Image encryption based on a chaos system can effectively protect the privacy of digital images. It is said that a 3D chaotic system has a larger parameter range, better unpredictability and more complex behavior compared to low-dimension chaotic systems. Motivated by this fact, we propose a new image cryptosystem that makes use of a 3D chaotic system. There are three main steps in our scheme. In the first step, the chaotic system uses the hash value of the plaintext image to generate three sequences. In step two, one of the sequences is used to dynamically select confusion and diffusion methods, where confusion and diffusion have three algorithms, respectively, and will produce 3²ⁿ (n > 100) combinations for encryption. In step three, the image is divided into hundreds of overlapping subblocks, along with the other two sequences, and each block is encrypted in the confusion and diffusion process. Information entropy, NPCR, UACI results and various security analysis results show that the algorithm has a better security performance than existing, similar algorithms, and can better resist clipping, noise, statistical analysis and other attacks.

The existing discrete cosine transform (DCT) differential quantization robust watermarking has poor robustness against JPEG compression, cropping, and combined attacks. To improve such issues, a pair of adjacent block coefficients are selected to reduce the offset and improve the robustness of the watermarking. Firstly, at adjacent positions of neighboring blocks, the differences of medium frequency coefficients are calculated, and then the differences are used to divide regions. Experimental results show that this method is more robust to various attacks than the existing DCT differential quantization robust watermarking. The accuracy of watermark extraction under a JPEG compression attack increased by 2%, while the error rates of watermark extraction under a cropping attack and a combination attack decreased by 4.4% and 9%.

Improved encryption devices place higher demands on the randomness and security of encrypted images. Existing image encryption optimization methods based on single- or multi-objectives concentrate on selecting keys and parameters, resulting in relatively fixed parameters and keys that are susceptible to leakage and cracking. Despite the possibility of increasing security, the DNA coding encryption method does not fully take into account the large capacity of image data and the difference between pixels, resulting in a limited level of randomness. To overcome the problems above, this paper proposes a method for generating complex texture features in images using random variation of pixels. With an annealing algorithm that can find an optimal solution in a large search space, the image is optimally optimized in terms of information entropy, pixel correlation, and value of x². Each iteration involves selecting one of 2⁵⁶³² combinations of DNA coding and operation. In comparison with current encryption algorithms based on optimization algorithms and DNA coding, this method is more secure and unbreakable.