A Recent Survey of Reversible Data Hiding Techniques for 2D and 3D Object Models

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Cryptology and Network Security with Machine Learning (ICCNSML 2022)

Part of the book series: Algorithms for Intelligent Systems ((AIS))

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Abstract

In recent years, humans have gradually begun experiencing the world in 3D object models, and the vast use of 3D object models has made them an ideal information hiding platform. The most common uses of these models are displaying virtual surfaces and volumes. The use of 3D object models in industrial, medical, and entertainment fields has increased substantially over the last decade, giving immense value to research in 3D object models. Information hiding is one of the most important techniques in terms of privacy protection for multimedia content. Additionally, reversible data hiding (RDH) offers impressive performance in data security and authentication. Thus, to explore more, the RDH in encrypted images technique has been extended to 3D mesh models. It gives better performance in comparison to existing 2D models. This paper presents a review with the aim to show the development of emerging methodologies in the field of RDH on 3D object models. In this paper, the existing RDH techniques in the spatial domain and encrypted domain on 2D and 3D object models have been compared. This paper also spots the areas where RDH on 3D object models may be explored more.

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References

  1. Pfitzmann B (1996) Information hiding terminology. In: Proceedings of first international workshop information hiding, Lecture notes in computer science, vol 1,174. Springer, Berlin, pp 347–356

    Google Scholar 

  2. Shannon C-E (1949) Communication theory of secrecy systems. Bell Syst Tech J 28:656–715

    Article  MathSciNet  MATH  Google Scholar 

  3. Goldwasser S, Micali S (1984) Probabilistic encryption. J Comput Syst Sci 28:270–299

    Article  MathSciNet  MATH  Google Scholar 

  4. Diffie W, Hellman M-E (1976) New directions in cryptography. IEEE Trans Inf Theory 22:644–654

    Article  MathSciNet  MATH  Google Scholar 

  5. Request for Proposals-Embedded Signalling Systems Issue 1.0. International Federation of the Phonographic Industry, U.K., London (1997)

    Google Scholar 

  6. Abraham D-G (1991) Transaction security system. IBM Syst J 30(2):206–229

    Article  Google Scholar 

  7. Miller ML, Cox IJ, Bloom JA (1998) Watermarking in the real world: an application to DVD. In: Proceedings of multimedia and security-workshop at ACM multimedia ’98, pp 71–76

    Google Scholar 

  8. Bender W, Gruhl D, Morimoto N, Lu A (1996) Techniques for data hiding. IBM Syst J 35(3):313–336

    Article  Google Scholar 

  9. Barton J-M (1997) Method and apparatus for embedding authentication information within digital data, U.S. Patent 5, pp 646–997

    Google Scholar 

  10. Honsinger CW, Jones PW, Rabbani M, Stoffel JC (2001) Lossless recovery of an original image containing embedded data, US Patent, 6, pp 278, 791

    Google Scholar 

  11. Delaigle JF, Vleeschouwer CD, Macq B-M-M (1996) Digital watermarking. In: Proceedings of SPIE 2659, optical security and counterfeit deterrence techniques

    Google Scholar 

  12. Fridrich J, Goljan M, Du R (2002) Lossless data embedding for all image formats. In: Proceedings of SPIE 4675, security and watermarking of multimedia contents IV

    Google Scholar 

  13. Ni N, Shi Y-Q, Ansari N, Su W (2006) Reversible data hiding. IEEE Trans Circ Syst Vid Technol 16(3):354–362

    Article  Google Scholar 

  14. Tian J (2003) Reversible data embedding using a difference expansion. IEEE Trans Circ Syst Vid Technol 13(8):890–896

    Article  Google Scholar 

  15. Ma K, Zhang W, Zhao X, Yu N, Li F (2013) Reversible data hiding in encrypted images by reserving room before encryption. IEEE Trans Inf Forensics Secur 8(3):553–562

    Article  Google Scholar 

  16. Li M, **ao D, Zhang Y, Nan H (2015) Reversible data hiding in encrypted images using cross division and additive homomorphism. Signal Process Image Commun 39:234–248

    Article  Google Scholar 

  17. Jung K-H (2016) A high-capacity reversible data hiding scheme based on sorting and prediction in digital images. Multimed Tools Appl 76

    Google Scholar 

  18. Jia Y, Yin Z, Zhang X, Luo Y (2019) Reversible data hiding based on reducing invalid shifting of pixels in histogram shifting. Signal Process 163:238–246

