Research article Special Issues

A visually secure image encryption method based on integer wavelet transform and rhombus prediction

  • Received: 25 October 2020 Accepted: 28 January 2021 Published: 07 February 2021
  • Traditional image encryption technology usually encrypts a normal image into a noise matrix, which can protect the image in a certain extent, but noise appearance is easy to arouse the suspicion of attackers. To avoid this problem, a method of encrypting image into carrier image with visual meaning is proposed. Inspired by the existing visually secure encryption technique, we proposed an improved method based on the integer wavelet transform (IWT) and prediction scheme. The secret image is hidden in the high frequency coefficients of IWT to achieve good invisibility, and prediction error are used to replace the pixels of the carrier image to improve the final image quality. Experimental results and analysis show that the quality of the encrypted image is 3.5 dB better than that of the previous ones.

    Citation: Xianyi Chen, Mengling Zou, Bin Yang, Zhenli Wang, Nannan Wu, Lili Qi. A visually secure image encryption method based on integer wavelet transform and rhombus prediction[J]. Mathematical Biosciences and Engineering, 2021, 18(2): 1722-1739. doi: 10.3934/mbe.2021089

    Related Papers:

  • Traditional image encryption technology usually encrypts a normal image into a noise matrix, which can protect the image in a certain extent, but noise appearance is easy to arouse the suspicion of attackers. To avoid this problem, a method of encrypting image into carrier image with visual meaning is proposed. Inspired by the existing visually secure encryption technique, we proposed an improved method based on the integer wavelet transform (IWT) and prediction scheme. The secret image is hidden in the high frequency coefficients of IWT to achieve good invisibility, and prediction error are used to replace the pixels of the carrier image to improve the final image quality. Experimental results and analysis show that the quality of the encrypted image is 3.5 dB better than that of the previous ones.



