的块拼图图像加密，该图像通过将图像将图像划分为置换的块，适用于无损压缩方法，例如JPEG标准。尽管在大量加密块的条件下，已经评估了使用块之间使用相关性的拼图拼图求解器的稳健性，这些拼图拼图求解器的攻击已得到评估，但从未评估过具有少量块的加密图像的安全性。在本文中，通过使用拼图拼图求解器攻击来评估Block障碍物的块图像加密的安全性加密。
The security of learnable image encryption schemes for image classification using deep neural networks against several attacks has been discussed. On the other hand, block scrambling image encryption using the vision transformer has been proposed, which applies to lossless compression methods such as JPEG standard by dividing an image into permuted blocks. Although robustness of the block scrambling image encryption against jigsaw puzzle solver attacks that utilize a correlation among the blocks has been evaluated under the condition of a large number of encrypted blocks, the security of encrypted images with a small number of blocks has never been evaluated. In this paper, the security of the block scrambling image encryption against ciphertext-only attacks is evaluated by using jigsaw puzzle solver attacks.
