A Parameter-Selection-Based Chaotic System

The rapid development of the Internet leads to a surge in the amount of information transmission and brings many security problems. For multimedia information transmission, especially digital images, it is necessary to compress and encrypt at the same time. The emergence of compressive sensing solves this problem. Compressive sensing can compress and encrypt at the same time, which can not only reduce the transmission bandwidth of the network but also improve the security of the system. However, when using compressive sensing encryption, the whole measurement matrix needs to be stored, and the compressive sensing can be combined with a chaotic system, so only the generation parameters of the matrix need to be stored, and the security of the system can be further improved by using the sensitivity of the chaotic system. This paper introduces a secure and efficient image compression-encryption scheme using a new chaotic structure and compressive sensing. The chaotic map used in the scheme is generated by our new and universal chaotic structure, which not only expands the chaotic range of the chaotic system but also improves the performance of the chaotic system. After analyzing the performance comparison of traditional one-dimensional chaotic maps and some existing methods, the image compression-encryption scheme based on a new chaotic structure and compressive sensing has a good encryption effect and large keyspace, which can resist brute force attack and statistical attack.

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“…(1) Sine map Sine map is a very simple and commonly used chaotic system [18]. Sine map is denoted as…”

Section: Chaotic Mapsmentioning

confidence: 99%

Secure and Efficient Image Compression-Encryption Scheme Using New Chaotic Structure and Compressive Sensing

Tang

Zhao

2020

Security and Communication Networks

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“…At present, many research works have focused on improving the chaos complexity of chaotic systems [29], [30]. These efforts can be classified into two types: 1) perturbing the chaotic signals of chaotic systems and 2) designing new chaotic systems.…”

Section: Introductionmentioning

confidence: 99%

Exponential Chaotic Model for Generating Robust Chaos

Hua

Zhou²

2021

IEEE Trans. Syst. Man Cybern, Syst.

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Robust chaos is defined as the inexistence of periodic windows and coexisting attractors in the neighborhood of parameter space. This characteristic is desired because a chaotic system with robust chaos can overcome the chaos disappearance caused by parameter disturbance in practical applications. However, many existing chaotic systems fail to consider the robust chaos. This article introduces an exponential chaotic model (ECM) to produce new one-dimensional (1-D) chaotic maps with robust chaos. ECM is a universal framework and can produce many new chaotic maps employing any two 1-D chaotic maps as base and exponent maps. As examples, we present nine chaotic maps produced by ECM, discuss their bifurcation diagrams and prove their robust chaos. Performance evaluations also show that these nine chaotic maps of ECM can obtain robust chaos in a large parameter space. To show the practical applications of ECM, we employ these nine chaotic maps of ECM in secure communication. Simulation results show their superior performance against various channel noise during data transmission.

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“…Chaotic systems have long been a subject of concern in academic and industrial fields [ 1 , 2 ]. Due to the advantages of the ergodicity, unpredictability, pseudo-randomness and initial value sensitivity [ 3 , 4 ], chaotic systems fit well to various chaos-based image encryptions [ 5 , 6 ] and secure communications [ 7 ].…”

Section: Introductionmentioning

confidence: 99%

Coexisting Infinite Orbits in an Area-Preserving Lozi Map

Chen

et al. 2020

Entropy

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Extreme multistability with coexisting infinite orbits has been reported in many continuous memristor-based dynamical circuits and systems, but rarely in discrete dynamical systems. This paper reports the finding of initial values-related coexisting infinite orbits in an area-preserving Lozi map under specific parameter settings. We use the bifurcation diagram and phase orbit diagram to disclose the coexisting infinite orbits that include period, quasi-period and chaos with different types and topologies, and we employ the spectral entropy and sample entropy to depict the initial values-related complexity. Finally, a microprocessor-based hardware platform is developed to acquire four sets of four-channel voltage sequences by switching the initial values. The results show that the area-preserving Lozi map displays coexisting infinite orbits with complicated complexity distributions, which heavily rely on its initial values.

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A Parameter-Selection-Based Chaotic System

Cited by 24 publications

References 24 publications

Secure and Efficient Image Compression-Encryption Scheme Using New Chaotic Structure and Compressive Sensing

Secure and Efficient Image Compression-Encryption Scheme Using New Chaotic Structure and Compressive Sensing

Exponential Chaotic Model for Generating Robust Chaos

Coexisting Infinite Orbits in an Area-Preserving Lozi Map

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