Chaotic Sequences Research Articles

A novel simultaneous permutation–diffusion image encryption scheme based on a discrete space map

The constant increase of devices connected to the internet and the development and spread of technologies such as 5G leads to substantial growth in data-sharing over non-secure channels in real-time applications, augmenting the need for fast cryptography algorithms. Algorithms such as the Advanced Encryption Standard (AES) are not optimized for image encryption, and hence, as an alternative, chaotic encryption strategies have been explored by researchers. However, due to the use of floating-point arithmetic and inefficient memory access, the performance of these chaotic ciphers is insufficient for the encryption of high-resolution images. Thus, this work proposes generating the chaotic sequences based on fixed-point arithmetic to increase computational efficiency, and using a simultaneous permutation–diffusion operation and block encryption to deal with the inefficient memory access. The proposed scheme leads to a throughput 353 times higher than the AES, 75 times higher than the previously higher value in the literature and 11 times higher than the Ascon algorithm. The cipher security evaluation is performed based on statistical attacks, with metrics such as Pearson, histogram variance, Shannon’s entropy, correlation coefficients, and NIST tests; differential attacks, with the NPCR, UACI, and MSE metrics; chosen plain-text, with the SSIM metric; brute-force, with the key-space; noise and occlusion attacks, with the PSNR metric.

Color image encryption algorithm based on Double layer Josephus scramble and laser chaotic system

In this paper, a color image encryption algorithm is presented, the new algorithm uses double-layer Joseph’s scramble, XOR diffusion, and is built on a laser chaos system. Firstly, a laser chaotic system is chosen in the scheme and it has the advantages of extended bandwidth and rapid propagation speed. Secondly, the structure of the image encryption scheme follows the Fridrich structure. In the scrambling part, a modified Joseph’s ring is adapted to process the chaotic sequence and the picture pixel sequence to achieve the scrambling of the plaintext image pixel positions. In the diffusion part, the XOR diffusion technique is employed to reduce the statistical characteristics of the plaintext picture, which can resist external attacks better. Finally, the presented encryption algorithm is demonstrated utilizing simulation results and security analysis. The simulation performance demonstrates that the new proposed method is practical. The security test performance indicates that the algorithm can validly encrypt the image with good security performance. In summary, the new scheme designed in this paper can offer better technical backing for the wide applications of image encryption.

Color image encryption algorithm based on bidirectional spiral transformation and DNA coding

The security of digital images has become increasingly important as information technology has advanced considerably. To ensure image security and improve the efficiency of image encryption, a novel color image encryption algorithm is proposed in this paper. Firstly, a novel three-dimensional chaotic system with extreme multistability is proposed and employed to generate the chaotic sequences to be used in the permutation and diffusion processes. Secondly, the proposed bidirectional spiral transformation is used to permute the R, G and B components extracted from the color plain image. Thirdly, the permuted pixel sequence is dynamically encoded into a DNA sequence. To further increase the permutation effect, the DNA sequence is permuted again using the index sequence. Finally, the dynamical DNA operations are performed to diffuse the permuted DNA sequence, and the designed look-up table method is used to quickly obtain the DNA operation results. The key space of the proposed algorithm is 10266, which is large enough to resist the brute-force attacks. The average entropy value of the cipher image of Peppers is 7.9971, which is much closer to the theoretical entropy value 8. The dynamic DNA operations process only takes up 0.032349s, which shows the advantage of the proposed look-up table method. Therefore, the proposed algorithm can be applied to the application that require high confidentiality and real-time.

