In recent years, chaos-based multimedia cryptosystems have gained prominence due to their nonlinear properties, such as sensitivity to initial conditions and long-term unpredictability, which parallel the cryptographic requirements of confusion and diffusion. However, many such systems lack standardization and deviate from secure design principles, resulting in practical vulnerabilities. This article presents a comprehensive cryptanalysis of a widely cited video cryptosystem. The target system combines S-box substitution—derived from either a 12D chaotic map or the Ikeda delay differential equation (DDE)—with a Cipher Block Chaining (CBC) diffusion scheme. Through an analysis of the encryption structure, fundamental design defects are identified. Specifically, the CBC diffusion mechanism lacks key dependence, and the system exhibits an excessive reliance on fixed, publicly exposed S-boxes. These vulnerabilities are demonstrated through chosen-plaintext attacks, known-plaintext attacks, and chosen-ciphertext attacks. Experimental results confirm that the S-box can be fully reconstructed, thereby facilitating the complete decryption of video content in the absence of the secret key. Beyond exposing vulnerabilities, this study offers constructive contributions by proposing six concrete improvement strategies, including dynamic key generation, structural enhancement, and dynamic S-box indexing. This work provides practical suggestions for designing secure chaos-based multimedia cryptosystems, offering valuable references for future research and promoting the development of efficient encryption systems.

Images are widely used in social networks, necessitating efficient and secure transmission, especially in bandwidth-constrained environments. This article aims to develop a color image encryption algorithm that enhances security while optimizing computational efficiency. A novel parallel color image encryption algorithm based on the 2-D logistic-Rulkov neuron map (2D-LRNM) is proposed. In this approach, the three channels of the color image are first separated. Cross-channel information interaction is introduced to form three new channels, which are then processed in parallel. During the encryption process of each channel, a block-wise parallel encryption mechanism is applied, ensuring simultaneous encryption of each block. This block-wise strategy effectively leverages parallel computing resources and balances the task load. To meet the demand for a large number of keystreams during encryption, the 2D-LRNM is introduced. It combines the simplicity and chaotic properties of the Logistic map with the multitimescale dynamics and neurodynamic behaviors of the Rulkov map. By overcoming the dimensional limitations inherent in the single Logistic map, this approach extends the system to a 2-D framework, significantly increasing the complexity of chaotic behavior and improving its unpredictability. Experimental results demonstrate that the proposed encryption algorithm achieves high security and reduces computation time by approximately 83.3%.

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.

Discrete chaotic systems based on memristors exhibit excellent dynamical properties and are more straightforward to implement in hardware, making them highly suitable for generating cryptographic keystreams. However, most existing memristor-based chaotic systems rely on a single memristor. This paper introduces a novel discrete chaotic system employing dual memristors, named the 3D memristive cubic map with dual discrete memristors (3D-MCM). The 3D-MCM system demonstrates richer and more intricate dynamical behaviors compared to its single-memristor counterparts, as verified through bifurcation diagrams, Lyapunov exponent spectra, and complexity analyses. Notably, the system exhibits coexisting attractors, substantially enhancing its dynamical complexity. Hardware implementation of the 3D-MCM attractors confirms its feasibility for industrial applications. To illustrate the system’s potential in encryption tasks, this study integrates the quaternary-based permutation and dynamic emanating diffusion (QPDED-IE) scheme with the 3D-MCM for image encryption. Experimental results demonstrate that the QPDED-IE scheme based on the 3D-MCM exhibits strong diffusion and confusion properties, effectively resisting cryptanalytic attacks.

The security of a chaos-based image encryption (IE) systems is based upon chaotic map’s performance and the encryption algorithm’s permutation and diffusion strategies. Nevertheless, existing IE schemes exhibit different drawbacks, such as limited disordering capabilities, inadequate dynamic performance, and the chaotic maps’ insensitivity. To address these limitations, this study presents an octal-based shuffling and multilayer rotational diffusing IE (OSMRD-IE) utilizing a 2-D hybrid Michalewicz–Ackley (2-D-HMA) map. The 2-D-HMA map has the capability to generate new hyperchaotic maps by integrating hybrid functions using different encapsulation functions. The integration of a map generator could lead to dynamic nature, chaotic perturbations, and parameter control mechanisms. To enhance the algorithm’s resilience against cyberthreats, the 2-D-HMA map-based OSMRD-IE scheme shuffles the pixels using octal-base scrambling and manipulates pixel values through multilayer rotation. By means of comparisons with existing techniques, the OSMRD-IE scheme’s reliability and 2-D-HMA map’s dynamic performance are validated independently. The superior chaotic properties of the 2-D-HMA map are evident in the experimental results, establishing OSMRD-IE as the more reliable scheme in both visual and quantitative comparisons.

