Research article

AMBTC-based visual secret sharing with different meaningful shadows

  • Received: 12 March 2021 Accepted: 04 June 2021 Published: 11 June 2021
  • Secret sharing based on Absolute Moment Block Truncation Coding (AMBTC) has been widely studied. However, the management of stego images is inconvenient as they seem indistinguishable. Moreover, there exists a problem of pixel expansion, which requires more storage space and higher transmission bandwidth. To conveniently manage the stego images, we use multiple cover images to make the stego images seem to be visually different from with each other. Futhermore, the stego images are different, which will not cause the attacker's suspicion and increase the security of the scheme. And traditional Visual Secret Sharing (VSS) is fused to eliminate pixel expansion. After images are compressed by AMBTC algorithm, the quantization levels and the bitmap corresponding to each block are obtained. At the same time, when the threshold is $ (k, k) $, bitmaps can be recovered losslessly, and the slight degradation of image quality is only caused by the compression itself. When the threshold is another value, the recovered image and the cover images can be recovered with satisfactory image quality. The experimental results and analyses show the effectiveness and advantages of our scheme.

    Citation: Shudong Wang, Yuliang Lu, Xuehu Yan, Longlong Li, Yongqiang Yu. AMBTC-based visual secret sharing with different meaningful shadows[J]. Mathematical Biosciences and Engineering, 2021, 18(5): 5236-5251. doi: 10.3934/mbe.2021266

    Related Papers:

  • Secret sharing based on Absolute Moment Block Truncation Coding (AMBTC) has been widely studied. However, the management of stego images is inconvenient as they seem indistinguishable. Moreover, there exists a problem of pixel expansion, which requires more storage space and higher transmission bandwidth. To conveniently manage the stego images, we use multiple cover images to make the stego images seem to be visually different from with each other. Futhermore, the stego images are different, which will not cause the attacker's suspicion and increase the security of the scheme. And traditional Visual Secret Sharing (VSS) is fused to eliminate pixel expansion. After images are compressed by AMBTC algorithm, the quantization levels and the bitmap corresponding to each block are obtained. At the same time, when the threshold is $ (k, k) $, bitmaps can be recovered losslessly, and the slight degradation of image quality is only caused by the compression itself. When the threshold is another value, the recovered image and the cover images can be recovered with satisfactory image quality. The experimental results and analyses show the effectiveness and advantages of our scheme.