A Review in Use of 4D Hyper chaotic Systems and DNA for Image Encryption

Recently, the color image encryption technique using the chaotic system and DNA bases hasattracted great interest from the research community.The current research presents a study in an efficient methodfor color image encryption by using Hyper-chaotic Lorenz system with Hyper-chaotic Rösler system and DNAcoding. Where the Secure Hashing Algorithm-256/384 was presented first, due to the need for chaotic systems tohave initial values (primary key), which are obtained using this hashing function.Then the study presented the useof Hyper-chaotic Lorenz system and its chaotic sequences generated, as it turns the normal color image into adistorted image. By mixing the three components (red, green and blue) of the color image. Finally, the use of acombination of methods to encode mixed components is shown to achieve significant randomness, Hyper-chaoticRösler system is shown as well as XOR operations are applied between image DNA components and DNAsequences that are generated on the basis of Hyper-chaotic Rösler system. then decode the DNA components of theimage; Thus, the final encoded image is generated. The use of these methods of encryption is more efficient whencompared to the previous many color image encryption algorithms, as these methods are safer for attacks, and thiswas proven by studying the histogram (graph) in addition to the use of DNA and its characteristics, the mostimportant of which is DNA encryption additional technique. It has characteristics, such as wide parallelism andlarge storage capacity, which make it a very promising field and thus use DNA and messy functions will provideimage protection in an efficient way. Messy maps and DNA technology are two of the most popular topicscurrently used in image coding, in combination or separately. These two technologies have good security featuresand can be used to secure digital images. Chaotic systems' sensitive initial conditions, unpredictable and nonperiodic ideal statistics, and other attributes enable them to build secure cryptographic systems. Numerousbeneficial properties of computational parallel DNA computing have been discovered on a large scale, less powerloss, and a large amount of storage space. This is what this study sought to find an encryption technology thatmaintains a high level of strength against encryption attacks

Non-Linear Analysis of Novel Equivalent Circuits of Single-Diode Solar Cell Models with Voltage-Dependent Resistance

The most commonly used model of solar cells is the single-diode model, with five unknown parameters. First, this paper proposes three variants of the single-diode model, which imply the voltage dependence of the series resistance, parallel resistance, and both resistors. Second, analytical relationships between the current and the voltage expressed were derived using the Lambert W function for each proposed model. Third, the paper presents a hybrid algorithm, Chaotic Snake Optimization (Chaotic SO), combining chaotic sequences with the snake optimization algorithm. The application of the proposed models and algorithm was justified on two well-known solar photovoltaic (PV) cells—RTC France solar cell and Photowatt-PWP201 module. The results showed that the root-mean-square-error (RMSE) values calculated by applying the proposed equivalent circuit with voltage dependence of both resistors are reduced by 20% for the RTC France solar cell and 40% for the Photowatt-PWP201 module compared to the standard single-diode equivalent circuit. Finally, an experimental investigation was conducted into the applicability of the proposed models to a solar laboratory module, and the results obtained proved the relevance and effectiveness of the proposed models.

High-security constellation shaped self-homodyne coherent system with 4-D joint encryption.

In recent years, the self-homodyne coherent (SHC) system and the constellation shaping (CS) technique have drawn considerable attention due to their abilities to further improve the transmission capacity for various scenarios. From the security point of view, the CS technique and the SHC infrastructure also provide new dimensions for encryption. We propose a high-security and reliable SHC system based on the CS technique and the digital chaos. With a four-dimensional hyperchaotic system, chaotic sequences are generated and used for the exclusive or operation, chaotic constant composition distribution matching, phase disturbance, and optical-layer time-delay disturbance. Moreover, 64-ary circular quadrature amplitude modulation (64CQAM) format is adopted for transmission due to its advantages of sensitivity to phase noise, immunity to conventional digital signal processing, and ability of time-mismatch masking, which is verified by simulation in a SHC system. Last, we conduct an experimental verification in a 20GBaud probabilistically shaped 64CQAM SHC system. Consequently, with a large-linewidth laser source, optical-layer security can be protected by time mismatches of tens of picoseconds. And the digital-layer security is protected by an enormous key space of 10127. The proposed scheme can provide reliable real-time encryption for the optical fiber transmission, serving as a potential candidate for the future high-capacity inter/intra-datacenter security interconnect.

