Showing papers on "Chaotic published in 2022"
TL;DR: Proof that chaotic systems resist dynamic degradation through theoretical analysis is presented, and a novel one-dimensional two-parameter with a wide-range system mixed coupled map lattice model (TWMCML) is given.
Abstract: Since chaotic cryptography has a long-term problem of dynamic degradation, this paper presents proof that chaotic systems resist dynamic degradation through theoretical analysis. Based on this proof, a novel one-dimensional two-parameter with a wide-range system mixed coupled map lattice model (TWMCML) is given. The evaluation of TWMCML shows that the system has the characteristics of strong chaos, high sensitivity, broader parameter ranges and wider chaos range, which helps to enhance the security of chaotic sequences. Based on the excellent performance of TWMCML, it is applied to the newly proposed encryption algorithm. The algorithm realizes double protection of private images under the premise of ensuring efficiency and safety. First, the important information of the image is extracted by edge detection technology. Then the important area is scrambled by the three-dimensional bit-level coupled XOR method. Finally, the global image is more fully confused by the dynamic index diffusion formula. The simulation experiment verified the effectiveness of the algorithm for grayscale and color images. Security tests show that the application of TWMCML makes the encryption algorithm have a better ability to overcome conventional attacks.
92 citations
89 citations
TL;DR: In this article , a discrete memristive Rulkov (m-Rulkov) neuron model is proposed and the bifurcation routes of the model are declared by detecting the eigenvalue loci.
Abstract: The magnetic induction effects have been emulated by various continuous memristive models but they have not been successfully described by a discrete memristive model yet. To address this issue, this article first constructs a discrete memristor and then presents a discrete memristive Rulkov (m-Rulkov) neuron model. The bifurcation routes of the m-Rulkov model are declared by detecting the eigenvalue loci. Using numerical measures, we investigate the complex dynamics shown in the m-Rulkov model, including regime transition behaviors, transient chaotic bursting regimes, and hyperchaotic firing behaviors, all of which are closely relied on the memristor parameter. Consequently, the involvement of memristor can be used to simulate the magnetic induction effects in such a discrete neuron model. Besides, we elaborate a hardware platform for implementing the m-Rulkov model and acquire diverse spiking-bursting sequences. These results show that the presented model is viable to better characterize the actual firing activities in biological neurons than the Rulkov model when biophysical memory effect is supplied.
72 citations
TL;DR: In this paper , a new crude oil price prediction model is proposed, which includes the long short-term memory (LSTM), technical indicators such as trend, volatility and momentum, and the chaotic Henry gas solubility optimization (CHGSO) technique.
71 citations
TL;DR: Wang et al. as mentioned in this paper proposed a memristive neuron model with significant chaotic characteristics, which can effectively protect the information security of images, and they also proposed a new encryption scheme to apply the model to the application of image encryption.
Abstract: The neuron models have been widely applied to neuromorphic computing systems and chaotic circuits. However, discrete neuron models and their application in image encryption have not gotten a lot of attention yet. This paper first presents a novel neuron model with significant chaotic characteristics, by coupling a memristor into the proposed neuron, a memristive neuron model is further obtained. Relevant control parameter-relied dynamical evolution is demonstrated using several numerical methods . The explorations manifest that memristor can boost chaos complexity of the discrete neuron, resulting in hyperchaos, infinite coexisting hidden attractors and attractor growing. Particularly, the NIST test verifies the generated hyperchaotic sequences exhibit high complexity, which makes them applicable to many applications based on chaos. Additionally, digital experiments based on developed hardware platform are designed to implement the memristive neuron model and get the hyperchaos. We also propose a new encryption scheme to apply the memristive neuron to the application of image encryption. The evaluation results show that the conceived algorithm appears excellent security characteristics and can effectively protect the information security of images.
59 citations
TL;DR: The proposed NCCS system has larger key space and exhibits better cryptographic features in dynamics than their original one-dimensional chaotic map, and the validity of the proposed algorithm in terms of high security is shown.
50 citations
TL;DR: In this article , a chaotic k-best gravitational search strategy (CKGSS) was proposed to obtain the adaptive step to improve the global exploratory ability, and the performance of the EOCSGWO was verified and compared with those of other seven meta-heuristic optimization algorithms.
