Skip to main content
SpringerLink
Log in
Book cover

International Conference on Cloud Computing and Security

ICCCS 2017: Cloud Computing and Security pp 74–84Cite as

Improved CMD Adaptive Image Steganography Method

  • Conference paper
  • First Online:

  • 1787 Accesses

Part of the book series: Lecture Notes in Computer Science ((LNISA,volume 10602))

Abstract

With the rapid development of information communication, information security is becoming more and more important. As an important technology in the field of information security, image steganography has attracted wide attention. CMD (clustering modification directions) steganographic strategy has high security performance. The cover image is decomposed into several sub-images, and then the costs of pixels are updated dynamically and the pixel modification directions are clustered. However, the sub-image cannot completely exploit mutual embedding impacts. In this paper, we propose a new steganography method based on patched block. This strategy can make the post-processing sub-image be influenced by all the sub-images which have already embedded. The experimental results show that the proposed method is more secure than CMD image steganographic method.

This is a preview of subscription content, log in via an institution.

Chapter
USD   29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD   39.99
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD   54.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Learn about institutional subscriptions

Notes

  1. 1.

    If the patch as Fig. 3(c) is adopted, we can acquire that \(S_1=I_{1,1}\), \(S_2=I_{2,1}\), \(S_3=I_{1,2}\), \(S_4=I_{2,2}\). If the patch as Fig. 3(d) is used, we can acquire that \(S_1=I_{1,1}\), \(S_2=I_{2,1}\), \(S_3=I_{2,2}\), \(S_4=I_{1,2}\).

References

  1. Zhou, Z., Wang, Y., Wu, J., Yang, C., Sun, X.: Effective and efficient global context verification for image copy detection. IEEE Trans. Inf. Forensics Secur. 12, 48–63 (2017)

    Article  Google Scholar 

  2. Zhou, Z., Yang, C., Chen, B., Sun, X., Li, Q., Wu, J.: Effective and efficient image copy detection with resistance to arbitrary rotation. IEICE Trans. Inf. Syst. 99(6), 1531–1540 (2016)

    Article  Google Scholar 

  3. Pan, Z., Lei, J., Zhang, Y., Sun, X., Sam, K.: Fast motion estimation based on content property for low-complexity H.265/HEVC encoder. IEEE Trans. Broadcast. 62, 675–684 (2016)

    Article  Google Scholar 

  4. Xia, Z., Xiong, N., Vasilakos, A.V., Sun, X.: EPCBIR: an efficient and privacy-preserving content-based image retrieval scheme in cloud computing. Inf. Sci. 387, 195–204 (2017)

    Article  Google Scholar 

  5. Xia, Z., Wang, X., Zhang, L., Qin, Z., Sun, X., Ren, K.A.: Privacy-preserving and copy-deterrence content-based image retrieval scheme in cloud computing. IEEE Trans. Inf. Forensics Secur. 11, 2594–2608 (2016)

    Article  Google Scholar 

  6. Xia, Z., Zhu, Y., Sun, X., Qin, Z., Ren, K.: Towards privacy-preserving content-based image retrieval in cloud computing. IEEE Trans. Cloud Comput. 99, 1–1 (2015)

    Article  Google Scholar 

  7. Xiong, L., Xu, Z., Xu, Y.: A secure re-encryption scheme for data services in a cloud computing environment. Concur. Comput. Pract. Exp. 27, 4573–4585 (2015)

    Article  Google Scholar 

  8. Fu, Z., Sun, X., Ji, S., Xie, G.: Towards efficient content-aware search over encrypted outsourced data in cloud. In: IEEE International Conference on Computer Communications, pp. 1–9. IEEE Press, Brest (2016)

    Google Scholar 

  9. Xia, Z., Lv, R., Zhu, Y., Ji, P., Sun, H., Shi, Y.Q.: Fingerprint liveness detection using gradient-based texture features. Sig. Image Video Proc. 11, 381–388 (2017)

    Article  Google Scholar 

  10. Chen, X., Sun, X., Zhou, Z., Zhang, J.: Reversible watermarking method based on asymmetric-histogram shifting of prediction errors. J. Syst. Softw. 86, 2620–2626 (2013)

    Article  Google Scholar 

  11. Liao, X., Shu, C.: Reversible data hiding in encrypted images based on absolute mean difference of multiple neighboring pixels. J. Vis. Commun. Image Representation 28, 21–27 (2015)

    Article  Google Scholar 

  12. Anderson, R.J., Petitcolas, F.A.: On the limits of steganography. IEEE J. Sel. Areas Commun. 16, 474–481 (1998)

    Article  Google Scholar 

  13. Cox, I.J., Miller, M.L., Bloom, J.A., Fridrich, J., Kalker, T.: Digital Watermarking and Steganography, 2nd edn. Morgan Kaufmann, San Francisco (2008)

    Google Scholar 

  14. Fridrich, J.: Minimizing the embedding impact in steganography. In: 8th ACM Workshop Multimedia Secur, Geneva, Switzerland, pp. 2–10 (2006)

