Location via proxy:   [ UP ]  
[Report a bug]   [Manage cookies]                
Skip to main content

Advertisement

Springer Nature Link
Log in

A cover selection-based reversible data hiding method by learning cross-modal hashing

  • Published:
Multimedia Tools and Applications Aims and scope Submit manuscript

Abstract

With the rapid development of the Internet, various ways of transmitting data have emerged, such as cloud and social applications. However, these data transmission ways with different network conditions have different effects on data hiding. To solve the problem of data hiding in different network transmission conditions, a cover selection-based reversible data hiding (RDH) method by learning cross-modal hashing was proposed in this paper. In the proposed method, images and audio are selected to carry messages according to the transmission environment. A cross-modal hashing method was adopted and an information expansion model was established to build the connection between images, audio, and secret messages. When the cover is selected, the prediction error expansion (PEE)-based method for images and the histogram shifting (HS)-based method for audio is applied to embed messages. Experimental results show that our method can achieve high embedding efficiency, visual quality for images, and auditory quality for audio, respectively.

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

Access this article

Log in via an institution

Subscribe and save

Springer+ Basic
$34.99 /Month
  • Get 10 units per month
  • Download Article/Chapter or eBook
  • 1 Unit = 1 Article or 1 Chapter
  • Cancel anytime
Subscribe now

Buy Now

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5
Fig. 6
Fig. 7
Fig. 8
Fig. 9
Fig. 10
Fig. 11
Fig. 12

Similar content being viewed by others

References

  1. Abdulla AA (2015) Exploiting similarities between secret and cover images for improved embedding efficiency and security in digital steganography, Phd Thesis University of Buckingham

  2. Abdulla AA, Jassim SA, Sellahewa H (2013) Secure steganography technique based on bitplane indexes. In: 2013 IEEE International symposium on multimedia. IEEE, pp 287–291

  3. Abdulla AA, Sellahewa H, Jassim SA (2014) Stego quality enhancement by message size reduction and fibonacci bit-plane mapping. In: International conference on research in security standardisation. Springer, pp 151–166

  4. Blei DM, Ng AY, Jordan MI, Lafferty J (2003) Latent dirichlet allocation. J Mach Learn Res 3:993–1022

    MATH  Google Scholar 

  5. Chan C-K, Cheng LM (2004) Hiding data in images by simple lsb substitution. Pattern Recogn 37(3):469–474

    Article  MATH  Google Scholar 

  6. Chang Q, Li X, Zhao Y, Ni R (2021) Adaptive pairwise prediction-error expansion and multiple histograms modification for reversible data hiding. IEEE Transactions on Circuits and Systems for Video Technology

  7. Chua T-S, Tang J, Hong R, Li H, Luo Z, Zheng Y (2009) Nus-wide: A real-world web image database from national university of singapore. In: Proceedings of the ACM international conference on image and video retrieval, CIVR ’09. Association for Computing Machinery, New York

  8. Coatrieux G, Le Guillou C, Cauvin J, Roux C (2009) Reversible watermarking for knowledge digest embedding and reliability control in medical images. IEEE Trans Inf Technol Biomed 13(2):158–165

    Article  Google Scholar 

  9. Faragallah OS, Elaskily MA, Alenezi AF, El-sayed HS, Kelash HM (2021) Quadruple histogram shifting-based reversible information hiding approach for digital images. Multimed Tools Appl, 1–21

  10. He W, Cai Z (2021) Reversible data hiding based on dual pairwise prediction-error expansion. IEEE Trans Image Process 30:5045–5055

    Article  Google Scholar 

  11. Hou D, Wang H, Zhang W, Yu N (2018) Reversible data hiding in jpeg image based on dct frequency and block selection. Signal Process 148:41–47

    Article  Google Scholar 

  12. Hou D, Zhang W, Chen K, Lin S, Yu N (2019) Reversible data hiding in color image with grayscale invariance. IEEE Trans Circuits Syst Video Technol 29(2):363–374

    Article  Google Scholar 

  13. Hou D, Zhang W, Yang Y, Yu N (2018) Reversible data hiding under inconsistent distortion metrics. IEEE Trans Image Process 27 (10):5087–5099

