In cryptosystems, the generation of random keys is crucial. The random number generator is required to have a sufficiently fast generation speed to ensure the size of the keyspace. At the same time, the randomness of the key is an important indicator to ensure the security of the encryption system. The chaotic random number generator has been widely used in cryptosystems due to the uncertainty, non-repeatability, and unpredictability of chaotic systems. However, chaotic systems, especially high-dimensional chaotic systems, have slow calculation speed and long iteration time. This caused a conflict between the number of random keys and the speed of generation. In this paper, we introduce the Least Squares Generative Adversarial Networks(LSGAN)into random number generation. Using LSGAN’s powerful learning ability, a novel learning random number generator is constructed. Six chaotic systems with different structures and different dimensions are used as training sets to realize the rapid and efficient generation of random numbers. Experimental results prove that the encryption key generated by this scheme can pass all randomness tests of the National Institute of Standards and Technology (NIST). Hence, our result shows that LSGAN has the potential to improve the quality of the random number generators. Finally, the results are successfully applied to the image encryption scheme based on selective scrambling and overlay diffusion, and good results are achieved.

Image encryption is an effective technology to protect digital image confidentiality. This paper presents an image segmentation encryption algorithm based on a hybrid chaotic system. First, a chaotic sequence is obtained by iterating a Quantum Cellular Neural Network (QCNN), and then it is scrambled by a 4-D hyperchaotic system to generate a key pool. Second, the chaotic pointers generated by 3-D chaotic systems and QCNN with different initial values are used to get the keys for image segmentation, scrambling, and diffusion from the key pool. Then, the plain-image is divided into two blocks by the chaotic segmentation method and scrambled by intra-block and inter-block pixel exchange. In addition, two blocks are statically diffused, and the cipher-image is obtained by dynamic diffusing after combining the image blocks. Especially, the key pool increases the efficiency of the proposed algorithm, and chaotic segmentation reduces the cipher-image pixel correlation. Finally, the simulation results and performance analysis indicate that the proposed algorithm has a well-security, high sensitivity, and faster speed.

In order to guarantee the security of digital images, image encryption is a good tool. This article puts forward a novel image encryption/decryption algorithm based on bit-level permutation and dynamic overlap diffusion. Firstly, location information set by users is used to scramble the plain image in the bit-level, changing the pixel position of the image while changing the pixel value. Then, using the plaintext related method to control the iteration parameters of Arnold transform. These two parts together form the permutation process of the algorithm. Thirdly, the overlap steps are set according to the encryption security requirements, and dynamic overlap diffusion is performed on the permutation image. At the same time, the plaintext information entropy and variance are used to update the diffusion key in the five-dimensional hyperchaotic system to achieve the plaintext correlation of the encryption key. Arnold transform and dynamic overlap diffusion can ensure that different key streams are generated when encrypting different images. Finally, experimental analysis and numerical simulation show that our algorithm has high efficiency, high security, high sensitivity, and can effectively resist various attacks.

With the rapid development of remote sensing technology, satellite remote sensing images have been involved in many areas of people’s lives. Remote sensing images contain military secrets, land profiles, and other sensitive data, so it is urgent to encrypt remote sensing images. This paper proposes a dual-channel key transmission model. The plaintext related key is embedded into the ciphertext image through bit-level key hiding transmission strategy, which enhanced the ability of ciphertext image to resist known-plaintext attack and chosen plaintext attack. In addition, a multiband remote sensing image encryption algorithm based on Boolean cross-scrambling and semi-tensor product diffusion is designed. Firstly, the pixel positions of each band of the remote sensing image are disturbed. Then, the random sequence generated by the four-dimensional chaotic system is processed and deformed to obtain a Boolean matrix. Based on the generated Boolean matrix and certain rules, the cross-confusion between the bands is carried out. Finally, the semi-tensor product operation is used in the diffusion process. Simulation results and experimental analysis show that the proposed algorithm obtains a larger key space and has stronger antiattack ability than other remote sensing image encryption algorithms. It can meet the security transmission of multiband remote sensing image in open space.