A Novel Chaotic Image Encryption Algorithm Based on Coordinate Descent and SHA-256

In recent years, chaotic image encryption algorithms with key and plaintext association have been developed, which are essentially similar to a one-time pad at a time because each encryption requires the transmission of the key. However, some existing schemes cannot uniquely map the seed key to the initial value of the chaotic system, which leads to the reduction of the key space of the encryption system. In addition, some schemes use the same key to encrypt the same image, which does not conform to the one-time pad strategy. This paper solves these problems from two aspects. On the one hand, random pixels are inserted into a plain image and then a hash value is generated using SHA-256. Different seed keys can be obtained even if the same image is encrypted. On the other hand, the Sequential Expansion Algorithm (SEA) and Feedback Iterative Piece-Wise Linear Chaotic Mapping (FI-PWLCM) are proposed to realize the one-to-one correspondence between the seed key and the encrypted key stream. SEA can quickly generate seed key sensitive and random sequences. FI-PWLCM achieves one-to-one correspondence with the seed key through feedback iteration with more control parameters. The mapping not only has the rapidity of PWLCM, but also can produce more complex chaotic sequences. Besides, this paper proposes a Segmented Coordinate Descent (SCD) method for histogram statistical optimization of images to improve the ability of cryptosystems against statistical attacks. Experiments and security analysis show that the algorithm can resist chosen-plaintext (chosen-ciphertext) attacks, brute force attacks, statistical attacks and so on. Compared with most current algorithms, it achieves the best performance in the statistical properties of histogram and entropy.