A secure image steganography based on Hamming codes and image block complexity estimation using a zig-zag order
DOI:
https://doi.org/10.54654/isj.v2i25.1123Keywords:
Hamming codes, Image Steganography, Block Complexity Estimation, Zig-zag Order, Universal Steganalysis, Bit-plane decomposition, Security, Canonical Gray CodeTóm tắt
Data hiding in digital images has received considerable attention in recent years. Research efforts have primarily focused on increasing embedding capacity while preserving the visual quality of stego-images. In this paper, we propose a data hiding scheme based on Hamming codes. To enhance visual quality, the scheme estimates block complexity from pairs of adjacent pixels arranged in zig-zag order and uses this measure to identify high-texture regions for embedding message bits. To further minimize distortion, secret bits are embedded using the proposed Hamming code-based method. Moreover, embedding capacity is increased by utilizing multiple pixel bit-planes. A Canonical Gray Code (CGC) is employed in the bit-plane decomposition process to improve the accuracy of texture characterization in data hiding. Experimental results demonstrate that the proposed scheme achieves higher embedding capacity, improved visual quality, and stronger resistance to detection attacks.
Downloads
References
V. T. Son and T. M. Duc, “A robust watermarking method based on rdwt-dct-svd in the ycbcr color space,” Journal of Science and Technology on Information security, pp. 5–14, Dec. 2024. DOI: http://dx.doi.org/10.54654/isj.v3i23.1054
D. Gr¯ıbermans, A. Jersovs, and P. Rusakovs, ˇ “Development of requirements specification for steganographic systems,” Applied Computer Systems, vol. 20, no. 1, pp. 40–48, Dec. 2016. DOI: http://dx.doi.org/10.1515/acss-2016-0014
S. Kumar, A. Singh, and M. Kumar, “Information hiding with adaptive steganography based on novel fuzzy edge identification,” Defence Technology, vol. 15, no. 2, pp. 162–169, Apr. 2019. DOI: http://dx.doi.org/10.1016/j.dt.2018.08.003
B. Ray, S. Mukhopadhyay, S. Hossain, S. K. Ghosal, and R. Sarkar, “Image steganography using deep learning based edge detection,” Multimedia Tools and Applications, vol. 80, no. 24, pp. 33 475–33 503, Aug. 2021. DOI: http://dx.doi.org/10.1007/s11042-021-11177-4
K. Gaurav and U. Ghanekar, “Image steganography based on canny edge detection, dilation operator and hybrid coding,” Journal of Information Security and Applications, vol. 41, pp. 41–51, Aug. 2018. DOI: http://dx.doi.org/10.1016/j.jisa.2018.05.001.
S.-Y. Shen and L.-H. Huang, “A data hiding scheme using pixel value differencing and improving exploiting modification directions,” Computers & Security, vol. 48, pp. 131–141, Feb. 2015. DOI: http://dx.doi.org/10.1016/j.cose.2014.07.008
H. Al-Dmour and A. Al-Ani, “A steganography embedding method based on edge identification and xor coding,” Expert Systems with Applications, vol. 46, pp. 293–306, Mar. 2016. DOI: http://dx.doi.org/10.1016/j.eswa.2015.10.024
W.-J. Chen, C.-C. Chang, and T. H. N. Le, “High payload steganography mechanism using hybrid edge detector,” Expert Systems with Applications, vol. 37, no. 4, pp. 3292–3301, Apr. 2010. DOI: http://dx.doi.org/10.1016/j.eswa.2009.09.050
S. Islam, M. R. Modi, and P. Gupta, “Edgebased image steganography,” EURASIP Journal on Information Security, vol. 2014, no. 1, Apr. 2014. DOI: http://dx.doi.org/10.1186/1687-417x-2014-8
D. R. I. M. Setiadi, “Improved payload capacity in lsb image steganography uses dilated hybrid edge detection,” Journal of King Saud University - Computer and Information Sciences, vol. 34, no. 2, pp. 104–114, Feb. 2022. DOI: http://dx.doi.org/10.1016/j.jksuci.2019.12.007
C. Kim and C.-N. Yang, “Data hiding based on overlapped pixels using hamming code,” Multimedia Tools and Applications, vol. 75, no. 23, pp. 15 651–15 663, Nov. 2014. DOI: http://dx.doi.org/10.1007/s11042-014-2355-x
B. Jana, D. Giri, and S. Kumar Mondal, “Dual image based reversible data hiding scheme using (7,4) hamming code,” Multimedia Tools and Applications, vol. 77, no. 1, pp. 763–785, Jan. 2017. DOI: http://dx.doi.org/10.1007/s11042-016-4230-4
