Application In Image Encryption Research Articles

A new controllable multi-wing chaotic system: applications in high-security color image encryption

A new controllable multi-wing chaotic system: applications in high-security color image encryption

Multi-wing chaotic system based on meminductor and its application in image encryption

Meminductor is a novel type of nonlinear device following the memristor, characterized by its memory properties. Currently, research on meminductors is still in its infancy, with their physical devices yet to be formally realized. Therefore, conducting fundamental research on their nonlinear circuit properties and applications is of great significance. In this paper, a new multi-wing chaotic system is proposed based on the mathematical model of a magnetically controlled meminductor. By varying the values of its parameters, the system can generate two-wing, three-wing, and four-wing chaotic attractors. Various analytical methods are employed to study the dynamical behaviours of the proposed chaotic system. The results demonstrate that the system is highly sensitive to its initial conditions and control parameters, which makes it suitable for image encryption. Based on the new system, we propose a new algorithm for image encryption that combines the newly established four-dimensional multi-wing chaotic system with bit plane decomposition technique, firstly, the high four-bit planes containing 94% image information are disordered by S-type permutation, then the disordered bit planes perform operation of XOR with the random matrix generated by chaotic sequences, and finally, the encrypted image is obtained by merging the bit planes.

A Novel Parameter-Variabled and Coupled Chaotic System and Its Application in Image Encryption with Plaintext-Related Key Concealment.

The design of a chaotic system and pseudo-random sequence generation method with excellent performance and its application in image encryption have always been attractive and challenging research fields. In this paper, a new model of parameter-variabled coupled chaotic system (PVCCS) is established by interaction coupling between parameters and states of multiple low-dimensional chaotic systems, and a new way to construct more complex hyperchaotic systems from simple low-dimensional systems is obtained. At the same time, based on this model and dynamical DNA codings and operations, a new pseudo-random sequence generation method (PSGM-3DPVCCS/DNA) is proposed, and it is verified that the generated pseudo-random sequence of PSGM-3DPVCCS/DNA has excellent random characteristics. Furthermore, this paper designs a novel pixel chain diffusion image encryption algorithm based on the proposed parameter-variabled coupled chaotic system (PVCCS) in which the hash value of plaintext image is associated with the initial key to participate in the encryption process so that the encryption key is closely associated with plaintext, which improves the security of the algorithm and effectively resists the differential cryptanalysis risk. In addition, an information hiding method is designed to hide the hash value of plaintext image in ciphertext image so that the hash value does not need to be transmitted in each encryption, and the initial key can be reused, which solves the key management problem in application and improves the application efficiency of the encryption algorithm. The experimental analysis shows that the chaotic system constructed in this paper is creative and universal and has more excellent chaotic characteristics than the original low-dimensional system. The sequence generated by the pseudo-random sequence generation method has excellent pseudo-random characteristics and security, and the image encryption algorithm can effectively resist differential cryptanalysis risk, showing advanced encryption performance.

Memristor-coupled cubic hyperchaotic system, feedback synchronization and its application in image encryption

Discrete memristive chaotic systems play a crucial role in information security, and chaotic synchronization form the bedrock of secure and confidential communication. To enhance the chaotic complexity of the Cubic map, we introduce a memristor-coupled Cubic hyperchaotic system by integrating a discrete absolute memristor model with the Cubic map. The dynamics are thoroughly investigated through attractor phase diagrams, bifurcation diagrams, SE complexity analysis, and diagrams illustrating the distribution of dynamic behaviors. Furthermore, we establish methods for chaos control and nonlinear feedback synchronization for the memristive Cubic map. Leveraging this feedback synchronization, we achieve encrypted transmission of digital images. Simulation results validate the feasibility and robust security of the proposed encrypted transmission scheme.

A new 2D cross hyperchaotic Sine-modulation-Logistic map and its application in bit-level image encryption

Chaotic theory is being increasingly researched for application in image encryption scheme (IES). This paper presents a novel two-dimensional cross hyperchaotic Sine-modulation-Logistic map (2D-CHSLM) based on the famous Sine and Logistic maps. The hyperchaotic behaviors of 2D-CHSLM are demonstrated through bifurcation diagrams, trajectory plots, Lyapunov exponents, histogram, correlation dimension, sensitivity to initial conditions, sample entropy, 0–1 test, and NIST 800–22 test. A new bit-level IES with traditional an encryption structure is proposed utilizing 2D-CHSLM. The 2D-CHSLM-IES performs 2D-CHSLM-based bit-level confusion using a zigzag transform and 2D-CHSLM-based cross coupled diffusion operations to generate a highly secure cipher-image. Simulations and security analyses, including key space, key sensitivity, histogram, correlation, information entropy, encryption quality, known-plain and chosen-plain attacks, floating Frequency, differential attack, noise and data loss attacks, demonstrate the robust security of the proposed 2D-CHSLM-IES.

