A Novel Secure Data Transmission Scheme Using Chaotic Compressed Sensing

Gan, Hongping; Xiao, Song; Zhao, Yao

doi:10.1109/access.2017.2780323

Cited by 29 publications

(25 citation statements)

References 43 publications

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“…In past work, Yu proposed to construct the measurement matrix of CS using chaotic mapping, and to generate chaotic sequences using logistic mapping and tent mapping [23]. Due to the ergodic characteristics of chaotic systems, the measurement matrix constructed by a chaotic system is essentially a sub-Gaussian random matrix.…”

Section: Logistic-tent Chaotic Systemmentioning

confidence: 99%

Image Parallel Encryption Technology Based on Sequence Generator and Chaotic Measurement Matrix

Guo

Song

et al. 2020

Entropy

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In this paper, a new image encryption transmission algorithm based on the parallel mode is proposed. This algorithm aims to improve information transmission efficiency and security based on existing hardware conditions. To improve efficiency, this paper adopts the method of parallel compressed sensing to realize image transmission. Compressed sensing can perform data sampling and compression at a rate much lower than the Nyquist sampling rate. To enhance security, this algorithm combines a sequence signal generator with chaotic cryptography. The initial sensitivity of chaos, used in a measurement matrix, makes it possible to improve the security of an encryption algorithm. The cryptographic characteristics of chaotic signals can be fully utilized by the flexible digital logic circuit. Simulation experiments and analyses show that the algorithm achieves the goal of improving transmission efficiency and has the capacity to resist illegal attacks.

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Section: Logistic-tent Chaotic Systemmentioning

confidence: 99%

Image Parallel Encryption Technology Based on Sequence Generator and Chaotic Measurement Matrix

Guo

Song

et al. 2020

Entropy

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“…Both RIP [16][17][18][19] and coherence [9][10][11][12][13][20][21][22][23][24][25][26][27] are important tools to analyze the property of measurement matrices. In this paper, coherence will be adopted to analyze and illustrate the property of constructed measurement matrices, because it is easier to compute.…”

Section: Lemma 11mentioning

confidence: 99%

Binary Sequence Family for Chaotic Compressed Sensing

2019

KSII TIIS

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It is significant to construct deterministic measurement matrices with easy hardware implementation, good sensing performance and good cryptographic property for practical compressed sensing (CS) applications. In this paper, a deterministic construction method of bipolar chaotic measurement matrices is presented based on binary sequence family (BSF) and Chebyshev chaotic sequence. The column vectors of these matrices are the sequences of BSF, where 1 is substituted with-1 and 0 is with 1. The proposed matrices, which exploit the pseudo-randomness of Chebyshev sequence, are sensitive to the initial state. The performance of proposed matrices is analyzed from the perspective of coherence. Theoretical analysis and simulation experiments show that the proposed matrices have limited influence on the recovery accuracy in different initial states and they outperform their Gaussian and Bernoulli counterparts in recovery accuracy. The proposed matrices can make the hardware implement easy by means of linear feedback shift register (LFSR) structures and numeric converter, which is conducive to practical CS.

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“…Synchronization chaotic systems have attracted great interest because of their potential applications in various fields such as electronics, signal processing, secure communication, aerospace, and biological systems [70][71][72][73][74][75][76][77]. Synchronization of chaotic systems is the control of the slave system to mimic the behavior of the master system.…”

Section: Introductionmentioning

confidence: 99%

A Modified Grey Wolf Optimizer for Optimum Parameters of Multilayer Type-2 Asymmetric Fuzzy Controller

Lin

Hong

2020

IEEE Access

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This study presents a modified algorithm of the grey wolf optimizer to solve the problem of learning rate selection in the multilayer type-2 asymmetric fuzzy controller (MT2AFC). The improvements of our modified optimizer are: the best position of the swarm is memorized, thus making the alpha wolves only update when a better position appears in the next iteration; search performance is enhanced by giving more freedom to update the grey wolf position. The proposed optimizer algorithm is then applied to optimize the suitable learning rates for the proposed controller. The multilayer type-2 asymmetric membership function is used in the fuzzy control network to enhance the learning ability and flexibility of the designed network architecture. The gradient descent method is used to adjust the parameters of the proposed MT2AFC controller online. The stability of the system is guaranteed using the Lyapunov approach. Besides, the self-evolving algorithm is used to construct the network structure autonomously. Ultimately, the numerical simulations of the chaotic synchronization systems are carried out to verify the effectiveness of our proposed method. INDEX TERMS grey wolf optimizer, interval type-2 fuzzy neural network, asymmetric membership function, chaotic synchronization systems.

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A Novel Secure Data Transmission Scheme Using Chaotic Compressed Sensing

Cited by 29 publications

References 43 publications

Image Parallel Encryption Technology Based on Sequence Generator and Chaotic Measurement Matrix

Image Parallel Encryption Technology Based on Sequence Generator and Chaotic Measurement Matrix

Binary Sequence Family for Chaotic Compressed Sensing

A Modified Grey Wolf Optimizer for Optimum Parameters of Multilayer Type-2 Asymmetric Fuzzy Controller

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