Application In Image Encryption Research Articles

A novel coupled functional neuron model and its application in medical image encryption

A novel coupled functional neuron model and its application in medical image encryption

New 4D hyperchaotic system’s application in image encryption

In order to protect sensitive information from unauthorized access and illegal copy during network transmission, storage and processing, we propose a new four-dimensional hyperchaotic system (4DHS) and apply it to encryption algorithm. Firstly, the dynamical properties of 4DHS are analyzed according to the structure, and the chaotic properties are verified by dissipation, equilibrium point and lyapunov exponent. Secondly, the chaotic sequence combined with Arnold scrambling method is adopted to scramble the pixel values of the plaintext image, and the scrambled pixel matrix is diffused into the ciphertext image matrix by XOR operation. Finally, we conduct the experiments to validate the effectiveness of the proposed encryption algorithm and achieve satisfactory results. At the same time, we compare the proposed encryption algorithm with other encryption algorithms, and the excellent encryption effect of our encryption algorithm can be proved.

Molding robust S-box design based on linear fractional transformation and multilayer Perceptron: Applications to multimedia security

This study introduces a novel and refined approach for generating exceptionally efficient S-boxes. The proposed methodology employs a hybrid approach that combines linear fractional transformation (LFT) with a multilayer perceptron (MLP) architecture. This method makes use of a perceptron with three layers: input, hidden, and output. Each layer's neuron count is fine-tuned to conform to the S-box layout. In addition, a threshold nonlinear transformation is utilized to increase nonlinearity, and a novel algorithm for boosting nonlinearity is introduced. The utilization of both LFT and MLP approaches has led to the development of S-boxes that possess nearly ideal average nonlinearity values, surpassing those that have been presented in literature. Notably, one S-box achieved an exceptional nonlinearity score of 114.50. Furthermore, to demonstrate how well the S-box works, this study also employs it in an image encryption application.

Analysis of a time-dependent memristor-based chaotic system and its application in image encryption

Abstract Compared with ordinary chaotic systems, memristor-based chaotic systems have more complex dynamic behaviors and are more suitable for image encryption algorithms. In this paper, a four-dimensional chaotic system is constructed by introducing a cubic nonlinear memristor into a three-dimensional chaotic system. Firstly, the dynamic characteristics of the constructed memristor-based chaotic system are analyzed in detail, and the simulation results show that the system has different attractors with different topological structures at different simulation times. Within a fixed simulation time, the system has 15 attractors with different topological structures under different parameter values, and there is a phenomenon of multiple stability in the system, indicating high complexity. Based on the above discoveries, a color image encryption algorithm including scrambling and diffusion is designed. Experimental results show that this algorithm can perfectly hide the information of the plaintext image, and the decrypted image is consistent with the plaintext image. Finally, the security of the algorithm is analyzed by using key space and so on. The analysis results indicate that the encryption algorithm designed in this paper can effectively resist external attacks and has high security.

Real time hybrid medical image encryption algorithm combining memristor-based chaos with DNA coding

Image encryption is a commonly used method to secure medical data on a public network, playing a crucial role in the healthcare industry. Because of their complex dynamics, memristors are often used in developing novel chaotic systems that can improve the efficiency of encryption algorithms based on chaos. In this work, we propose a novel locally active memristor-based chaotic circuit model and present a real time hybrid image encryption application developed on a PYNQ-Z1 (Python Productivity for Zynq) low-cost FPGA board using Jupiter programming environment. The proposed hybrid algorithm combines memristor-based chaos with a DNA (deoxyribonucleic acid) encryption algorithm exploiting diffusion-confusion technique. We initially present a new compact and inductorless chaotic circuit, derive the model equations, and then verify its chaotic dynamics numerically through the investigation of the phase portraits, Lyapunov exponents and the bifurcation diagrams. We further implement the chaotic circuit experimentally with discrete elements. The randomness of the chaotic sequence is improved using Trivium and von Neumann post-processor algorithms and assessed through the NIST tests. Finally, the performance of the encryption algorithm is evaluated through various metrics, including histogram and correlation analyses, differential attack, information entropy, as well as data-loss and noise attack, demonstrating its security and suitability for real-time encryption systems.