An Image-Encipherment Algorithm Using a Combination of a One-Dimensional Chaotic Map and a Three-Dimensional Piecewise Chaotic Map

One-dimensional and three-dimensional piecewise chaotic maps are used to propose an image-encipher technique in this article. First, the logistic map is used to construct the pseudo-random sequence. After that, this sequence is used to scramble the plain image. Next, the three-dimensional piecewise chaotic map has produced a mask of the chaotic sequence. After doing some preprocessing steps on the mask, a bit-wise XOR operation with the mask is applied to the shuffled image. The suggested algorithm is used to encipher and decipher a different range of images. To check the algorithm security and efficiency, the algorithm performance was calculated using multiple statistical tests and compared to several recent algorithms. Furthermore, numerical simulations and experimental data are also used to validate the proposed algorithm’s resistance to various attacks.

A chaotic PRNG tested with the heuristic Differential Evolution

A pseudo random number generator (PRNG) is built with a chaotic map without fixed points implemented using fixed-point arithmetic. The generated binary sequences by the PRNG pass all the TestU01 statistical tests to prove the randomness of the generated binary sequences. Three multimodal benchmark functions are optimized with the heuristic Differential Evolution (DE) using the proposed PRNG, and these are compared with the DE using the standard random function available in the C programming language. If the shuffling technique is added to the generated chaotic random sequences, both approaches give the same statistically solutions. A hardware design in FPGA of the PRNG also is shown.

Fully fixed-point integrated digital circuit design of discrete memristive systems

In this paper, the fully fixed-point digital integrated circuits of discrete memristive systems are designed with very low circuit area cost, where the two-stage pipeline and multi-cycle architecture is employed. Firstly, the mathematical models of the discrete memristor and a memristor chaotic map are presented and dynamics are analyzed. Secondly, data flow design is carried out and the feasibility of the fixed-point model is discussed, which provides a foundation for the further circuit design. Thirdly, different architectures are designed and we get the optimal results. As a result, gate area of the discrete memristor is 40288 μm2 and the equivalent gate counts are 4588, while gate area of the discrete memristor map is 40424 μm2 and the equivalent gate counts are 4604. Moreover, a chaotic pseudo random sequence generator is designed and the NIST test is passed. It provides the foundation for the further applications of the discrete memristor and discrete memristor chaotic systems.

Automatic Segmentation of Psoriasis Skin Images Using Adaptive Chimp Optimization Algorithm-Based CNN.

Psoriasis is a severe skin disease that is surveyed outwardly by dermatologists. In recent years, computer vision is the major solution for diagnosing the psoriasis skin disease by segmenting the infected skin images. Besides, many researchers had presented efficient machine learning techniques for segmenting the psoriasis skin images. Nevertheless, accuracy and time consumption of the model are further to be improved. Thus, in this work, we present adaptive chimp optimization algorithm (AChOA)-based convolutional neural network (CNN) which is introduced for automatic segmentation of psoriasis skin images. After pre-processing, the input images are segmented using AChOA-CNN model where weight and bias values of CNN are optimized with the AChOA. The search ability of ChOA is enhanced by adapting the chaotic sequence based on tent map. At final, from the segmented output images, artifacts are removed by applying the threshold module. From the simulation, we attain 97% of accuracy.

A data encryption technology for serial communication of multi degree of freedom manipulator based on chaotic sequence

In order to effectively improve the security of serial communication data encryption of manipulator and shorten the encryption time, a multi degree of freedom serial communication data encryption technology of manipulator based on chaotic sequence is proposed. The serial communication data of the manipulator is obtained by using the logistic chaotic map, and the chaotic sequence of the communication data is generated. Based on the binary sequence generated by the logistic chaotic map, the serial communication data encryption key of each wheel is generated. The serial communication data obtained is forward XOR or reverse XOR with the sub key to realise the serial communication data encryption of the mechanical arm. The experimental results show that the maximum value of the cross-correlation function of the proposed method is closer to 0, and the data encryption time is only 15.2 s, which effectively improves the security of data encryption.