49 citations
47 citations
TL;DR: In this article, the chaotic dynamical system theory provides a simplified analytical framework that provides deeper insights into the performance of the asymmetric tristable energy harvester, which can more easily jump into the interwell motion and output the higher voltage under low-level excitations.
46 citations
TL;DR: In this paper , the chaotic dynamical system theory provides a simplified analytical framework that provides deeper insights into the performance of the asymmetric tristable energy harvester, which can more easily jump into the interwell motion and output the higher voltage under low-level excitations.
46 citations
TL;DR: In this paper , a new 4D chaotic system with self-excited attractors or hidden attractors is designed and the generation of self excited attractors and hidden attractedors depends on the parameters of the new chaotic system.
TL;DR: In this article, a chaotic strategy-based quadratic opposition-based learning adaptive variable speed whale optimization algorithm is proposed to solve the problems that the current algorithm's convergence accuracy and convergence speed are insufficient.
TL;DR: In this paper , a chaotic strategy-based quadratic opposition-based learning adaptive variable speed whale optimization algorithm is proposed to solve the problems that the current algorithm's convergence accuracy and convergence speed are insufficient.
TL;DR: In this paper , the authors proposed a locally active discrete memristor model for the first time and proved the three fingerprints characteristics of this model according to the definition of generalized memristors.
Abstract: The continuous memristor is a popular topic of research in recent years, however, there is rare discussion about the discrete memristor model, especially the locally active discrete memristor model. This paper proposes a locally active discrete memristor model for the first time and proves the three fingerprints characteristics of this model according to the definition of generalized memristor. A novel hyperchaotic map is constructed by coupling the discrete memristor with a two-dimensional generalized square map. The dynamical behaviors are analyzed with attractor phase diagram, bifurcation diagram, Lyapunov exponent spectrum, and dynamic behavior distribution diagram. Numerical simulation analysis shows that there is significant improvement in the hyperchaotic area, the quasi periodic area and the chaotic complexity of the two-dimensional map when applying the locally active discrete memristor. In addition, antimonotonicity and transient chaos behaviors of system are reported. In particular, the coexisting attractors can be observed in this discrete memristive system, resulting from the different initial values of the memristor. Results of theoretical analysis are well verified with hardware experimental measurements. This paper lays a great foundation for future analysis and engineering application of the discrete memristor and relevant the study of other hyperchaotic maps.
TL;DR: Wang et al. as discussed by the authors proposed a new combination chaotic system (NCCS) for image encryption, which has larger key space and exhibits better cryptographic features in dynamics than their original one-dimensional chaotic map.
01 Jan 2022
TL;DR: A novel chaotic search-and-rescue-optimization-based multi-hop data transmission (CSRO-MHDT) protocol for UWSNs that resulted in higher values of number of packets received (NPR) under all rounds and a chaotic search and rescue optimization algorithm for route optimization, which was developed in-house.
Abstract: Underwater wireless sensor networks (UWSNs) have applications in several fields, such as disaster management, underwater navigation, and environment monitoring. Since the nodes in UWSNs are restricted to inbuilt batteries, the effective utilization of available energy becomes essential. Clustering and routing approaches can be employed as energy-efficient solutions for UWSNs. However, the cluster-based routing techniques developed for conventional wireless networks cannot be employed for a UWSN because of the low bandwidth, spread stay, underwater current, and error probability. To resolve these issues, this article introduces a novel chaotic search-and-rescue-optimization-based multi-hop data transmission (CSRO-MHDT) protocol for UWSNs. When using the CSRO-MHDT technique, cluster headers (CHs) are selected and clusters are prearranged, rendering a range of features, including remaining energy, intracluster distance, and intercluster detachment. Additionally, the chaotic search and rescue optimization (CSRO) algorithm is discussed, which is created by incorporating chaotic notions into the classic search and rescue optimization (SRO) algorithm. In addition, the CSRO-MHDT approach calculates a fitness function that takes residual energy, distance, and node degree into account, among other factors. A distinctive aspect of the paper is demonstrated by the development of the CSRO algorithm for route optimization, which was developed in-house. To validate the success of the CSRO-MHDT method, a sequence of tests were carried out, and the results showed the CSRO-MHDT method to have a packet delivery ratio (PDR) of 88%, whereas the energy-efficient clustering routing protocol (EECRP), the fuzzy C-means and moth–flame optimization (FCMMFO), the fuzzy scheme and particle swarm optimization (FBCPSO), the energy-efficient grid routing based on 3D cubes (EGRC), and the low-energy adaptive clustering hierarchy based on expected residual energy (LEACH-ERE) methods have reached lesser PDRs of 83%, 81%, 78%, 77%, and 75%, respectively, for 1000 rounds. The CSRO-MHDT technique resulted in higher values of number of packets received (NPR) under all rounds. For instance, with 50 rounds, the CSRO-MHDT technique attained a higher NPR of 3792%.