Drive–response asymptotic shape synchronization for a class of two-dimensional chaotic systems and its application in image encryption

This paper proposes the concept of drive–response asymptotic shape synchronization for two-dimensional chaotic systems and its application in image encryption. It overcomes the limitations of traditional shape synchronization, eliminates the restrictions on the drive system’s continuous differentiability, and the response system’s specific format, while simplifying the controller design, thereby demonstrating enhanced applicability and ease of implementation. Moreover, based on the characteristics of asymptotic shape synchronization, we propose a novel image encryption scheme. In this scheme, the drive and response systems, initialized with distinct values, achieve identical chaotic attractors through rotation and translation parameters in rigid transformation, which are utilized for encryption and decryption processes, respectively. Our encryption algorithm employs DNA coding to construct a DNA plane and incorporates the concept of Rubik’s cube rotations for scrambling and diffusion. Experimental simulations and performance analysis verify the effectiveness of the proposed encryption scheme in withstanding various attacks, ensuring a high level of security.

S-box design based on logistic skewed chaotic map and modified Rabin-Karp algorithm: applications to multimedia security

A substitution box (S-box) serves as the nonlinearity component in a symmetric key encryption scheme; it directly determines the performance and security level of ciphers. Thus, the construction of an S-box with superior performance and efficiency, specifically in terms of high cryptographic properties, is critical. This research proposes a novel method to construct the S-box using the skewed logistic chaotic map and modified Rabin-Karp rolling hash function without disturbing its mathematical structure. First, iterate the skewed logistic map by selecting a seed value and specifying the parameters to generate the chaotic values. The map’s sensitivity to initial conditions and parameters results in a seemingly random and unpredictable chaotic values. Second, hash the chaotic values using Rabin-Karp for generating sequences of numbers within a specific range (0–255 for an 8-bit S-box). Then an S-box is constructed using the hash values. Performance evaluations indicate that the S-box produced through our suggested approach exhibits superior performance, demonstrating robust resistance against various security threats, including but not limited to linear attacks, differential attacks, and others. To demonstrate the effectiveness of the constructed S-box, this paper goes on to employ it in an image encryption application. Security analyses reveal that the developed image encryption algorithm successfully encrypts diverse types of images, producing cipher images characterized by uniformly distributed histograms. Performance assessments illustrate its high-security level, surpassing several state-of-the-art encryption algorithms.

A new approach based on artificial neural networks and chaos for designing deterministic random number generator and its application in image encryption

A new approach based on artificial neural networks and chaos for designing deterministic random number generator and its application in image encryption

Event-triggered passivity and synchronization of multiple derivative coupled reaction–diffusion neural networks

The paper studies the event-triggered passivity and synchronization problems for multiple derivative coupled reaction–diffusion neural networks. Two types of multiple derivative coupled reaction–diffusion neural networks, with and without time-varying delay, are considered. According to the characteristics of multiple derivative coupled reaction–diffusion neural networks, an event-triggered condition is constructed. By imposing appropriate Lyapunov functionals and inequality techniques, several passivity conditions are established for these two networks under the designed event-triggered controllers. Then, synchronization criteria of these two networks are derived based on the relationship between output-strict passivity and synchronization. Moreover, the non-occurrence of the Zeno behavior in the proposed control is proved. Numerical example is illustrated to verify the effectiveness of the proposed criteria. Finally, theoretical results and the associated image encryption application are validated through numerical simulations and statistical analyses.

Stability and complexity evaluation of attractors in a controllable piezoelectric Fitzhugh-Nagumo circuit

Chaotic systems have potential applications in secure communication and image encryption. The FitzHugh-Nagumo (FHN) neuron circuit model, as one of the most important models for neuron modelling, has a good chaotic discharge mode. On this basis, a controllable FHN piezoelectric neuron circuit is designed in this paper. By adjusting the state of the switch on or off, the circuit model can produce three different operating modes. The results show that the dynamic state of the system is determined by external stimuli, internal parameters of the system, and the number and nature of the external driving sources. More drivers can provide more chaos parameters. By converting different working modes, we can generate chaotic sequences with high randomness under different parameters. We found that when multiple drivers work together, the system output is more complex, and there is competition between dynamics induced by different drivers in the system. The addition of chaotic current makes the output discharge of the system produce chaotic resonance and pseudo-chaotic mode, which greatly improves the complexity of the sequence. This provides a new method for generating chaotic sequences with high randomness. Our work lays a theoretical foundation for the optimization of chaotic encryption algorithms in the future. In the future, we will further explore the effects of chaotic current stimulation with different properties. We hope that these findings will provide new insights into the security of information communications.