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    [1] D. D. Hou, W. M. Zhang, N. Yu, Image camouflage by reversible image transformation, J. Visual Commun. Image Representation, 40 (2016), 225–236. doi: 10.1016/j.jvcir.2016.06.018
    [2] G. R. Chen, Y. B. Mao, C. K. Chui, A symmetric image encryption scheme based on 3D chaotic cat maps, Chaos Solitons Fractals, 21 (2004), 749–761. doi: 10.1016/j.chaos.2003.12.022
    [3] M. Mollaeefar, A. Sharif, M. Narazi, A novel encryption scheme for colored image based on high level chaotic maps, Multimed Tools Appl., 76 (2017), 607–629. doi: 10.1007/s11042-015-3064-9
    [4] D. Xiao, J. Liang, Q. Ma, Y. Xiang, Y. Zhang, High capacity data hiding in encrypted image based on compressive sensing for nonequivalent resources, Comput. Mater. Continua, 58 (2019), 1–13. doi: 10.32604/cmc.2019.02171
    [5] J. Fridrich, M. Goljan, R. Du, Detecting LSB steganography in color and gray-scale images, IEEE Multimedia, 8 (2001), 22–28.
    [6] S. Husien, H. Badi, Artificial neural network for steganography, Neural Comput. Appl., 26 (2015), 111–116. doi: 10.1007/s00521-014-1702-1
    [7] J. Fridrich, Symmetric ciphers based on two-dimensional chaotic maps, Int. J. Bifurcation Chaos, 8 (1998), 1259–1284. doi: 10.1142/S021812749800098X
    [8] G. Gu, L. Jie, A fast image encryption method by using chaotic 3D cat maps, Optik Int. J. Light Electron Optics, 125 (2014), 4700–4705. doi: 10.1016/j.ijleo.2014.05.023
    [9] Z. H. Guan, F. Huang, W. Guan, Chaos-based image encryption algorithm, Phys. Lett. A, 346 (2005), 153–157. doi: 10.1016/j.physleta.2005.08.006
    [10] J. Nechvatal, E. Barker, L. Bassham, W. Burr, M. Dworkin, J. Foti, et al., Report on the development of the Advanced Encryption Standard (AES), J. Res. Natl. Inst. Stand. Technol., 106 (2001), 511–577. doi: 10.6028/jres.106.023
    [11] Z. Y. Xia, L. H. Liu, H. J. Shim, X.Y. Chen, B. Jeon, A privacy-preserving image retrieval based on AC-Coefficients and color histograms in cloud environment, Comput. Mater. Continua, 58 (2019), 27–43. doi: 10.32604/cmc.2019.02688
    [12] L. Teng, X. Wang, J. Meng, A chaotic color image encryption using inter grated bit-level permutation, Multimed Tools Appl., 77 (2018), 6883–6896. doi: 10.1007/s11042-017-4605-1
    [13] M. Ahmad, O. Farooq, Secure satellite images transmission scheme based on chaos and discrete wavelet transform, International Conference on High Performance Architecture and Grid Computing, Springer, Berlin, Heidelberg, 2011.
    [14] L. Xiong, Z. Xu, Y. Q. Shi, An integer wavelet transform based scheme for reversible data hiding in encrypted images, Multidimens. Syst. Signal Process., 29 (2018), 1191–1202. doi: 10.1007/s11045-017-0497-5
    [15] G. D. Ye, K. X. Jiao, H. Wu, C. Pan, X. Huang, An asymmetric image encryption algorithm based on a fractional-order chaotic system and the RSA public-key cryptosystem, Int. J. Bifurcation Chaos, 30 (2020), 2050233. doi: 10.1142/S0218127420502338
    [16] G. D. Ye, C. Pan, Y. X. Dong, Y. Shi, X. L. Huang, Image encryption and hiding algorithm based on compressive sensing and random numbers insertion, Signal Process., 172 (2020), 107563. doi: 10.1016/j.sigpro.2020.107563
    [17] X. L. Huang, Y. X. Dong, K.X. Jiao, G. D. Ye, Asymmetric pixel confusion algorithm for images based on RSA and Arnold transform, Front. Inf. Technol. Electron. Eng., 21 (2020), 1783–1794. doi: 10.1631/FITEE.2000241
    [18] H. S. Ye, N. R. Zhou, L. H. Gong, Multi-image compression-encryption scheme based on quaternion discrete fractional hartley transform and chaotic systems, Signal Process., 175 (2020), 107652. doi: 10.1016/j.sigpro.2020.107652
    [19] Z. Hua, Y. Zhou, C. M. Pun, C. L. P. Chen, 2D Sine logistic modulation map for image encryption, Inf. Sci., 297 (2015), 80–94. doi: 10.1016/j.ins.2014.11.018
    [20] X. Y. Chen, H. D. Zhong, Z. F. Bao, A GLCM feature based approach for reversible image transformation, Comput. Mater. Continua, 59 (2019), 239–255. doi: 10.32604/cmc.2019.03572
    [21] J. Tian, Reversible data embedding using a difference expansion, IEEE Trans. Circuits Syst. Video Technol., 13 (2003), 890–896. doi: 10.1109/TCSVT.2003.815962
    [22] J. Li, X. Li, B. Yang, X. Sun, Segmentation-Based image copy-move forgery detection scheme, IEEE Trans. Inf. Forensics Secur., 10 (2015), 507–518. doi: 10.1109/TIFS.2014.2381872