A novel approach to secure biometric data using integer wavelet transform, chaotic sequences and improved logistic system-based watermarking

A novel approach to secure biometric data using integer wavelet transform, chaotic sequences and improved logistic system-based watermarking

A novel approach to secure biometric data using integer wavelet transform, chaotic sequences and improved logistic system-based watermarking

A novel approach to secure biometric data using integer wavelet transform, chaotic sequences and improved logistic system-based watermarking

An Algorithm Based on Hodgkin-Huxley Model and Latin Square for Image Encryption

Image transmission is happening more frequently in this era of technologically sophisticated digital information. Additionally, more individuals are becoming aware of its importance. In order to secure images, many academics are participating in research, which is advantageous for guaranteeing data security. In order to strengthen the security of images during transmission, we have investigated new encryption algorithms to guarantee this. First, a current representing the Lorenz chaotic system is introduced into the neuron model. The neuron model generates sequences after receiving the current signal. The next move is made as the current shifts based on whether the sequence that results is chaotic or not. If so, the subsequent operation is carried out; otherwise, the current is altered until chaotic sequences are produced. Second, a global scrambling with de-duplication technique is used to scramble the image using the resulting chaotic sequence. To complete the dislocation effect, the Latin square is used to dislocate the image after the initial dislocation. Fourth, the image that has been scrambled is subjected to two rounds of additive mode diffusion. They are diffusion in the forward additive mode and diffusion in the inverse additive mode. Lastly, to improve the diffusion effect, the image is diffused in the finite domain. Eventually, the encrypted image is obtained. After evaluation tests and comparison with related literature, it can be found that the algorithm of this study has certain advantages. Also, the resistance to attack is good. It can protect the security of the image.

VLSI Implementation of Optimized 2D SIMM Chaotic Map for Image Encryption

The current research work proposed a novel optimization-based 2D-SIMM (Two-Dimensional Sine Iterative chaotic map with infinite collapse Modulation Map) model for image encryption. The proposed 2D-SIMM model is derived out of sine map and Iterative Chaotic Map with Infinite Collapse (ICMIC). In this technique, scrambling effect is achieved with the help of Chaotic Shift Transform (CST). Chaotic Shift Transform is used to change the value of pixels in the input image while the substituted value is cyclically shifted according to the chaotic sequence generated by 2D-SIMM model. These chaotic sequences, generated using 2D-SIMM model, are sensitive to initial conditions. In the proposed algorithm, these initial conditions are optimized using JAYA optimization algorithm. Correlation coefficient and entropy are considered as fitness functions in this study to evaluate the best solution for initial conditions. The simulation results clearly shows that the proposed algorithm achieved a better performance over existing algorithms. In addition, the VLSI implementation of the proposed algorithm was also carried out using Xilinx system generator. With optimization, the correlation coefficient was −0.014096 and without optimization, it was 0.002585.

Construction and Optimization of Dynamic S-Boxes Based on Gaussian Distribution

Block ciphers are widely used for securing data and are known for their resistance to various types of attacks. The strength of a block cipher against these attacks often depends on the S-boxes used in the cipher. There are many chaotic map-based techniques in the literature for constructing the dynamic S-Boxes. While chaos-based approaches have certain attractive properties for this purpose, they also have some inherent weaknesses, including finite precision effect, dynamical degradation of chaotic systems, non-uniform distribution, discontinuity in chaotic sequences. These weaknesses can limit the effectiveness of chaotic map-based substitution boxes. In this paper, we propose an innovative approach for constructing dynamic S-boxes using Gaussian distribution-based pseudo-random sequences. The proposed technique overcomes the weaknesses of existing chaos-based S-box techniques by leveraging the strength of pseudo-randomness sequences. However, one of the main drawbacks of using Gaussian distribution-based pseudo-random sequences is the low nonlinearity of the resulting S-boxes. To address this limitation, we introduce the use of genetic algorithms (GA) to optimize the nonlinearity of Gaussian distribution-based S-boxes while preserving a high level of randomness. The proposed technique is evaluated using standard S-box performance criteria, including nonlinearity, bit independence criterion (BIC), linear approximation probability (LP), strict avalanche criterion (SAC), and differential approximation probability (DP). Results demonstrate that the proposed technique achieves a maximum nonlinearity of 112, which is comparable to the ASE algorithm.

