Cryptanalysis of Dual-Stage Permutation Encryption Using Large-Kernel Convolutional Neural Network and Known Plaintext Attack

被引:0
|
作者
Chang, Ching-Chun [1 ]
Xu, Shuying [2 ]
Gao, Kai [2 ]
Chang, Chin-Chen [2 ]
机构
[1] Feng Chia Univ, Informat & Commun Secur Res Ctr, Taichung 407102, Taiwan
[2] Feng Chia Univ, Dept Informat Engn & Comp Sci, Taichung 407102, Taiwan
关键词
cryptanalysis; image encryption; convolution network; known plaintext attack; IMAGES;
D O I
10.3390/cryptography8030041
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
Reversible data-hiding in encrypted images (RDHEI) plays a pivotal role in preserving privacy within images stored on cloud platforms. Recently, Wang et al. introduced a dual-stage permutation encryption scheme, which is highly compatible with RDHEI techniques. In this study, we undertake an exhaustive examination of the characteristics inherent to the dual-stage permutation scheme and propose two cryptanalysis schemes leveraging a large-kernel convolutional neural network (LKCNN) and a known plaintext attack (KPA) scheme, respectively. Our experimental findings demonstrate the effectiveness of our cryptanalysis schemes in breaking the dual-stage permutation encryption scheme. Based on our investigation, we highlight significant security vulnerabilities in the dual-stage permutation encryption scheme, raising concerns about its suitability for secure image storage and privacy protection in cloud environments.
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页数:16
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