    Article  MathSciNet  MATH  Google Scholar 

  14. Hu R, Xiang S (2021) Reversible data hiding by using cnn prediction and adaptive embedding. IEEE Transactions on Pattern Analysis and Machine Intelligence

  15. Huang F, Qu X, Kim HJ, Huang J (2016) Reversible data hiding in jpeg images. IEEE Trans Circuits Syst Video Technol 26(9):1610–1621

    Article  Google Scholar 

  16. Huiskes MJ, Lew MS (2008) The mir flickr retrieval evaluation. Association for Computing Machinery, New York, pp 39–43

    Google Scholar 

  17. Ke Y, Zhang MQ, Liu J, Su TT, Yang XY (2020) Fully homomorphic encryption encapsulated difference expansion for reversible data hiding in encrypted domain. IEEE Trans Circuits Syst Video Technol 30(8):2353–2365

    Article  Google Scholar 

  18. Kim S, Qu X, Sachnev V, Kim HJ (2019) Skewed histogram shifting for reversible data hiding using a pair of extreme predictions. IEEE Trans Circuits Syst Video Technol 29(11):3236–3246

    Article  Google Scholar 

  19. Lee S-H, Lee E-J, Hwang W-J, Kwon K-R (2018) Reversible dna data hiding using multiple difference expansions for dna authentication and storage. Multimed Tools Appl 77(15):19499–19526

    Article  Google Scholar 

  20. Lee S, Yoo CD, Kalker T (2007) Reversible image watermarking based on integer-to-integer wavelet transform. IEEE Trans Inform Forensic Secur 2 (3):321–330

    Article  Google Scholar 

  21. Li S, Hu L, Sun C, Chi L, Li T, Li H (2020) A reversible data hiding algorithm based on prediction error with large amounts of data hiding in spatial domain, vol 8

  22. Liu Y, Shen Y, Liu Q, Shi R, Yang H, Yang D, Sang L (2013) Performance evaluation and accuracy upgrading of pesq in chinese environment. In: 2013 IEEE 77Th vehicular technology conference (VTC spring), pp 1–5

  23. Lowe DG (1999) Object recognition from local scale-invariant features. In: Proceedings of the Seventh IEEE international conference on computer vision, volume 2, pp 1150–1157 vol 2

  24. Ni Z, Shi Y-Q, Ansari N, Su W (2006) Reversible data hiding. IEEE Trans Circuits Syst Video Technol 16(3):354–362

    Article  Google Scholar 

  25. Ou B, Li X, Zhang W, Zhao Y (2019) Improving pairwise pee via hybrid-dimensional histogram generation and adaptive mapping selection. IEEE Trans Circuits Syst Video Technol 29(7):2176–2190

    Article  Google Scholar 

  26. Ou B, Li X, Zhao Y, Ni R, Shi Y (2013) Pairwise prediction-error expansion for efficient reversible data hiding. IEEE Trans Image Process 22(12):5010–5021

    Article  MathSciNet  MATH  Google Scholar 

  27. Ou B, Zhao Y (2020) High capacity reversible data hiding based on multiple histograms modification. IEEE Trans Circuits Syst Video Technol 30 (8):2329–2342

    Article  Google Scholar 

  28. Pan Z, Gao X, Wang L, Gao E (2020) Effective reversible data hiding using dynamic neighboring pixels prediction based on prediction-error histogram. Multimed Tools Appl, 1–27

  29. Rasiwasia N, Pereira JC, Coviello E, Doyle G, Lanckriet GRG, Levy R, Vasconcelos N (2010) A new approach to cross-modal multimedia retrieval. Association for Computing Machinery, New York, pp 251–260

    Google Scholar 

  30. Shi Y, Li X, Zhang X, Wu H, Ma B (2016) Reversible data hiding: Advances in the past two decades. IEEE Access 4:3210–3237

    Article  Google Scholar 

  31. Simonyan K, Zisserman A (2014) Very deep convolutional networks for large-scale image recognition arXiv preprint

  32. Tang X, Wang H, Chen Y (2020) Reversible data hiding based on a modified difference expansion for h. 264/avc video streams. Multimed Tools Appl 79(39):28661–28674