TL;DR: In this paper , a general 3D discrete memristor-based (3D-DM) map model was presented, which can enhance the chaos complexity of existing discrete maps and its coupling maps can display hyperchaos.
Abstract: With the nonlinearity and plasticity, memristors are widely used as nonlinear devices for chaotic oscillations or as biological synapses for neuromorphic computations. But discrete memristors (DMs) and their coupling maps have not received much attention, yet. Using a DM model, this article presents a general three-dimensional discrete memristor-based (3-D-DM) map model. By coupling the DM with four 2-D discrete maps, four examples of 3-D-DM maps with no or infinitely many fixed points are generated. We simulate the coupling coefficient-depended and memristor initial-boosted bifurcation behaviors of these 3-D-DM maps using numerical measures. The results demonstrate that the memristor can enhance the chaos complexity of existing discrete maps and its coupling maps can display hyperchaos. Furthermore, a hardware platform is developed to implement the 3-D-DM maps and the acquired hyperchaotic sequences have high randomness. Particularly, these hyperchaotic sequences can be applied to the auxiliary classifier generative adversarial nets for greatly improving the discriminator accuracy.
TL;DR: Wang et al. as discussed by the authors proposed a new fractional-order chaotic system based on the model of 4-neurons-based Hopfield Neural Network (HNN).
Abstract: In this work, we propose a new fractional-order chaotic system based on the model of 4-neurons-based Hopfield Neural Network (HNN). By using Adomain decomposition method, the proposed fractional-order chaotic system is solved. With the orders changing, the proposed fractional-order system shows rich dynamical characteristics. Then, based on the pseudo-random numbers (PRNs) generated by the proposed system, a new construction method of multiple hash index chain is designed. And a new image encryption algorithm is designed according to the multiple hash index chain. The safety test results show that the design encryption algorithm has higher security performance. Finally, the 4-neurons-based HNN fractional-order system is implemented by Multisim circuit simulation. The experimental results show the feasibility of the theoretical analysis.
01 Apr 2022
TL;DR: Wang et al. as mentioned in this paper combined a four-dimensional chaotic system with DNA technology to design a color image encryption algorithm, which converted each pixel value into two 4-bit binary for WSSM scrambling.
Abstract: This paper combines a four-dimensional chaotic system with DNA technology to design a color image encryption algorithm. The algorithm converts each pixel value into two 4-bit binary for WSSM scrambling. The proposed 4D chaotic system is used to generate four chaotic sequences to determine the rules of DNA encoding, decoding and calculation. Finally, the three matrices of R, G, and B are divided into blocks and scrambled. Security analysis is carried out, including histogram, key sensitivity, entropy, correlation, anti-differential attack, anti-noise attack, occlusion attack and other aspects. All experimental results show that the proposed image encryption algorithm can effectively resist various attacks.
TL;DR: Wang et al. as discussed by the authors proposed a stable image encryption scheme to create visually secure cipher image by using new fractional-order chaotic map, Bayesian compressive sensing and DVT embedding.
TL;DR: Wang et al. as discussed by the authors proposed a new image encryption scheme by combining six-dimensional non-degenerate discrete hyper-chaotic system, two-dimensional discrete cosine Stockwell transform with DNA-level modulus diffusion.
Abstract: • An image encryption scheme with 2D discrete cosine Stockwell transform and DNA-level modulus diffusion is proposed. • The 2D discrete cosine Stockwell transform performs better in image compression and anti-noise. • The improved global chaotic diffusion algorithm achieves a better diffusion effect. A new image encryption scheme is presented by combining six-dimensional non-degenerate discrete hyper-chaotic system, two-dimensional discrete cosine Stockwell transform with DNA-level modulus diffusion. The significant advantages of this scheme are the large key space, strong anti-noise ability and resistance to common attacks. To resist the powerful chosen plaintext attack, the initial conditions of the chaotic systems are generated with the SHA-512 hash function value of the plaintext image and the external key. The transmission burden is reduced by compressing the original image with the two-dimensional discrete cosine Stockwell transform. Then random DNA encoding is performed on the compressed image to obtain the DNA image. To speed up the encryption, the DNA-level modulus diffusion algorithm is designed to scramble and diffuse pixels at the same time. Finally, the final encrypted image is obtained by re-encrypting the diffused DNA image with the bit-level permutation and the improved global dynamic diffusion. The two high-dimensional chaotic systems introduced in the image encryption scheme greatly increases the key space and then the image encryption scheme can resist the brute-force attack. The presented scheme is sensitive to both plaintext images and secret keys. Simulation results show that the proposed image encryption algorithm is feasible, secure and effective.
