Abstract Joint compression and encryption algorithms are one of the key candidate technologies for JPEG image processing. However, these methods inevitably impair compression efficiency of JPEG images. To balance protection power and compression performance, a novel JPEG image cryptosystem is proposed based on a complex chaotic map. Specifically, a two dimensional coupled Rastrigin complex hyperchaotic map (2D-CRCCM) is studied as the key generator. Meanwhile, the global and group permutation algorithms are designed to prevent the leakage of sensitive information in the adaptive discrete cosine transform (DCT) domain, namely the alternating current coefficients (ACCs) and direct current components (DCCs). Finally, a lightweight binary stream encryption method is presented to further enhance the data security during the transmission process. Experimental results show that the proposed approach effectively mitigates the risk of sensitive information leakage. It also reduces file size increment, maintains format compatibility, and exhibits linear time complexity in worst-case scenarios. Notably, across most compression ratios, our method yields higher PSNR value than others, and better than standard JPEG compression.

With the swift rise in the number of digital images, their transmission and storage are facing severe challenges. Although traditional encryption algorithms can effectively protect image privacy, the noise-like features they generate may attract more attention from attackers. To address these problems, a new visually meaningful image encryption algorithm based on compressive sensing and a multi-objective optimization method is proposed. The proposed algorithm includes an improvement method for measurement matrix based on singular value decomposition and an advanced embedding method, and a multi-objective optimization algorithm is used for parameter selection. Simulation results show that the proposed algorithm performs well in reconstruction quality, visual security, and efficiency. Compared with existing algorithms, the proposed method demonstrates significant advantages in efficiency, reconstruction quality, embedding rate, and robustness.

At present, design of discrete memristor based chaotic maps starts to attract the attention of the scientists, but it is still in its incipient stage. In this paper, spatiotemporal chaos in the Sine map lattice with discrete memristor coupling is investigated. Firstly, the$3\times m$higher dimensional chaotic map is proposed, where there are$m$discrete memristors and$m$state variable difference items as the inputs of the discrete memristors. Since it is a spatiotemporal chaotic system, thus it can generate massive chaotic sequences according to the system dimension. Secondly, dynamical characteristics of the system is carried out theoretically and numerically. It shows that there are$m$positive Lyapunov exponents with high complexity. The two examples with one memristor and two memristors are analyzed, and it indicates that the system has rich dynamics including hyperchaos and multistability. Finally, analogue circuit and DSP digital circuit of the two illustrative examples and an Knowm memristor based example are designed to verify the physical realizability of the proposed discrete memristor chaotic maps.

A universal modular plus parallel (MPP) method is proposed to construct enhanced chaotic maps, including one-dimensional MPP chaotic map (1D-MPPCM) and high-dimensional MPPCM (HD-MPPCM). It is theoretically proved that 1D-MPPCM model can significantly increase the Lyapunov exponent (LE) and parameter range of seed chaotic maps. To further increase the system dimension, the HD-MPPCM model is established through the close-loop parallel coupling mechanism. Based on several typical seed chaotic maps, some new parallel chaotic maps are obtained by self-parallel and hybrid-parallel, and their dynamics are analyzed by phase diagram, LEs, permutation entropy (PE) complexity and statistic$\chi ^{2}$. The simulation results show that the proposed maps have large maximum Lyapunov exponent (MLE), PE complexity, and uniform distribution. In particular, HD-MPPCMs have some interesting characteristics, such as full positive LEs, hyperchaotic behavior, global chaos, and full attractor distribution, which are the potential model for engineering applications. To further verify the practicability, the proposed maps are implemented on DSP platform, and applied to pseudo-random number generator (PRNG).