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

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.

[1]  Xingyuan Wang,et al.  A novel chaotic image encryption scheme using DNA sequence operations , 2015 .

[2]  R. Amutha,et al.  Encryption of image data using compressive sensing and chaotic system , 2018, Multimedia Tools and Applications.

[3]  Yong Wang,et al.  An image coding scheme using parallel compressive sensing for simultaneous compression-encryption applications , 2017, J. Vis. Commun. Image Represent..

[4]  Zhiliang Zhu,et al.  A Novel Image Encryption Scheme Using the Composite Discrete Chaotic System , 2016, Entropy.

[5]  Ching-Yu Yang Robust high-capacity watermarking scheme based on Euclidean norms and quick coefficient alignment , 2015, Multimedia Tools and Applications.

[6]  Kehui Sun,et al.  A fast image encryption algorithm based on compressive sensing and hyperchaotic map , 2019, Optics and Lasers in Engineering.

[7]  Kehui Sun,et al.  A fast image encryption algorithm based on chaotic map , 2016 .

[8]  Sudhish N. George,et al.  Audio security through compressive sampling and cellular automata , 2014, Multimedia Tools and Applications.

[9]  Janier Arias-Garcia,et al.  Image encryption based on the pseudo-orbits from 1D chaotic map. , 2019, Chaos.

[10]  Y. Rachlin,et al.  The secrecy of compressed sensing measurements , 2008, 2008 46th Annual Allerton Conference on Communication, Control, and Computing.

[11]  Li-Hua Gong,et al.  Novel image compression–encryption hybrid algorithm based on key-controlled measurement matrix in compressive sensing , 2014 .

[12]  Nanrun Zhou,et al.  Color Image Encryption Algorithm Combining Compressive Sensing with Arnold Transform , 2013, J. Comput..

[13]  Yimin Zhao,et al.  A Novel Secure Data Transmission Scheme Using Chaotic Compressed Sensing , 2018, IEEE Access.

[14]  G. Sharma,et al.  On the security and robustness of encryption via compressed sensing , 2008, MILCOM 2008 - 2008 IEEE Military Communications Conference.

[15]  Shouzhi Yang,et al.  Image Encryption Technique Combining Compressive Sensing with Double Random-Phase Encoding , 2018 .

[16]  Sudhish N. George,et al.  A Secure LFSR Based Random Measurement Matrix for Compressive Sensing , 2014 .

[17]  Alfredo De Santis,et al.  On-Board Format-Independent Security of Functional Magnetic Resonance Images , 2017, ACM Trans. Embed. Comput. Syst..

[18]  Erivelton G. Nepomuceno,et al.  Image encryption using finite-precision error , 2019, Chaos, Solitons & Fractals.

[19]  Maher K. Mahmood Al-Azawi,et al.  Combined speech compression and encryption using chaotic compressive sensing with large key size , 2018, IET Signal Process..

[20]  Hong Wang,et al.  Image compression-encryption scheme combining 2D compressive sensing with discrete fractional random transform , 2017, Multimedia Tools and Applications.

[21]  Ming Li,et al.  Secure image encryption scheme using double random-phase encoding and compressed sensing , 2020 .

[22]  R. Amutha,et al.  Compressive sensing based image compression-encryption using Novel 1D-Chaotic map , 2017, Multimedia Tools and Applications.

[23]  Yide Ma,et al.  A Novel 1D Hybrid Chaotic Map-Based Image Compression and Encryption Using Compressed Sensing and Fibonacci-Lucas Transform , 2016 .

[24]  Rudy Susanto Endra Compressive sensing-based image encryption with optimized sensing matrix , 2013, 2013 IEEE International Conference on Computational Intelligence and Cybernetics (CYBERNETICSCOM).

[25]  Xing-yuan Wang,et al.  A fast image algorithm based on rows and columns switch , 2014, Nonlinear Dynamics.

[26]  Lu Xu,et al.  A novel bit-level image encryption algorithm based on chaotic maps , 2016 .

[27]  Kwok-Wo Wong,et al.  Bi-level Protected Compressive Sampling , 2016, IEEE Transactions on Multimedia.

[28]  Di Wang,et al.  Image compression and encryption scheme based on 2D compressive sensing and fractional Mellin transform , 2015 .