    Article  Google Scholar 

  33. Tian J (2003) Reversible data embedding using a difference expansion. IEEE Trans Circuits Syst Video Technol 13(8):890–896

    Article  Google Scholar 

  34. Wang Xu, Chang C-C, Lin C- (2021) High capacity reversible data hiding in encrypted images based on prediction error and block classification. Multimed Tools Appl 80(19):29915–29937

    Article  Google Scholar 

  35. Wang J, Ni J, Zhang X, Shi Y (2017) Rate and distortion optimization for reversible data hiding using multiple histogram shifting. IEEE Trans Cybern 47(2):315–326

    Google Scholar 

  36. Xiang S, Ruan G (2021) Efficient pvo-based reversible data hiding by selecting blocks with full-enclosing context. IEEE Transactions on Circuits and Systems for Video Technology

  37. Xu X, Shen F, Yang Y, Shen HT, Li X (2017) Learning discriminative binary codes for large-scale cross-modal retrieval. IEEE Trans Image Process 26 (5):2494–2507

    Article  MathSciNet  MATH  Google Scholar 

  38. Yao H, Mao F, Qin C, Tang Z (2021) Dual-jpeg-image reversible data hiding. Inf Sci 563:130–149

    Article  MathSciNet  Google Scholar 

  39. Yao H, Qin C, Tang Z, Tian Y (2017) Improved dual-image reversible data hiding method using the selection strategy of shiftable pixels’ coordinates with minimum distortion. Signal Process 135:26–35

    Article  Google Scholar 

  40. Yao H, Qin C, Tang Z, Zhang X (2018) A general framework for shiftable position-based dual-image reversible data hiding. EURASIP Journal on Image and Video Processing, 2018(1)

  41. Yin Z, Xiang Y, Zhang X (2020) Reversible data hiding in encrypted images based on multi-msb prediction and huffman coding. IEEE Trans Multimed 22(4):874–884

    Article  Google Scholar 

  42. Zhang T, Li X, Qi W, Guo Z (2020) Location-based pvo and adaptive pairwise modification for efficient reversible data hiding. IEEE Trans Inform Forens Secur 15:2306–2319

    Article  Google Scholar 

  43. Zheng W, Chang C, Weng S (2020) A novel adjustable rdh method for ambtc-compressed codes using one-to-many map. IEEE Access 8:13105–13118

    Article  Google Scholar 

  44. Zhou H, Chen K, Zhang W, Yao Y, Yu N (2019) Distortion design for secure adaptive 3-d mesh steganography. IEEE Trans Multimed 21 (6):1384–1398

    Article  Google Scholar 

Download references

Acknowledgements

This work was supported in part by Scientific Research Leader Studio of Jinan (No. 2021GXRC081), in part by Joint Project for Smart Computing of Shandong Natural Science Foundation (ZR2020LZH015), and in part by Taishan Scholar Project of Shandong, China (No. ts20190924).

Author information

Authors and Affiliations

  1. School of Information Science and Engineering, Shandong Normal University, Jinan, 250358, Shandong, China

    Liming Zou, Jiande Sun & Wenbo Wan

  2. School of Journalism and Communication, Shandong Normal University, Jinan, 250358, China

    Jing Li

  3. Department of Electrical and Computer Engineering, University of Windsor, Windsor, N9B3P4, Canada

    Q. M. Jonathan Wu

Authors
  1. Liming Zou
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Jiande Sun
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Wenbo Wan
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Jing Li
    View author publications

    You can also search for this author in PubMed Google Scholar

  5. Q. M. Jonathan Wu
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding authors

Correspondence to Jiande Sun or Jing Li.

Ethics declarations

Conflict of Interests

The authors declare no conflict of interest.

Additional information

Publisher’s note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Supplementary Information

Below is the link to the electronic supplementary material.

(ZIP 8.16 MB)

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Zou, L., Sun, J., Wan, W. et al. A cover selection-based reversible data hiding method by learning cross-modal hashing. Multimed Tools Appl 82, 2983–3005 (2023). https://doi.org/10.1007/s11042-022-12936-7

Download citation

  • Received:

  • Revised:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s11042-022-12936-7

Keywords

Search

Navigation