A new three-dimensional memristor chaotic circuit design and its application in image encryption

A new three-dimensional memristor chaotic circuit design and its application in image encryption

Multiple-image encryption scheme based on a new 2D hyperchaotic map with blurred pixels

It is known that chaotic, especially hyperchaotic system can be suitable for the application in image encryption owing to itself characteristics. While currently, certain improved chaotic or hyperchaotic systems are confronted with the security issue of encryption due to their less complex dynamical behaviors. To address the problem well, we introduce a novel two-dimensional (2D) crossed hyperchaotic map which is based on the logistic map and the infinite collapse map. The analysis of phase diagram and Lyapunov exponential spectrum demonstrate that the given system can exhibit extensive hyperchaotic behavior and good traversal properties. Moreover, the growing use of digital images has prompted demand for multi-image encryption scheme. For this reason, based on the given 2D crossed hyperchaotic map, a multiple image encryption (MIE) scheme that employs a cross-plane with the operation of simultaneous permutation and diffusion to modify the values of its positions and pixels across multiple images is proposed. A pixel blur preprocessing technique is introduced such that the efficiency of key calculation and the speed and safety of information encryption are greatly improved. Eventually, some simulation examples and security analysis reveal that the put forward encryption scheme is able to keep out kinds of attacks such as the selective plaintext attacks and data loss.

Generation multi-scroll chaotic attractors using composite sine function and its application in image encryption

In this paper, a composite sine function is proposed and applied in a chaotic system, which is capable of generating definite number of chaotic attractors. The proposed composite sine function possesses infinite breakpoints, but it can produce a fixed number of scrolls by adjusting its parameters. Compared to other chaotic systems with multiple scrolls chaotic attractors, the realization circuit of the chaotic system with compound sine function allows obtaining different numbers of scrolls by adjusting only one resistance value. As a result, the circuit structure remains unchanged despite variations in the number of scrolls. Various analytical methods are applied to study the dynamical behaviors of the proposed chaotic system, including Lyapunov exponent, equilibrium point, bifurcation diagram, phase diagram, spectral entropy and C0-algorithm. Furthermore, based on the analysis of dynamical characteristics, the electronic circuits of the proposed system are given on Multisim circuit simulation software, and the multi-scroll chaotic attractors exhibit consistency with the numerical simulation results. Finally, we incorporated the proposed chaotic system into a Deoxyribonucleic acid coding algorithm for image encryption, and this method exhibits excellent encryption efficiency and high level of security.

CCM-PRNG: Pseudo-random bit generator based on cross-over chaotic map and its application in image encryption

CCM-PRNG: Pseudo-random bit generator based on cross-over chaotic map and its application in image encryption

Complex hidden dynamics in a memristive map with delta connection and its application in image encryption

Complex hidden dynamics in a memristive map with delta connection and its application in image encryption

Dynamic behavior of small system under the influence of parameters and application of image encryption

Dynamic behavior of small system under the influence of parameters and application of image encryption

Fixed/predefined-time projective synchronization for a class of fuzzy inertial discontinuous neural networks with distributed delays

In this article, fixed-time projective synchronization (FTPS) and predefined-time projective synchronization (PTPS) for a class of discontinuous fuzzy inertial neural networks (FINNs) with distributed delays are considered. To this end, regarding differential inclusion theories and the Lyapunov stability method, more precise and improved setting times of FTPS are systematically constructed. Furthermore, a more general and novel predefined-time stability lemma is established to make the synchronized time more flexible and can be an accurate value in advance. Meanwhile, some effective feedback controllers and new criteria are established to guarantee the proposed FINNs achieve FTPS and PTPS, respectively. Finally, the corresponding numerical simulations and image encryption application are offered to confirm the obtained results.

A tri-valued memristive chaotic system with hidden attractors and its image encryption application

A tri-valued memristive chaotic system with hidden attractors and its image encryption application

A Memristive Fully Connect Neural Network and Application of Medical Image Encryption Based on Central Diffusion Algorithm

A Memristive Fully Connect Neural Network and Application of Medical Image Encryption Based on Central Diffusion Algorithm

A 5-D memristive hyperchaotic system with extreme multistability and its application in image encryption

By coupling memristors to nonlinear circuits, more complex dynamical behaviors can be induced. However, to date, there has been insufficient attention given to high-dimensional chaotic systems based on memristors. In this paper, a magnetic-controlled memristor is combined with a three-dimensional chaotic system, resulting in a five-dimensional memristive chaotic system. Through dynamic analysis and numerical simulations, the chaotic nature of the system is elucidated based on fundamental system behaviors, including Lyapunov dimension, dissipativity, stability of equilibrium points, 0–1 test, and Poincaré mapping. During the complex dynamical analysis of this system, unique dynamical behaviors are discovered, including intermittent chaos, transient chaos, extreme multistability, and offset-boosting. Moreover, the consistency between numerical calculations and the physical implementation of the actual system is verified through equivalent circuit design. Finally, this system is applied to image encryption, leading to the design of an efficient and secure hyper-chaotic image encryption algorithm, whose effectiveness is confirmed through several security tests.