C. Kim, D. Shin, C.-N. Yang, and Y.-S. Chou, “Improving capacity of Hamming (n,k) + 1 stego-code by using optimized Hamming + k,” Digital Signal Processing, vol. 78, pp. 284–293, Jul. 2018. DOI: http://dx.doi.org/10.1016/j.dsp.2018.03.016
C.-F. Lee, C.-C. Chang, X. Xie, K. Mao, and R.-H. Shi, “An adaptive high-fidelity steganographic scheme using edge detection and hybrid hamming codes,” Displays, vol. 53, pp. 30–39, Jul. 2018. DOI: http://dx.doi.org/10.1016/j.displa.2018.06.001
W. Luo, F. Huang, and J. Huang, “Edge adaptive image steganography based on lsb matching revisited,” IEEE Transactions on Information Forensics and Security, vol. 5, no. 2, pp. 201–214, Jun. 2010. DOI: http://dx.doi.org/10.1109/tifs.2010.2041812
E. Kawaguchi and R. O. Eason, “Principles and applications of bpcs steganography,” in Multimedia systems and applications, vol. 3528. SPIE, 1999, pp. 464–473.
S. Sun, “A new information hiding method based on improved bpcs steganography,” Advances in Multimedia, vol. 2015, pp. 1–7, 2015. DOI: http://dx.doi.org/10.1155/2015/698492
F. Andrieux and C. Deltel, “Jpeg steganography using bpcs,” in Proceedings of the 20th Annual SIG Conference on Information Technology Education, ser. SIGITE ’19. ACM, Sep. 2019, pp. 163–163. DOI: http://dx.doi.org/10.1145/3349266.3351383
V. Sabeti, S. Samavi, and S. Shirani, “An adaptive lsb matching steganography based on octonary complexity measure,” Multimedia Tools and Applications, vol. 64, no. 3, pp. 777–793, Jan. 2012. DOI: http://dx.doi.org/10.1007/s11042-011-0975-y
C. Munuera, “Hamming codes for wet paper steganography,” Designs, Codes and Cryptography, vol. 76, no. 1, pp. 101–111, 2014. DOI: http://dx.doi.org/10.1007/s10623-014-9998-5
Y. Kim, Z. Duric, and D. Richards, Modified Matrix Encoding Technique for Minimal Distortion Steganography. Springer Berlin Heidelberg, 2007, pp. 314–327. DOI: http://dx.doi.org/10.1007/978-3-540-74124-4_21
F. Huang, J. Huang, and Y.-Q. Shi, “New channel selection rule for jpeg steganography,” IEEE Transactions on Information Forensics and Security, vol. 7, no. 4, pp. 1181–1191, Aug. 2012. DOI: http://dx.doi.org/10.1109/tifs.2012.2198213
Y. Zhong, F. Huang, and D. Zhang, New Channel Selection Criterion for Spatial Domain Steganography. Springer Berlin Heidelberg, 2013, pp. 1–7. DOI: http://dx.doi.org/10.1007/978-3-642-40099-5_1
S. Mozaffari, “Parallel image encryption with bitplane decomposition and genetic algorithm,” Multimedia Tools and Applications, vol. 77, no. 19, pp. 25 799–25 819, Apr. 2018. DOI: http://dx.doi.org/10.1007/s11042-018-5817-8
T. D. Nguyen and H. D. Le, “A reversible data hiding scheme based on (5, 3) hamming code using extra information on overlapped pixel blocks of grayscale images,” Multimedia Tools and Applications, vol. 80, no. 9, pp. 13 099–13 120, Jan. 2021. DOI: http://dx.doi.org/10.1007/s11042-020-10347-0
A. Saeed, Fawad, M. J. Khan, H. Shahid, S. I. Naqvi, M. A. Riaz, M. S. Khan, and Y. Amin, “An accurate texture complexity estimation for qualityenhanced and secure image steganography,” IEEE Access, vol. 8, pp. 21 613–21 630, 2020. DOI:
http://dx.doi.org/10.1109/access.2020.2968217
D. Laishram and T. Tuithung, “A novel minimal distortion-based edge adaptive image steganography scheme using local complexity: (beass),” Multimedia Tools and Applications, vol. 80, no. 1, pp. 831–854, Sep. 2020. DOI: http://dx.doi.org/10.1007/s11042-020-09519-9
Z. Wang, A. Bovik, H. Sheikh, and E. Simoncelli, “Image quality assessment: from error visibility to
structural similarity,” IEEE Transactions on Image Processing, vol. 13, no. 4, pp. 600–612, Apr. 2004. DOI: http://dx.doi.org/10.1109/tip.2003.819861
J. J. Ranjani and F. Zaid, “Pseudo magic cubes: A multidimensional data hiding scheme exploiting modification directions for large payloads,” Computers & Electrical Engineering, vol. 89, p. 106928, Jan. 2021. DOI: http://dx.doi.org/10.1016/j.compeleceng.2020.106928.