    Article  Google Scholar 

  19. Weng S, Tan W, Ou B, Pan J-S (2021) Reversible data hiding method for multi-histogram point selection based on improved criss-cross optimization algorithm. Inf Sci 549:13–33

    Article  Google Scholar 

  20. **ang Y, **ao D, Zhang R, Liang J, Liu R (2021) Cryptanalysis and improvement of a reversible data-hiding scheme in encrypted images by redundant space transfer. Inf Sci 545:188–206

    Article  MathSciNet  MATH  Google Scholar 

  21. 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 

  22. Hou J, Ou B, Tian H, Qin Z (2021) Reversible data hiding based on multiple histograms modification and deep neural networks. Signal Process: Image Commun 92:116118

    Google Scholar 

  23. Yin Z, She X, Tang J, Luo B (2021) Reversible data hiding in encrypted images based on pixel prediction and multi-MSB planes rearrangement. Signal Process 187:108146

    Article  Google Scholar 

  24. Zhongyun H et al (2021) Secure reversible data hiding in encrypted images using cipher-feedback secret sharing. ar**v:2106.14139

  25. Agarwal R, Kumar M (2021) A two side histogram shifting based reversible data hiding technique in encrypted images. In: Computer vision and image processing, vol 1376. Springer, Singapore, CVIP (2021)

    Google Scholar 

  26. Agarwal R, Kumar R (2021) Block-wise reversible data hiding in encrypted domain using SVD. Optik 247:16801

    Article  Google Scholar 

  27. Fu Z, Gong M, Long G et al (2022) Efficient capacity-distortion reversible data hiding based on combining multipeak embedding with local complexity. Appl Intell

    Google Scholar 

  28. Qiu Y, Ying Q, Yang Y, Zeng H, Li S, Qian Z, High-capacity framework for reversible data hiding in encrypted image using pixel prediction and entropy encoding. IEEE Trans Circuits Syst Video Technol

    Google Scholar 

  29. Wu H-T, Cheung Y-M, Zhuang Z, Xu L, Hu J, lossless data hiding in encrypted images compatible with homomorphic processing. IEEE Trans Cybern

    Google Scholar 

  30. Fang C, Yujie F, Heng Y, Mian Z, Jian l, Chuan Q (2022) Separable reversible data hiding in encrypted VQ-encoded images. Secur Commun Netw 16

    Google Scholar 

  31. Qin J, He Z, **ang X, Tan Y (2022) Reversible data hiding in encrypted images based on adaptive gradient prediction. Secur Commun Netw 12

    Google Scholar 

  32. Tsai Y-Y, Liu H-L, Kuo P-L, Chan C-S (2022) Extending multi-MSB prediction and huffman coding for reversible data hiding in encrypted HDR images. IEEE Access 10:49347–49358

    Article  Google Scholar 

  33. Xu D (2022) Reversible data hiding in encrypted images with high payload. IET Inf Secur 16(4):301–313

    Article  Google Scholar 

  34. Arai E, Imaizumi S (2022) High-capacity reversible data hiding in encrypted images with flexible restoration. J Imaging 8:176

    Article  Google Scholar 

  35. Yang C-H, Weng C-Y, Chen J-Y (2022) High-fidelity reversible data hiding in encrypted image based on difference-preserving encryption. Soft Comput 26:4

    Article  Google Scholar 

  36. Rai A-K, Om H, Chand S (2022) High capacity reversible data hiding in encrypted images using prediction error encoding. Multimed Tools Appl

    Google Scholar 

  37. Panchikkil S, Manikandan V-M, Zhang Y-D (2022) A pseudo-random pixel map** with weighted mesh graph approach for reversible data hiding in encrypted image. Multimed Tools Appl. 81(12):16279–16307

    Google Scholar 

  38. Meng L et al (2022) Reversible data hiding in encrypted images based on IWT and chaotic system. Multimed Tools Appl 81(12):16833–16861

    Google Scholar 

  39. Tsai C-S, Zhang Y-S, Weng C-Y (2022) Separable reversible data hiding in encrypted images based on Paillier cryptosystem. Multimed Tools Appl 81(13):18807–18827

    Article  Google Scholar 

  40. Fengyong L, Zhu H, Qin C (2022) Reversible data hiding in encrypted images using median prediction and bit plane cycling-XOR. Multimed Tools Appl 1–20

    Google Scholar 

  41. Lin J et al (2022) A large payload data hiding scheme using scalable secret reference matrix. Symmetry 14(4):828

    Google Scholar 

  42. Jiang R, Zhang W, Hou D et al (2018) Reversible data hiding for 3D mesh models with three-dimensional prediction-error histogram modification. Multimed Tools Appl 77:5263–5280

