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Xingyuan Wang

Bio: Xingyuan Wang is an academic researcher from Dalian Maritime University. The author has contributed to research in topics: Encryption & Chaotic. The author has an hindex of 11, co-authored 61 publications receiving 375 citations. Previous affiliations of Xingyuan Wang include Guangxi Normal University & Qilu University of Technology.

Papers published on a yearly basis

Papers
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Journal ArticleDOI
TL;DR: This paper constructs a more efficient and secure chaotic image encryption algorithm than other approaches and presents a new method of global pixel diffusion with two chaotic sequences, which offers good security and high encryption efficiency.

250 citations

Journal ArticleDOI
TL;DR: The 2DNLCML system contains good features such as ergodic pseudo-random sequence, less periodic windows in bifurcations and larger range of parameters in chaotic dynamics, which is more suitable for image encryption.

111 citations

Journal ArticleDOI
TL;DR: A novel triple-image encryption and hiding algorithm is proposed by combining a 2D chaotic system, compressive sensing (CS) and the 3D discrete cosine transform (DCT) to obtain a visually meaningful cipher image.

106 citations

Journal ArticleDOI
TL;DR: The application of TMDPCML system in private images encryption further proves that TMD PCML system has good chaotic behavior and meets the requirements of cryptography.

91 citations

Journal ArticleDOI
TL;DR: Simulation experiment and security analysis show that the correlation coefficient and entropy of ciphertext are excellent, and it can resist all kinds of typical attacks and has better encryption effect.

79 citations


Cited by
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Journal ArticleDOI
TL;DR: Understanding the network structure of a chaotic map’s SMN in digital computers can facilitate counteracting the undesirable degeneration of chaotic dynamics in finite-precision domains, also helping to classify and improve the randomness of pseudo-random number sequences generated by iterating the chaotic maps.
Abstract: Chaotic dynamics is widely used to design pseudo-random number generators and for other applications such as secure communications and encryption. This paper aims to study the dynamics of discrete-time chaotic maps in the digital (i.e., finite-precision) domain. Differing from the traditional approaches treating a digital chaotic map as a black box with different explanations according to the test results of the output, the dynamical properties of such chaotic maps are first explored with a fixed-point arithmetic, using the Logistic map and the Tent map as two representative examples, from a new perspective with the corresponding state-mapping networks (SMNs). In an SMN, every possible value in the digital domain is considered as a node and the mapping relationship between any pair of nodes is a directed edge. The scale-free properties of the Logistic map's SMN are proved. The analytic results are further extended to the scenario of floating-point arithmetic and for other chaotic maps. Understanding the network structure of a chaotic map's SMN in digital computers can facilitate counteracting the undesirable degeneration of chaotic dynamics in finite-precision domains, helping also classify and improve the randomness of pseudo-random number sequences generated by iterating chaotic maps.