A Color Image Encryption Scheme Based on Singular Values and Chaos

The security of digital images transmitted via the Internet or other public media is of the utmost importance. Image encryption is a method of keeping an image secure while it travels across a non-secure communication medium where it could be intercepted by unauthorized entities. This study provides an approach to color image encryption that could find practical use in various contexts. The proposed method, which combines four chaotic systems, employs singular value decomposition and a chaotic sequence, making it both secure and compression-friendly. The unified average change intensity, the number of pixels’ change rate, information entropy analysis, correlation coefficient analysis, compression friendliness, and security against brute force, statistical analysis and differential attacks are all used to evaluate the algorithm’s performance. Following a thorough investigation of the experimental data, it is concluded that the proposed image encryption approach is secure against a wide range of attacks and provides superior compression friendliness when compared to chaos-based alternatives.

Chaotic Image Encryption Using Piecewise-Logistic-Sine Map

The classical one-dimension chaotic maps are not adequately secure, and some improved maps usually have a high time complexity. To address these problems, this paper presents a new Piecewise-Logistic-Sine map (PLSM). The bifurcation diagrams, Lyapunov exponent, and running time of the proposed PLSM are analyzed, and the outcomes show that it has better chaotic behavior with low time complexity. Furthermore, diffusion by certain rules is vulnerable to attack, so a PLSM-based image encryption scheme with random exclusive OR diffusion is proposed. Using a 256-bit secret key, the initial value and parameters of PLSM are calculated by the key distribution method. Then four chaotic sequences are generated by PLSM, they are used in three rounds of random exclusive OR diffusion. This scheme can spread a small change in the original image to all pixels, and the performance evaluation shows the security of this image encryption scheme.

Graded Optimization of Upper Limb Exoskeleton Parts for Grid Operations

Upper limb exoskeleton is gradually used in industrial production because of its flexibility, safety, and ease of wear. To improve the load reduction effect of the upper limb exoskeleton in power grid operation, this paper first establishes an efficiency optimization model considering the number of gears, transmission ratio, and pressure angle of upper limb exoskeleton transmission joint gears. Further, an exoskeleton load reduction model based on the joint optimization of multiple parameters of the upper limb exoskeleton is constructed by combining the muscle force application fatigue evaluation. For the above model, a hybrid simulated annealing-flash connection process algorithm based on Cubic mapping and golden sine is designed for the solution. To address the shortcomings of the standard LAPO, Cubic mapping, simulated annealing algorithm, and golden sine operator are introduced for improvement, producing high-quality initial solutions through the traversal of Cubic chaotic sequences, hybrid simulated annealing algorithm to enhance the global search capability of the algorithm, and further incorporating golden sine operator to strengthen the local search capability of the algorithm. In the simulation section, the designed Improved Lightning Connection Process Algorithm (ILAPO) is compared horizontally with cutting-edge swarm intelligence algorithms such as LAPO, PSO, and HBA to verify the feasibility of the model in this paper in the exoskeleton domain and the efficiency of the designed algorithm.

Parameter Estimation of Fractional-Order Chaotic Power System Based on Lens Imaging Learning Strategy State Transition Algorithm

Parameter identification of fractional-order chaotic power systems is a multidimensional optimization problem that plays a decisive role in the synchronization and control of fractional-order chaotic power systems. In this paper, a state transition algorithm based on the lens imaging learning strategy is proposed for parameter identification of fractional-order chaotic power systems. Taking a fractional-order six-dimensional chaotic power system mathematical model as an example, the mathematical model and chaotic state are analyzed. First, the Tent chaotic mapping is used to initialize the population, thus increasing population diversity. The randomness and ergodicity of the Tent chaotic sequence are used to enhance the global searching ability of the algorithm. Second, a maturity index is employed to determine population maturity. The lens imaging learning strategy is used to suppress the premature convergence of the state transition algorithm effectively and help the population jump out of local optima. Finally, the improved state transition algorithm is used to identify the parameters of the fractional-order six-dimensional chaotic power system model. The proposed improved state transition algorithm shows high estimation accuracy and convergence speed, and is superior to the traditional state transition and particle swarm optimization algorithms. The simulation results show that the parameters of the fractional-order chaotic power system are identified accurately even in the presence of white noise, demonstrating the strong robustness and versatility of the proposed algorithm.