    [23] X. Gao, C. Deng, X. Li, D. Tao, Geometric distortion insensitive image watermarking in affine covariant regions, IEEE Trans. Syst. Man Cybern. Part C, 40 (2010), 278–286. doi: 10.1109/TSMCC.2009.2037512
    [24] M. L. Liu, H. S. Seah, C. Zhu, W. Lin, F. Tian, Reducing location map in prediction-based difference expansion reversible image data embedding, Signal Process., 92 (2012), 819–828. doi: 10.1016/j.sigpro.2011.09.028
    [25] R. Calderbank, I. Daubechies, W. Sweldens, B. Yeo, Wavelet transforms that map integers to Integers, Appl. Comput. Harmonic Anal., 5 (1998), 332–369. doi: 10.1006/acha.1997.0238
    [26] L. L. Shen, X. F. Chen, Z. Q. Pan, K. Fan, F. Li, J. Lei, No-reference stereoscopic image quality assessment based on global and local content characteristics, Neurocomputing, 424 (2021), 132–142. doi: 10.1016/j.neucom.2020.10.024
    [27] Z. Q. Pan, X. K. Yi, Y. Zhang, H. Yu, F. L. Wang, S. Kwong, Frame-level bit allocation optimization based on video content characteristics for HEVC, ACM Trans. Multimedia Comput. Commun. Appl., 16 (2020), 1–20.
    [28] Z. Q. Pan, X. K. Yi, Y. Zhang, B. Jeon, S. Kwong, Efficient in-loop filtering based on enhanced deep convolutional neural networks for HEVC, IEEE Trans. Image Process., 29 (2020), 5352–5366. doi: 10.1109/TIP.2020.2982534
    [29] L. Bao, Y. Zhou, Image encryption: Generating visually meaningful encrypted images, Inf. Sci., 324 (2015), 197–207.
    [30] M. V. D. Veen, F. Bruekers, A. V. Leest, S. Cavin, High capacity reversible watermarking for audio, Security and Watermarking of Multimedia Contents V, International Society for Optics and Photonics, 2003.
    [31] A. Kanso, M. Ghebleh, An algorithm for encryption of secret images into meaningful images, Opt. Lasers Eng., 90 (2017), 196–208. doi: 10.1016/j.optlaseng.2016.10.009
    [32] Y. G. Yang, Y. C. Zhang, X. B. Chen, Y. H. Zhou, W. M. Shi, Eliminating the texture features in visually meaningful cipher images, Inf. Sci., 429 (2018), 102–119. doi: 10.1016/j.ins.2017.11.009
    [33] X. Chai, Z. Gan, Y. Chen, Y. Zhang, A visually secure image encryption scheme based on compressive sensing, Signal Process., 134 (2017), 35–51. doi: 10.1016/j.sigpro.2016.11.016
    [34] M. Barni, F. Bartolini, V. Cappellini, A. Lippi, A. Piva, DWT-based technique for spatio- frequency masking of digital signatures, Security and Watermarking of Multimedia Contents. International Society for Optics and Photonics, 1999.
    [35] N. Saravanan, K. I. Ramachandran, Incipient gear box fault diagnosis using discrete wavelet transform (DWT) for feature extraction and classification using artificial neural network (ANN), Expert Syst. Appl., 37 (2010), 4168–4181. doi: 10.1016/j.eswa.2009.11.006
    [36] V. Sachnev, H. J. Kim, J. Nam, S. Suresh, Y. Q. Shi, Reversible watermarking algorithm using sorting and prediction. IEEE Trans. Circuits Syst. Video Technol., 19 (2009), 989–999.
    [37] Boss Base Image Database, 2018. Available from: http://agents.fel.cvut.cz/stegodata/RAWs.
    [38] M. Zeng, Y. Li, Q. Meng, T. Yang, J. Liu, Improving histogram-based image contrast enhancement using gray-level information histogram with application to X-ray images, Optik, 123 (2012), 511–520. doi: 10.1016/j.ijleo.2011.05.017
    [39] H. Yao, X. Liu, Z. Tang, C. Qin, Y. Tian, Adaptive image camouflage using human visual system model, Multimedia Tools Appl., 78 (2019), 8311–8334. doi: 10.1007/s11042-018-6813-8
    [40] Z. Wang, A. C. Bovik, H. R. Sheikh, E. P. Simoncelli, Image quality assessment: from error visibility to structural similarity, IEEE Trans. Image Process., 13 (2004), 600–612. doi: 10.1109/TIP.2003.819861
    [41] L. Kamstra, H. J. A. M. Heijmans, Reversible data embedding into images using wavelet techniques and sorting, IEEE Trans. Image Process., 14 (2005), 2082–2090. doi: 10.1109/TIP.2005.859373
    [42] Y. Luo, M. Du, J. Liu, A symmetrical image encryption scheme in wavelet and time domain, Commun. Nonlinear Sci. Numer. Simul., 20 (2015), 447–460. doi: 10.1016/j.cnsns.2014.05.022
    [43] J. O. Armijo-Correa, J. S. Murguía, and M. Mejía-Carlos, V. E. Arce-Guevara, J. A. Aboytes-González, An improved visually meaningful encrypted image scheme, Opt. Laser Technol., 127 (2020), 106165.
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