TL;DR: A survey on the most up-to-date chaos-based image encryption techniques and classifies them into spatial, temporal and spatio-temporal domains for better understanding is presented in this paper .
Abstract: Abstract Chaos-based cryptosystems have been an active area of research in recent years. Although these algorithms are not standardized like AES, DES, RSA, etc., chaos-based cryptosystems like Chebyshev polynomials can provide additional security when used with standard public key cryptosystems like RSA and El-gamal. Standard encryption algorithms such as AES have always been the primary choice, but when it comes to image or video encryption, many researchers recommend chaos-based encryption techniques due to their computational efficiency. This paper presents a survey on the most up-to-date chaos-based image encryption techniques and classifies them into spatial, temporal and spatiotemporal domains for better understanding. The significant improvements in the field of image encryption are discussed. In addition, comparative analysis is performed to validate the evaluation matrices for quantifying the encryption algorithms’ security and performance in recent papers.
TL;DR: The present investigation shows that CLFD is a robust technique that can efficiently find optimal mechanical design problems with a proper chaotic map selection.
Abstract: This work proposed a new metaheuristic dubbed as Chaotic Lévy flight distribution (CLFD) algorithm, to address physical world engineering optimization problems that incorporate the chaotic maps in the elementary Lévy flight distribution (LFD). Hybridization aims to increase the LFD rate of convergence while also providing a problem‐free optimization approach. The proposed methodology is investigated for five case studies of constrained optimization issues followed by shape optimization of structural design. The outcomes from the CFLD algorithm are further contrasted with its fundamental version and other distinguished recently introduced algorithms. The computational analysis illustrates the dominance of CLFD over other considered optimizers. Moreover, the present investigation shows that CLFD is a robust technique that can efficiently find optimal mechanical design problems with a proper chaotic map selection.
TL;DR: In this paper , a wrapper feature selection method that combines chaotic maps (CMs) and binary Group Search Optimizer (GSO) is proposed, which is used to solve the FS problem.
Abstract: Feature selection (FS) is recognized as one of the majority public and challenging problems in the Machine Learning domain. FS can be examined as an optimization problem that needs an effective optimizer to determine its optimal subset of more informative features. This paper proposes a wrapper FS method that combines chaotic maps (CMs) and binary Group Search Optimizer (GSO) called CGSO, which is used to solve the FS problem. In this method, five chaotic maps are incorporated with the GSO algorithm’s main procedures, namely, Logistic, Piecewise, Singer, Sinusoidal, and Tent. The GSO algorithm is used as a search strategy, while k-NN is employed as an induction algorithm. The objective function is to integrate three main objectives: maximizing the classification accuracy value, minimizing the number of selected features, and minimizing the complexity of generated k-NN models. To evaluate the proposed methods’ performance, twenty well-known UCI datasets are used and compared with other well-known published methods in the literature. The obtained results reveal the superiority of the proposed methods in outperforming other well-known methods, especially when using binary GSO with Tent CM. Finally, it is a beneficial method to be utilized in systems that require FS pre-processing.
TL;DR: In this article , an improved form of chaotic based atom search optimization (IASO) algorithm was proposed by adapting one-dimensional (1D) chaotic map (tent, sine and logistic) to improve the search ability by intensifying the exploration and exploitation phase.
TL;DR: Gao et al. as discussed by the authors proposed a 3D model encryption method based on a 2D chaotic system constructed via the coupling of the logistic map and infinite collapse (2D-LAIC) and on semi-tensor product (STP) theory.
TL;DR: In this article , a two-dimensional cross-mode hyperchaotic map based on logistic and sine maps (2D-CLSS) is presented, which combines permutation and diffusion to alter the location and the value of the pixels.