    加载中


    [1] R. I. Yousif, N. H. Salman, Image compression based on arithmetic coding algorithm, Iraqi J. Sci., 2021 (2021), 329-334.
    [2] S. Kim, D. Lee, J. S. Kim, H. J. Lee, A block truncation coding algorithm and hardware implementation targeting 1/12 compression for lcd overdrive, J. Display Technol., 12 (2015), 376-389.
    [3] V. Holub, J. Fridrich, Low-complexity features for jpeg steganalysis using undecimated dct, IEEE Trans. Infor. Forensics Secur., 10 (2015), 219-228.
    [4] R. Starosolski, Skipping selected steps of dwt computation in lossless jpeg 2000 for improved bitrates, Plos One, 11 (2016), e0168704. doi: 10.1371/journal.pone.0168704
    [5] X. Wu, D. Chen, C. N. Yang, Y. Y. Yang, A (k, n) threshold partial reversible ambtc-based visual cryptography using one reference image, J. Visual Commun. Image Representation, 59 (2019), 550-562. doi: 10.1016/j.jvcir.2019.02.008
    [6] M. Ebadi, A. Ebrahimi, Video data compression by progressive iterative approximation, Int. J. Interact. Multimedia Artif. Intell., 6 (2020), 89-195.
    [7] A. Ab, B. An, C. Tg, Deep learning-based appearance features extraction for automated carp species identification, Aquacultural Eng., 89 (2020), 102053. doi: 10.1016/j.aquaeng.2020.102053
    [8] J. Wei, B. Ling, K. W. Chau, L. Heutte, Palmprint identification using restricted fusion-sciencedirect, Appl. Math. Comput., 205 (2008), 927-9348.
    [9] S. Shamshirband, T. Rabczuk, K. W. Chau, A survey of deep learning techniques: Application in wind and solar energy resources, IEEE Access, 7 (2019), 164650-164666. doi: 10.1109/ACCESS.2019.2951750
    [10] C. L. Wu, K. W. Chau, Prediction of rainfall time series using modular soft computingmethods, Eng. Appl. Artif. Intell., 26 (2013), 997-1007. doi: 10.1016/j.engappai.2012.05.023
    [11] Y. Wu, Q. Wu, N. Dey, R. S. Sherratt, Learning models for semantic classification of insufficient plantar pressure images, Int. J. Interact. Multimedia Artif. Intell., 6 (2020), 51-61.
    [12] G. Ye, K. 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. Bifurcations Chaos, 30 (2020), 2050233. doi: 10.1142/S0218127420502338
    [13] J. Zhou, N. R. Zhou, L. H. Gong, Fast color image encryption scheme based on 3d orthogonal latin squares and matching matrix, Optics Laser Technol., 131 (2020), 106437. doi: 10.1016/j.optlastec.2020.106437
    [14] A. Shamir, How to share a secret, Commun. ACM, 22 (1979), 612-613.
    [15] G. R. Blakley, Safeguarding cryptographic keys, in 1979 International Workshop on Managing Requirements Knowledge, IEEE Computer Society, 1979.
    [16] M. Naor, A. Shamir, Visual cryptography, Lect. Notes Comput. Sci., 1994 (1994), 1-12.
    [17] H. B. Chen, H. C. Hsu, S. T. Juan, An easy-to-implement construction for $(k, n)$-threshold progressive visual secret sharing schemes, preprint, arXiv: 2002.09125.
    [18] R. De Prisco, A. De Santis, On the relation of random grid and deterministic visual cryptography, Inf. Forensics Secur. IEEE Trans., 9 (2014), 653-665. doi: 10.1109/TIFS.2014.2305574
    [19] C. N. Yang, C. C. Wu, D. S. Wang, A discussion on the relationship between probabilistic visual cryptography and random grid, Inf. Sci., 278 (2017), 141-173.
    [20] O. Kafri, E. Keren, Encryption of pictures and shapes by random grids, Optics Lett., 12 (1987), 377. doi: 10.1364/OL.12.000377
    [21] X. Yan, X. Liu, C. N. Yang, An enhanced threshold visual secret sharing based on random grids, J. Real Time Image Proc., 14 (2018), 61-73. doi: 10.1007/s11554-015-0540-4
    [22] X. Wu, W. Sun, Improved tagged visual cryptography by random grids, Signal Proc., 97 (2014), 64-82. doi: 10.1016/j.sigpro.2013.10.023
    [23] T. Guo, F. Liu, C. K. Wu, K out of k extended visual cryptography scheme by random grids, Signal Proc., 94 (2014), 90-101. doi: 10.1016/j.sigpro.2013.06.003
    [24] X. Yan, S. Wang, X. Niu, C. N. Yang, Halftone visual cryptography with minimum auxiliary black pixels and uniform image quality, Digital Signal Proc., 38 (2015), 53-65. doi: 10.1016/j.dsp.2014.12.002
    [25] X. Yan, W. Q. Yan, L. Liu, Y. Lu, Penrose tiling for visual secret sharing, Multimedia Tools Appl., 79 (2020), 32693-32710. doi: 10.1007/s11042-020-09568-0
    [26] G. Ye, C. Pan, Y. Dong, K. Jiao, X. Huang, A novel multi-image visually meaningful encryption algorithm based on compressive sensing and schur decomposition, Trans. Emerging Telecommun. Technol., 32 (2021), e4071.
    [27] C. N. Yang, X. Wu, Y. C. Chou, Z. Fu, Constructions of general (k, n) reversible ambtc-based visual cryptography with two decryption options, J. Visual Commun. Image Representation, 48 (2017), 182-194. doi: 10.1016/j.jvcir.2017.06.012
    [28] X. Wu, C. N. Yang, Invertible secret image sharing with steganography and authentication for ambtc compressed images, Signal Proce. Image Commun., 78 (2019), 437-447. doi: 10.1016/j.image.2019.08.007
    [29] X. Wu, C. N. Yang, Partial reversible ambtc-based secret image sharing with steganography, Digital Signal Proc., 93 (2019), 22-33. doi: 10.1016/j.dsp.2019.06.016
    [30] D. Ou, W. Sun, Reversible ambtc-based secret sharing scheme with abilities of two decryptions, J. Visual Commun. Image Representation, 25 (2014), 1222-1239. doi: 10.1016/j.jvcir.2013.12.018
    [31] X. Yan, Y. Lu, L. Liu, X. Song, Reversible image secret sharing, IEEE Trans. Inf. Forensics Secur., 15 (2020), 3848-3858.
    [32] D. M. Liou, Y. Huang, N. Reynolds, A new microcomputer based imaging system with technique, in IEEE Region 10 Conference on Computer and Communication Systems, 2002.
    [33] D. Healym O. Mitchell, Digital video bandwidth compression using block truncation coding, IEEE Trans. Commun., 29 (1981), 1809-1817. doi: 10.1109/TCOM.1981.1094938
    [34] D. Wang, T. Song, L. Dong, C. Yang, Optimal contrast grayscale visual cryptography schemes with reversing, IEEE Trans. Inf. Forensics Secur., 8 (2013), 2059-2072. doi: 10.1109/TIFS.2013.2281108
    [35] T. H. Chen, K. H. Tsao, Threshold visual secret sharing by random grids, J. Syst. Software, 84 (2011), 1197-1208. doi: 10.1016/j.jss.2011.02.023
  • Reader Comments
  • © 2021 the Author(s), licensee AIMS Press. This is an open access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0)
通讯作者: 陈斌, bchen63@163.com
  • 1. 

    沈阳化工大学材料科学与工程学院 沈阳 110142

  1. 本站搜索
  2. 百度学术搜索
  3. 万方数据库搜索
  4. CNKI搜索

Metrics

Article views(2621) PDF downloads(80) Cited by(2)

Article outline

Figures and Tables

Figures(4)  /  Tables(5)

/

DownLoad:  Full-Size Img  PowerPoint
Return
Return

Catalog