Improved Chua’s chaotic system with a novel memristor: generating multi-scroll hidden attractors and applications in image encryption

In this paper, a new method for generating multi-scroll chaotic attractors by introducing a new memristor model into an improved Chua’s system is presented. The dynamic characteristics of the system are analyzed, including equilibria and stability, bifurcation diagrams, Lyapunov exponents and phase diagrams. Strikingly, it can exhibit three-scroll, four-scroll and five-scroll hidden attractors by only changing one system parameter and different shapes of chaotic attractors coexist with the same parameter. Furthermore, the high randomness of the system is verified through 0–1 test and NIST test. By using the high randomness of the system, an image encryption algorithm (IEA) is designed to guarantee the secure and efficient transmission of digital images. This IEA uses whirlpool transformation to scramble pixel positions and DNA computation to diffuse pixel values. The simulation and performance analysis results indicate that the proposed IEA has high security and reliable encryption performance, which in turn confirms the availability of the new memristor-based Chua’s chaotic system.

Dynamic analysis of a novel hyperchaotic system based on STM32 and application in image encryption

This paper presents a novel 4D hyperchaotic system derived from a modified 3D Lorenz chaotic system. A key aspect of this system is the presence of a single equilibrium point, and its stability is carefully analyzed. The dynamic properties, including the Lyapunov exponent spectrum, bifurcation diagram, and chaotic attractors, are investigated using MATLAB simulations. The results reveal that the system displays hyperchaotic behavior across a wide range of the parameter d\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$d$$\\end{document}, with its chaotic attractor transitioning through four states: hyperchaotic, chaotic, periodic, and quasi-periodic, showcasing the system's complex dynamics. Experimental validation using STM32 embedded hardware successfully reproduces these four types of chaotic attractors, confirming the theoretical predictions. The proposed hyperchaotic system is then applied to image encryption, introducing a novel encryption method. The hyperchaotic key sequence generated by this system meets 15 tests of the NIST SP800-22 standard, and further experimental validation with STM32 hardware demonstrates the algorithm's effectiveness, simplicity, non-linearity, and high security. The encrypted images and sequences are rigorously tested key space analysis, histogram similarity analysis, information entropy analysis, statistical attack analysis, differential attack analysis, key sensitivity analysis, and correlation analysis, highlighting the robustness and reliability of the proposed system. This method is versatile and can be extended to various fields, including audio and video encryption, text encryption, IoT security, financial transaction security, and medical data protection.

Fractional-order heterogeneous neuron network based on coupled locally-active memristors and its application in image encryption and hiding

Synaptic crosstalk significantly influences neural firing in the brain. Locally-active memristors can effectively emulate neural network synapses and have a significant importance in neural network research. This paper designs a tristable locally-active memristive model and presents a novel fractional-order (FO) heterogeneous neuron network. This neural network consists of Hindmarsh-Rose (HR) neuron and FitzHugh-Nagumo (FHN) neuron, which are connected by coupling FO locally-active memristors. The research found that changes in the order of different dimensions have a significant effect on the neural network firing through the three-parameter bifurcation diagram. Moreover, it is found that the locally-active memristor as a synapse can affect the coexistence firing behavior of the network. The complex dynamics have been studied numerically by using phase diagrams, Lyapunov exponent spectrum, bifurcation diagram and extreme multistability can be found. In particular, the system can generate a complex bursting behavior in the presence of an external current. In order to verify the accuracy of the simulation, the phase diagram of FO heterogeneous neuron network is implemented by STM32 microcontroller, and results of the experiments are in great agreement with results of the numerical simulations. Finally, an image encryption and hiding method based on FO heterogeneous neuron network and discrete wavelet transform (DWT) is proposed. The experimental results demonstrate that the encryption and hiding scheme has excellent security and strong robustness.