C. Kim, D. Shin, B.-G. Kim, and C.-N. Yang, “Secure medical images based on data hiding using a hybrid scheme with the hamming code, lsb, and opap,” Journal of Real-Time Image Processing, vol. 14, no. 1, pp. 115–126, Feb. 2017. DOI: http://dx.doi.org/10.1007/s11554-017-0674-7
A. Munoz, ˜ “Stegsecret. a simple steganalysis tool.” , (2007), accessed: 22/9/2025, http:// stegsecret.sourceforge.net/.
J. Kodovsky, J. Fridrich, and V. Holub, “Ensemble classifiers for steganalysis of digital media,” IEEE Transactions on Information Forensics and Security, vol. 7, no. 2, pp. 432–444, Apr. 2012. DOI: http://dx.doi.org/10.1109/tifs.2011.2175919
Q. Li, G. Feng, H. Wu, and X. Zhang, Ensemble Steganalysis Based on Deep Residual Network. Springer International Publishing, 2020, pp. 84–95. DOI: http://dx.doi.org/10.1007/978-3-030-43575-2_7
T. Pevny, P. Bas, and J. Fridrich, “Steganalysis by subtractive pixel adjacency matrix,” IEEE Transactions on Information Forensics and Security, vol. 5, no. 2, pp. 215–224, Jun. 2010. DOI: http://dx.doi.org/10.1109/tifs.2010.2045842
G. Xu, H.-Z. Wu, and Y.-Q. Shi, “Structural design of convolutional neural networks for steganalysis,” IEEE Signal Processing Letters, vol. 23, no. 5, pp. 708–712, May 2016. DOI: http://dx.doi.org/10.1109/LSP.2016.2548421
S. Brijesh, “XuNet: Structural design of convolutional neural networks for steganalysis,” (2016), Accessed: 2025-08-26, https://github.com/brijeshiitg/XuNet-Structural-Design-of-ConvolutionalNeural-Networksfor-Steganalysis/.
Downloads
Published
How to Cite
Issue
Section
License
Proposed Policy for Journals That Offer Open Access
Authors who publish with this journal agree to the following terms:
1. Authors retain copyright and grant the journal right of first publication with the work simultaneously licensed under a Creative Commons Attribution License that allows others to share the work with an acknowledgement of the work's authorship and initial publication in this journal.
2. Authors are able to enter into separate, additional contractual arrangements for the non-exclusive distribution of the journal's published version of the work (e.g., post it to an institutional repository or publish it in a book), with an acknowledgement of its initial publication in this journal.
3. Authors are permitted and encouraged to post their work online (e.g., in institutional repositories or on their website) prior to and during the submission process, as it can lead to productive exchanges, as well as earlier and greater citation of published work (See The Effect of Open Access).
Proposed Policy for Journals That Offer Delayed Open Access
Authors who publish with this journal agree to the following terms:
1. Authors retain copyright and grant the journal right of first publication, with the work [SPECIFY PERIOD OF TIME] after publication simultaneously licensed under a Creative Commons Attribution License that allows others to share the work with an acknowledgement of the work's authorship and initial publication in this journal.
2. Authors are able to enter into separate, additional contractual arrangements for the non-exclusive distribution of the journal's published version of the work (e.g., post it to an institutional repository or publish it in a book), with an acknowledgement of its initial publication in this journal.
3. Authors are permitted and encouraged to post their work online (e.g., in institutional repositories or on their website) prior to and during the submission process, as it can lead to productive exchanges, as well as earlier and greater citation of published work (See The Effect of Open Access).