This paper proposes an image compression and encryption algorithm based on 3D Logistic-Sine-Memristor coupled map (3D-LSMCM), compressed sensing (CS) and the Game of Life scrambling with Semi-Tensor Product (STP-GoL) to solve the problems of computational redundancy and security vulnerability in image transmission. First, the 3D-LSMCM is initialized by using a hash function to generate a random chaotic sequence iteratively and it improves key unpredictability. Second, The Semi-Tensor Product (STP) measurement matrix constructed from these sequences significantly reduces storage requirements in CS whilst supporting lossless compression through arithmetic coding. STP technology enables flexible matrix dimension design, effectively lowering computational costs. Finally, STP is used to convert logical operations into matrix operations in the entire encryption process. The cryptographic technique consists of the STP-GoL scrambling, chaotic global scrambling with STP (STP-CG) and the chain XOR diffusion based on STP (STP-CXOR). Furthermore, theoretical analysis indicates that the computational complexity of this algorithm is expected to be reduced by approximately 28% compared with recent studies, while the average information entropy of the ciphertext reaches 7.9987. Overall, this study proposes a novel, secure and efficient image compression and encryption method, with its source code publicly available at https://github.com/Ssshou7/STP-GoL.

This article introduces a memristor-based neural network with bidirectional cyclic constructed from square wave pulse functions. Additionally, we design an image encryption and compression network framework incorporating a self-attention mechanism based on this memristor neural network. Specifically, this study introduces a novel model of a high-dimensional multiscroll memristor neural network (MMNN) that incorporates three neurons and a synapse made from memristive elements. Its complex dynamic behavior is analyzed in depth. Theoretical analysis and numerical simulations demonstrate that the proposed MMNN can generate an unlimited number of hyperchaotic multiscroll attractors and various other types of dynamics, which can be fine-tuned by modifying the system’s parameters or initial conditions. Additionally, a simulated equivalent circuit for MMNN proves the validity and practicality of the multiscroll attractor behavior. Finally, an image encryption and compression network framework based on end-to-end and MMNN and the self-attention mechanism is proposed, called SAECNet. Extensive performance evaluation highlights the system’s high accuracy in compression and reconstruction, strong encryption capabilities, and solid defense against potential attacks.

The demand of information security drives the core application of pseudo-random generator in cryptography. Furthermore, chaos theory offers novel methodologies for the Internet of Things (IoT) to address nonlinear and high-dimensional dynamic challenges, demonstrating substantial potential in enhancing security, energy efficiency, and predictive accuracy. Compared with dissipative chaotic systems, the phase space conservation, symmetric Lyapunov exponential spectrum and non-reconfiguration of conservative chaotic systems significantly improve the attack resistance and dynamic stability, and the pseudo-random number generator designed by conservative chaotic systems has obvious advantages. In this paper, we explore a novel method for designing a new class of Hamiltonian chaotic systems with simple structural and complex behaviors. A five-dimensional (5D) system is presented and analyzed in detail. Using bifurcation diagram, Lyapunov exponents (LEs), complexity, phase portraits, and other indicators. Compared to existing systems, the proposed system exhibits better characteristics such as structural simplicity and heightened complexity. Additionally, the National Institute of Standards and Technology (NIST) has verified that the proposed system exhibits good randomness and has been deployed on a hardware platform for digital signal processing.

The chaotic system as a source of randomness is very important for chaos-based secure communication. Different from other chaotic maps, this work explores an n-dimensional (n-D) nondegenerate discrete hyperchaotic map with any desired Lyapunov exponents (LEs). First, theoretical analysis proves that the proposed map is chaotic. Based on this proof, it is designed for any desired LEs. To illustrate the effectiveness of the n-dimensional (n-D) new map, we use some chaotic and nonchaotic maps as examples. The simulation results demonstrated that the proposed maps exhibit stronger chaotic properties and more complex dynamic behaviors compared to some previous results. Moreover, the chaotic signals generated by our maps passed NIST and TestU01 tests, which show that our map has better randomness. Furthermore, a chaotic system with higher LEs do not necessarily have higher complexity degree. Next, the proposed map is implemented by hardware digital signal processing platform, indicating the feasibility for industrial applications. More importantly, compared with other maps, the proposed map has simple structure with more complex behaviors and fewer parameters, and it is easy to set the desired LEs. Finally, we design a novel image encryption algorithm based on the proposed chaotic system and dynamic S-boxes. The experimental results show that the proposed chaotic system can be effectively applied in the field of data encryption.

To provide robust security measures for audio data during transmission, this article has developed a novel dual-channel audio encryption scheme based on chaos theory. Specifically, a new 2-D chaotic system called 2-D infinite collapse with logistic map (2-D-ICLM) is designed in this article. Compared to traditional 2-D chaotic systems, the 2-D-ICLM exhibits a larger parameter space, complexity, and richness, along with high unpredictability and randomness. These characteristics provide potential advantages and applications in the field of encryption. In the proposed encryption scheme, audio information serves as input to a hash function, which generates the initial values and parameters for the 2-D-ICLM, producing the keystream for the cryptographic system. Considering the correlation between the two channels of audio information, the information from the left and right channels is fused to create a new audio signal for encryption. Scrambling and diffusion processes are performed synchronously in the encryption algorithm, with the ciphertext information from the left channel utilized in the encryption of the right channel audio. The experimental results prove the effectiveness of the suggested audio encryption technique, effectively countering various conventional attack methods and showcasing its robust security features. The correlation of adjacent elements of ciphertext audio is 0.0013, the NSCR and UACI is around 0.9960 and 0.3345, and the efficiency is 0.0003 s/KB.