    Google Scholar 

  15. Filler, T., Judas, J., Fridrich, J.: Minimizing additive distortion in steganography using syndrome-trellis codes. IEEE Trans. Inf. Forensics Secur. 6, 920–935 (2011)

    Article  Google Scholar 

  16. Pevný, T., Filler, T., Bas, P.: Using high-dimensional image models to perform highly undetectable steganography. In: Böhme, R., Fong, P.W.L., Safavi-Naini, R. (eds.) IH 2010. LNCS, vol. 6387, pp. 161–177. Springer, Heidelberg (2010). doi:10.1007/978-3-642-16435-4_13

    Chapter  Google Scholar 

  17. Holub, V., Fridrich, J.: Designing steganographic distortion using directional filters. In: 2012 IEEE International Workshop on Information Forensics and Security, pp. 234–239. IEEE Press, Tenerife (2012)

    Google Scholar 

  18. Liao, X., Chen, G., Li, Q.: Improved WOW adaptive image steganography method. In: 15th IEEE International Conference on Algorithms and Architectures for Parallel Processing, pp. 685–702. IEEE Press, ChangSha (2015)

    Google Scholar 

  19. Holub, V., Fridrich, J., Denemark, T.: Universal distortion function for steganography in an arbitrary domain. EURASIP J. Inf. Secur. 2014, 1–13 (2014)

    Article  Google Scholar 

  20. Li, B., Wang, M., Huang, J., Li, X.: A new cost function for spatial image steganography. In: IEEE International Conference on Image Process, pp. 4026–4210. IEEE Press, Paris (2014)

    Google Scholar 

  21. Li, B., Wang, M., Li, X., Tan, S.: A strategy of clustering modification directions in spatial image steganography. IEEE Trans. Inf. Forensics Secur. 10, 1905–1917 (2015)

    Article  Google Scholar 

  22. Hong, W.: Adaptive image data hiding in edges using patched reference table and pair-wise embedding technique. Inf. Sci. 221, 473–489 (2013)

    Article  Google Scholar 

  23. Bas, P., Filler, T., Pevný, T.: “Break Our Steganographic System”: the ins and outs of organizing BOSS. In: Filler, T., Pevný, T., Craver, S., Ker, A. (eds.) IH 2011. LNCS, vol. 6958, pp. 59–70. Springer, Heidelberg (2011). doi:10.1007/978-3-642-24178-9_5

    Chapter  Google Scholar 

  24. Fridrich, J., Kodovsk, J.: Rich models for steganalysis of digital images. IEEE Trans. Inf. Foren. Secur. 7, 868–882 (2012)

    Article  Google Scholar 

  25. Kodovsk, J., Fridrich, J., Holub, V.: Ensemble classifiers for steganalysis of digital media. IEEE Trans. Inf. Foren. Secur. 7, 432–444 (2012)

    Article  Google Scholar 

Download references

Acknowledgments

This work is supported by National Natural Science Foundation of China (Grant Nos. 61402162, 61572182, 61370225, 61472131, 61272546), Hunan Provincial Natural Science Foundation of China (Grant No. 2017JJ3040), Specialized Research Fund for the Doctoral Program of Higher Education (Grant No. 20130161120004), Science and Technology Key Projects of Hunan Province (Grant Nos. 2015TP1004, 2016JC2012), Opening Project of Shanghai Key Laboratory of Integrated Administration Technologies for Information Security (Grant No. AGK201605).

Author information

Authors and Affiliations

  1. College of Computer Science and Electronic Engineering, Hunan University, Changsha, 410082, China

    Yingbo Yu & Xin Liao

  2. Shenzhen Key Laboratory of Media Security, Shenzhen University, Shenzhen, 518060, China

    Xin Liao

Authors
  1. Yingbo Yu
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Xin Liao
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Xin Liao .

Editor information

Editors and Affiliations

  1. Nanjing University of Information Science and Technology, Nanjing, China

    Xingming Sun

  2. National Dong Hwa University, Shoufeng, Taiwan

    Han-Chieh Chao

  3. China Information Technology Security Evaluation Center, Nanjing, China

    Xingang You

  4. Department of Computer Science, Purdue University, West Lafayette, Indiana, USA

    Elisa Bertino

Rights and permissions

Reprints and permissions

Copyright information

© 2017 Springer International Publishing AG

About this paper

Check for updates. Verify currency and authenticity via CrossMark

Cite this paper

Yu, Y., Liao, X. (2017). Improved CMD Adaptive Image Steganography Method. In: Sun, X., Chao, HC., You, X., Bertino, E. (eds) Cloud Computing and Security. ICCCS 2017. Lecture Notes in Computer Science(), vol 10602. Springer, Cham. https://doi.org/10.1007/978-3-319-68505-2_7

Download citation

  • DOI: https://doi.org/10.1007/978-3-319-68505-2_7

  • Published:

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-68504-5

  • Online ISBN: 978-3-319-68505-2

  • eBook Packages: Computer ScienceComputer Science (R0)

Publish with us

Policies and ethics

Search

Navigation