Chaotic CS Encryption: An Efficient Image Encryption Algorithm Based on Chebyshev Chaotic System and Compressive Sensing

被引:0
|
作者
Sun, Mingliang [1 ]
Yuan, Jie [1 ]
Li, Xiaoyong [1 ]
Liu, Dongxiao [1 ]
机构
[1] Beijing Univ Posts & Telecommun, Key Lab Trustworthy Distributed Comp & Serv, Minist Educ, Beijing 100876, Peoples R China
来源
CMC-COMPUTERS MATERIALS & CONTINUA | 2024年 / 79卷 / 02期
基金
中国国家自然科学基金;
关键词
Image encryption; chaotic system; compressive sensing; arnold transform; DNA; MAP;
D O I
10.32604/cmc.2024.050337
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
Images are the most important carrier of human information. Moreover, how to safely transmit digital images through public channels has become an urgent problem. In this paper, we propose a novel image encryption algorithm, called chaotic compressive sensing (CS) encryption (CCSE), which can not only improve the efficiency of image transmission but also introduce the high security of the chaotic system. Specifically, the proposed CCSE can fully leverage the advantages of the Chebyshev chaotic system and CS, enabling it to withstand various attacks, such as differential attacks, and exhibit robustness. First, we use a sparse trans-form to sparse the plaintext image and then use the Arnold transform to perturb the image pixels. After that, we elaborate a Chebyshev Toeplitz chaotic sensing matrix for CCSE. By using this Toeplitz matrix, the perturbed image is compressed and sampled to reduce the transmission bandwidth and the amount of data. Finally, a bilateral diffusion operator and a chaotic encryption operator are used to perturb and expand the image pixels to change the pixel position and value of the compressed image, and ultimately obtain an encrypted image. Experimental results show that our method can be resistant to various attacks, such as the statistical attack and noise attack, and can outperform its current competitors.
引用
收藏
页码:2625 / 2646
页数:22
相关论文
共 50 条
  • [1] An image encryption algorithm based on chaotic system and compressive sensing
    Chai, Xiuli
    Zheng, Xiaoyu
    Gan, Zhihua
    Han, Daojun
    Chen, Yiran
    [J]. SIGNAL PROCESSING, 2018, 148 : 124 - 144
  • [2] An image compression and encryption algorithm based on chaotic system and compressive sensing
    Gong, Lihua
    Qiu, Kaide
    Deng, Chengzhi
    Zhou, Nanrun
    [J]. OPTICS AND LASER TECHNOLOGY, 2019, 115 : 257 - 267
  • [3] Meaningful color image encryption algorithm based on compressive sensing and chaotic map
    Liu, Min
    Ye, Guodong
    Lin, Qiuzhen
    [J]. 2021 IEEE INTERNATIONAL SYMPOSIUM ON SOFTWARE RELIABILITY ENGINEERING WORKSHOPS (ISSREW 2021), 2021, : 262 - 265
  • [4] A joint image encryption and watermarking algorithm based on compressive sensing and chaotic map
    肖迪
    蔡洪坤
    郑洪英
    [J]. Chinese Physics B, 2015, (06) : 202 - 210
  • [5] A joint image encryption and watermarking algorithm based on compressive sensing and chaotic map
    Xiao Di
    Cai Hong-Kun
    Zheng Hong-Ying
    [J]. CHINESE PHYSICS B, 2015, 24 (06)
  • [6] Encryption of image data using compressive sensing and chaotic system
    R. Ponuma
    R. Amutha
    [J]. Multimedia Tools and Applications, 2019, 78 : 11857 - 11881
  • [7] Encryption of image data using compressive sensing and chaotic system
    Ponuma, R.
    Amutha, R.
    [J]. MULTIMEDIA TOOLS AND APPLICATIONS, 2019, 78 (09) : 11857 - 11881
  • [8] Image encryption algorithm based on chaotic system
    Fan, Jiu-Lun
    Zhang, Xue-Feng
    [J]. 7TH INTERNATIONAL CONFERENCE ON COMPUTER-AIDED INDUSTRIAL DESIGN & CONCEPTUAL DESIGN, 2006, : 767 - 771
  • [9] Image encryption algorithm using chaotic Chebyshev generator
    Huang, Xiaoling
    [J]. NONLINEAR DYNAMICS, 2012, 67 (04) : 2411 - 2417
  • [10] Image encryption algorithm using chaotic Chebyshev generator
    Xiaoling Huang
    [J]. Nonlinear Dynamics, 2012, 67 : 2411 - 2417