A Four-Dimensional No-Equilibrium Chaotic System with Multi-Scroll Chaotic Hidden Attractors and its Application in Image Encryption

Abstract In recent years, constructing hidden attractors with multi-scroll has become a key discussion point in the research and application fields of chaos science. In this paper, with the existing four-dimensional (4D) chaotic system as the base, a new four-dimensional chaotic system featuring significant characteristics of multi-scroll hidden attractors is constructed by adding a nonlinear function. Comprehensive studies including theoretical analyses and numerical simulations have been carried out on the dynamic properties of the new chaotic system, and all the results show that this system exhibits extremely complex chaotic behaviours and excellent unpredictability, which has great value in image encryption. Therefore, an image encryption scheme based on the new chaotic system is proposed, which cleverly integrates the new scrambling algorithm based on parity coordinate transformation and the new rotational diffusion algorithm. And the effectiveness of this encryption algorithm has been thoroughly analyzed and tested. The results based on the experiments show that this encryption algorithm exhibits significant advantages in performance, which can greatly enhance the security of images during encryption and transmission.

DNA dynamic coding image encryption algorithm with a meminductor chaotic system

With the acceleration of information technology development, the protection of information security becomes increasingly critical. Images, as extensively used multimedia tools, encounter serious challenges in safeguarding sensitive data, including personal privacy and business confidentiality. This research presents a novel algorithm for color image encryption, that combines a meminductor chaotic system and DNA encoding cross-coupling operations to enhance image security and effectively prevent unauthorized access and decryption. Initially, this paper designs an equivalent circuit model for the Meminductor and constructs the corresponding chaotic system, followed by an in-depth analysis of its nonlinear dynamic characteristics. Then, artificial neuron is employed to perturb the original chaotic sequence generated by the system, resulting in a highly random mixed sequence. The original image is then subjected to rearrangement and encoding through Arnold transformation and dynamic DNA encoding techniques. Additionally, this research introduces a DNA encoding cross-coupling operation method that operates at the block level of pixels to diffuse and confuse image data, enhancing the complexity of the image encryption algorithm. Finally, a dynamic decoding technique is employed to decode the encoded image, yielding the encrypted result. Experimental results show that the algorithm is capable of providing larger key space and higher complexity in image encryption applications, and is able to withstand various types of attacks.

Retraction Note: Construction of S-box based on chaotic Boolean functions and its application in image encryption

Retraction Note: Construction of S-box based on chaotic Boolean functions and its application in image encryption

A novel S-box generator using Frobenius automorphism and its applications in image encryption

A novel S-box generator using Frobenius automorphism and its applications in image encryption

S-Boxes design based on the Lu-Chen system and their application in image encryption

S-Boxes design based on the Lu-Chen system and their application in image encryption

Autonomous three-dimensional oscillator with two and four wings attractors embedded in the microcontroller: analysis, amplitude controls, random number generator, and image encryption application

Robust chaotic systems offer unpredictability, complex dynamics, noise-like properties, efficient bifurcation behavior, and the ability to model real-world phenomena, making them valuable in diverse scientific and engineering applications. This paper details on the dynamical appraisal, amplitude controls, microcontroller execution, Random number generator (RNG) of an autonomous three-dimensional (3D) oscillator with two and four wings attractors (ATDOTFWA), and its image encryption application. Thanks to the Routh-Hurwitz criteria, five steady states found in the ATDOTFWA are classified as stable or unstable, depending on its two control parameters. During the numerical simulations employing the Runge–Kutta scheme, the ATDOTFWA exhibit a wide range of dynamic behaviors, including no oscillations, Hopf bifurcation, limit cycle, five distinct presentations of two wings chaotic structures, monostable and bistable two wings chaotic structures, bistable and monostable regular oscillations, chaotic bursting characteristics, coexistence of period-2-oscillations and four wings chaotic structure, and four wings chaotic attractor which were validated experimentally by the microcontroller implementation. The total and partial controls of the amplitude are achieved in the ATDOTFWA. A RNG is designed based on the ATDOTFWA, and the generated random numbers are successfully tested using the ENT and NIST 800–22 statistical test suites, demonstrating the reliability of the ATDOTFWA-based RNG. This reliability is further confirmed through the application of the ATDOTFWA-based RNG in an efficient and secure image encryption process, where the generated random numbers are used as the encryption key. The effectiveness of the image encryption process is validated through comprehensive cryptanalysis, with an encryption time of 0.1923 s for a 512×512 image, an average normalized pixel change rate (NPCR) of 99.6126%, an average unified average changing intensity (UACI) of 33.4578%, and an average information entropy of 7.9994.