Currently, discrete memristors are a focal point in the study of chaotic maps. Similar to memristors, memcapacitors-another type of memory circuit component-have not received widespread attention in the design of chaotic maps. In this article, we propose a 4-D memcapacitive hyperchaotic logistic map (4D-MHLM) by integrating memcapacitors with the logistic map. The dynamical behavior of the 4D-MHLM is analyzed using Lyapunov exponent analysis, and the impact of different parameters on system performance is discussed. The complexity of generating pseudo-random sequences with the 4D-MHLM is investigated through complexity analysis, including spectral entropy complexity and C0 complexity. Notably, attractor analysis reveals a unique phenomenon of infinite coexisting attractors within the 4D-MHLM. Finally, the chaotic attractor generated by the 4D-MHLM is successfully implemented on a hardware platform. Theoretical analysis and digital circuit implementation results indicate that the 4D-MHLM exhibits rich dynamical behavior and higher complexity, offering significant value for practical applications.

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.

A chaotic system is a mathematical model exhibiting random and unpredictable behavior. However, existing chaotic systems suffer from suboptimal parameters regarding chaotic indicators. In this study, a novel leader Pareto grey wolf optimizer (LP-GWO) is proposed for multiobjective (MO) design of 2D parametric hyperchaotic system (2D-PHS). The MO capability of LP-GWO is improved by integrating a LP solution within the Pareto optimal set. The effectiveness of LP-GWO is corroborated through a comparison with regular MO versions of grey wolf optimizer (GWO), artificial bee colony, particle swarm optimization, and differential evolution. Additionally, the validation extends to the exploration of LP-GWO’s performance across four variants of the 2D-PHS optimized by the compared algorithms. A 2D-PHS model with eight parameters is conceived and then optimized using LP-GWO by ensuring tradeoff between two objectives: Lyapunov exponent (LE) and Kolmogorov entropy (KE). A globally optimal design is chosen for freely improving the two objectives. The chaotic performance of 2D-PHS significantly outperforms existing systems in terms of precise chaos indicators. Therefore, the 2D-PHS has the best ergodicity and erraticity due to optimal parameters provided by LP-GWO.

A novel chaotic map based on Euler number namely Euler Map (EMAP) is suggested for image encryption algorithms (IEAs). The chaotic behavior of EMAP is appreciated with bifurcation analysis and Lyapunov Exponent (LE). The LE is the best due to the ultimate and most stable characteristic in case compared with the literature. A two-stage IEA, permutation and diffusion, is used to demonstrate the successful performance of EMAP, and this is how the success of EMAP is verified. The IEA with EMAP is examined in secure cryptanalyses and computational complexity. Some results are validated with the state of the arts. In the comparison, the suggested EMAP-based IEA stands out due to the diversity and complexity performance. It achieves a cropped image having minimum loss, a good operation time of 0.2297s and a low computational complexity. Therefore, the proposed EMAP can be applied to realistic systems.

In this article, the authors propose an adaptive frequency median filter (AFMF) to remove the salt and pepper noise. AFMF uses the same adaptive condition of adaptive median filter (AMF). However, AFMF employs frequency median to restore grey values of the corrupted pixels instead of the median of AMF. The frequency median can exclude noisy pixels from evaluating a grey value of the centre pixel of the considered window, and it focuses on the uniqueness of grey values. Hence, the frequency median produces a grey value closer to the original grey value than the one by the median of AMF. Therefore, AFMF outperforms AMF. In experiments, the authors tested the proposed method on a variety of natural images of the MATLAB library, as well as the TESTIMAGES data set. Additionally, they also compared the denoising results of AFMF to the ones of other state‐of‐the‐art denoising methods. The results showed that AFMF denoises more effectively than other methods.