153 citations

01 Jan 2000
TL;DR: Fahidy as mentioned in this paper presents a 763 page book for advanced mathematics with a focus on set theory, groups, rings and fields, vector spaces, matrix theory, linear functionals and special functions.
Abstract: This 763 page book, available as both hardback and paperback, is unique in the sense that it sails across the ocean of contemporary advanced mathematics by an impressive tour de force. In twelve ambitious chapters it covers major topics in set theory, groups, rings and fields, vector spaces, matrix theory, linear functionals and special functions. The depth of coverage, however, is highly uneven. Two chapters on linear functionals, one chapter on inner products and norms, and one chapter on convergence in normed vector spaces contain a wealth of finely tuned knowledge. On the other hand, Chapter 1 on the foundations of computation, and the final Chapter 12 on special functions, just skim the surface. The selection of material and its presentation is evidently aimed at computer scientists and computer engineers. Their colleagues in other disciplines will find little that applies directly to their respective fields in spite of the many (more than 400) exercise problems. The author's approach is fundamentally different from similar titles in the literature, e.g. the time-honoured multi-edition text for physicists by Arfken. It provides a cogent, elegant and often esoteric structural framework for mathematical formulations, but with limited interest in exploring detailed solutions. A case in point is the brief presentation of Weber's Y (or N) function, better known as the Bessel function of the second kind. It appears as an eigenfunction of the Bessel operator (Section 12.4), but without any mention of how this function can be routinely eliminated from solutions where the physical quantity of interest is finite at the origin - a cornerstone of numerous practical problem solutions in physics and engineering. Other omissions are equally vexing. In Chapter 3 (Evaluation of Functions), the bisection method is dismissed in nine lines, and no mention is made of the secant method and Wegstein's method, which are just as important for numerical root finding as the analytical (and temperamental) Newton's method. Classical integration techniques are discussed, but not even one of the modern methods (e.g. Gaussian, Chebyshev, Rodau, Lobatto, Laguerre, Hermite and Filon integration) is given any mention. The classical Euler method for integrating ordinary differential equations is the subject of four pages, but there is nothing at all on the widely used Runge-Kutta techniques, nor the highly efficient Richardson's extrapolation method. Modified Bessel functions and Kelvin functions, essential tools in physics and engineering, are completely missing. Fourier transforms are bestowed a short section (11.8), but Laplace transforms? - nothing. Complex numbers pop up here and there, but complex calculus is ignored. The list continues.... Will this work become `... an ideal textbook for senior undergraduate and graduate students in the physical sciences and engineering...' and `... a valuable reference for working engineers...'? The author's claim for the affirmative is extremely tenuous, inasmuch as only highly motivated students with a broad command of mathematics would be able (if willing) to master its contents. The working engineer would most likely look for pragmatic texts, which provide practical/numerical examples in equally modern packing (e.g. Advanced Engineering Mathematics by Robert J Lopez (Addison Wesley, 2000)). Finally, a number of witty comments throughout the book lighten the task of its reading. Some readers will consider the statement (p 494) that `... eigenvalue is a mongrel word...' (in contrast, presumably, with the purebred Eigenwert and valeur propre) to be amusingly clever. An entire Section 8.2 (albeit consisting only of four lines) tells us that `... there seem to be almost as many ways to spell Chebyshev as there are written human languages...', then gracefully provides the proper Cyrillic spelling. Thomas Z Fahidy

141 citations

Journal ArticleDOI
TL;DR: A novel triple-image encryption and hiding algorithm is proposed by combining a 2D chaotic system, compressive sensing (CS) and the 3D discrete cosine transform (DCT) to obtain a visually meaningful cipher image.

106 citations

Journal ArticleDOI
TL;DR: This paper introduces a non-ideal flux-controlled memristor model into a Hopfield neural network (HNN), a novel memristive HNN model with multi-double-scroll attractors that has excellent randomness and is suitable for image encryption application.
Abstract: Memristors are widely considered to be promising candidates to mimic biological synapses. In this paper, by introducing a non-ideal flux-controlled memristor model into a Hopfield neural network (HNN), a novel memristive HNN model with multi-double-scroll attractors is constructed. The parity of the number of double scrolls can be flexibly controlled by the internal parameters of the memristor. Through theoretical analysis and numerical simulation, various coexisting attractors and amplitude control are observed. Particularly, the interesting and rare phenomenon of the memristor initial offset boosting coexisting dynamics is discovered, in which the initial offset boosting coexisting double-scroll attractors with banded attraction basins are distributed in a line along the boosting route with the variation of the memristor initial condition. In addition, it is also found that the number of the initial offset boosting coexisting double-scroll attractors is closely related to the total number of scrolls and ultimately tends to infinity with increasing the total number of scrolls, meaning the emergence of extreme multistability. Then, the random performance of the initial offset boosting coexisting double-scroll attractors is tested by the NIST test suite. Moreover, an encryption scheme based on them is also proposed. The obtained results show that they have excellent randomness and are suitable for image encryption application. Finally, numerical simulation results are well demonstrated by circuit experiments, showing the feasibility of the designed memristive multi-double-scroll HNN model.

92 citations

Journal ArticleDOI
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