Retraction Note: A novel construction of substitution box for image encryption applications with Gingerbreadman chaotic map and S8 permutation

Retraction Note: A novel construction of substitution box for image encryption applications with Gingerbreadman chaotic map and S8 permutation

Generating grid double-scroll attractors from magnetized SC-CNN and its application in image encryption

Cellular neural network has attracted widespread attention due to its easy hardware implementation and general application in information processing. In this paper, a new memristive State-Controlled-CNN (MSC-CNN) model is established by introducing two novel flux-controlled memristors into a three-cell network, where one of which simulates the electromagnetic radiation and the other characterizes the coupling weight. The present MSC-CNN can generate multi-double-scroll attractors (MDSAs) in one direction or grid multi-double-scroll attractors (GMDSAs). Stability analysis shows that each asymptotically stable equilibrium point of the memristors serves as index-1 saddle-focus in the MSC-CNN, which induces the corresponding connecting bond orbits between two scrolls. Thus, the number of GMDSAs can be flexibly adjusted by varying the number of the asymptotically stable equilibrium points of the memristors. Moreover, the memristive coupling strength also controls the number of MDSAs. Through numerical simulations, complex dynamic behaviors such as extreme multistability and amplitude control are also observed. Then, an image encryption scheme based on the proposed MSC-CNN is designed from the application perspective. Finally, a microcontroller-based hardware system is implemented to verify the effectiveness of numerical simulations.

Constructing Multiscroll Memristive Neural Network With Local Activity Memristor and Application in Image Encryption.

Memristor possesses synapse-like properties that can mimic excitation and inhibition between neurons. This article introduces the Sigmoid functions to the memristor and constructs a new memristive Hopfield neural network (HNN). Its most distinctive feature is the simple topology, which contains only unidirectional connections in neurons. The equilibrium points analysis reveals the mechanism of its multiscroll attractors generation. Homogeneous and heterogeneous coexisting attractors are observed with the variation of the network parameters. Note that the state equation of memristor can affect the number of coexisting attractors. A hardware implementation is designed for it, and the multiscroll attractors are captured in the oscilloscope. Finally, it is also applied to developing an image encryption algorithm with excellent performance.

A variable-order fractional memristor neural network: Secure image encryption and synchronization via a smooth and robust control approach

In this research, we introduce and investigate a variable-order fractional memristor neural network, focusing on its engineering applications in synchronization and image encryption. This study stands out as a pioneering effort in proposing such an architecture for image encryption purposes. Distinct from conventional fractional-order systems, our model incorporates a time-varying fractional derivative, leading to more complex behaviors. Through numerical simulations, we vividly demonstrate the chaotic dynamics of the system. Our results further reveal the system's outstanding performance in image encryption applications. To augment the system's efficiency, we introduce a robust control strategy that guarantees smooth stabilization and synchronization of the variable-order fractional system. Considering the unique variable-order fractional nature of the system, we provide theoretical validations and empirical evidence supporting its stability and convergence properties. Additionally, we present synchronization outcomes between pairs of such neural networks employing our robust control approach. Our numerical analyses firmly substantiate the superiority of our control strategy, particularly highlighting its precision, robustness, and ability to maintain chattering-free performance under external disturbances.

A new four-dimensional memristive system, synchronization and its application in image encryption

A new four-dimensional memristive system, synchronization and its application in image encryption

Hyperchaotic color image encryption scheme based on simultaneous color channel confusion-diffusion operations

Shortcomings have been identified in current color image encryption methods. Firstly, these methods encrypt each color channel separately, resulting in a time-consuming process and independent encrypted channels, which can make hacking easier. Secondly, the use of XOR operations between image pixel values and code values during encryption can be vulnerable. To address these issues, a novel algorithm is introduced that incorporates a new XOR operation and simultaneous encryption of color channels. This approach creates interdependence between the encrypted channels, reduces encryption time, and enhances security by introducing a more complex XOR operation. The proposed method employs a substitution technique that involves XOR operations between groups of pixels and codes, inspired by the principles of the fast Walsh-Hadamard transform algorithm. The encryption process involves several key phases that enhance the security and efficiency of the system. In the initial phase, line processing involves mixing lines from different channels and application of chaotic substitution permutation operations. Subsequently, a similar operation is applied to columns, and finally, the channels are divided into overlapping squared sub-blocks, with a newly XOR proposed chaos-based confusion operation simultaneously applied to the three-channel sub-blocks. These phases are designed to ensure interdependence between color channels and reduce encryption time, resulting in a more robust encryption method. With this method, the RGB cipher channels become mutually dependent, rendering decryption of one channel impossible without the others. The approach has been evaluated using appropriate metrics and found to be robust, efficient, and resistant to various attacks, outperforming recently published methods. It is suitable for modern image encryption applications, including those related to the Internet of Medical Things (IoMT).