Image encryption based on logistic chaotic systems and deep autoencoder - Sang, Yongpeng; Sang, Jun; Alam, Mohammad S. (Pattern recognition letters, 2022)
•Deep autoencoder is incorporated with logistic chaotic systems for image encryption.•A single network can be utilized to encrypt different plaintext images.•Extensive experiments demonstrate that the proposed method is with high sencurity while can effectively resist attacks Please check editor name in valid PIT's and styled as title-footnote or misc-text according to JSS. In this paper, we propose a novel image encryption method based on logistic chaotic systems and deep autoencoder. In the encryption phase, first, the plaintext image is randomly scrambled by a logistic chaotic system. Then, the random scrambled image is encoded by a deep autoencoder to generate the ciphertext image. In order to obtain the ciphertext image with uniform distribution, we incorporated the uniform distribution constraint into the training of the deep autoencoder. The resulting ciphertext image contains high randomness, which is critical for an excellent image encryption algorithm. Histogram analysis, information entropy analysis, key space analysis, key sensitivity analysis, correlation analysis, and ablation experiments show that the proposed encryption algorithm can effectively resist attacks and has excellent encryption performance while providing high security.