    Article  Google Scholar 

  43. Shah M, Zhang W, Hu H et al (2018) Homomorphic encryption-based reversible data hiding for 3D mesh models. Arab J Sci Eng 43:8145–8157

    Article  Google Scholar 

  44. Jiang R, Zhou H, Zhang W, Yu N (2018) Reversible data hiding in encrypted three-dimensional mesh models. IEEE Trans. Multimed 20(1):55–67

    Article  Google Scholar 

  45. Zhang Q, Song X, Wen T et al (2019) Reversible data hiding for 3D mesh models with hybrid prediction and multilayer strategy. Multimed Tools Appl 78:29713–29729

    Article  Google Scholar 

  46. Girdhar A, Kumar V (2019) A reversible and affine invariant 3D data hiding technique based on difference shifting and logistic map. J Ambient Intell Human Comput 10:4947–4961

    Article  Google Scholar 

  47. Farrag S, Alexan W (2020) Secure 3D data hiding technique based on a mesh traversal algorithm. Multimed Tools Appl 79:29289–29303

    Article  Google Scholar 

  48. Luo T, Li L, Zhang S, Wang S, Gu W (2021) A novel reversible data hiding method for 3D model in homomorphic encryption domain. Symmetry 13(6):1090

    Google Scholar 

  49. Rensburg B-J-V, Puteaux P, Puech W, Pedeboy J-P (2021) Homomorphic two tier reversible data hiding in encrypted 3D objects. In: IEEE International conference on image processing (ICIP), pp 3068–3072

    Google Scholar 

  50. Xu N, Tang J, Luo B et al (2022) Separable reversible data hiding based on integer map** and MSB prediction for encrypted 3D mesh models. Cogn Comput 14:1172–1181

    Google Scholar 

  51. Tsai YY (2021) separable reversible data hiding for encrypted three-dimensional models based on spatial subdivision and space encoding. IEEE Trans Multimed 23:2286–2296

    Google Scholar 

  52. lyu W, Cheng L Yin Z (2022) High-capacity reversible data hiding in encrypted 3d mesh models based on multi-Msb prediction volume 108686:201

    Google Scholar 

  53. Peng F, Liao T, Long M (2022) A semi-fragile reversible watermarking for authenticating 3D models in dual domains based on variable direction double modulation. IEEE Trans Circuits Syst Video Technol 31:11

    Google Scholar 

  54. Bhardwaj R (2022) Efficient separable reversible data hiding algorithm for compressed 3D mesh models. Biomed Signal Process Control 73:103265

    Article  Google Scholar 

  55. Girdhar A, Kumar V (2017) Comprehensive survey of 3D image steganography techniques. IET Image Proc 12(1):1–10

    Article  Google Scholar 

  56. Wu X, **e Z, Gao Y, **ao Y (2020) SSTNet: detecting manipulated faces through spatial, steganalysis and temporal features. In: IEEE international conference on acoustics, speech and signal processing (ICASSP), pp 2952–2956

    Google Scholar 

  57. Zhu J, Kaplan R, Johnson J, Fei-Fei L (2018) Hidden: Hiding data with deep networks. In: Proceedings of the European conference on computer vision, pp 657–672

    Google Scholar 

  58. Lavoué G (2009) A local roughness measure for 3d meshes and its application to visual masking. ACM Trans Appl Percept (TAP) 5(4), 1–23

    Google Scholar 

  59. Silva S, Madeira J, Ferreira C, Santos B-S (2007) Comparison of methods for the simplification of mesh models using quality indices and an observer study. In: Human vision and electronic imaging XII, vol 6492, pp 64921L

    Google Scholar 

  60. Cho J-W, Prost R, Jung H-Y (2006) An oblivious watermarking for 3d polygonal meshes using distribution of vertex norms. IEEE Trans Signal Process 55(1):142–155

    Article  MATH  Google Scholar 

  61. http://graphics.stanford.edu/data/3Dscanrep/

  62. Zhou Q, Jacobson A (2016) Thingi10k: a dataset of 10,000 3d-printing models, p 04797. ar**v: 1605

  63. Cho J-W, Prost R, Jung H-Y (2006) An oblivious watermarking for 3-d polygonal meshes using distribution of vertex norms. IEEE Trans Signal Process 55(1):142–155

    Article  MathSciNet  MATH  Google Scholar 

  64. Nader G, Wang K, Hétroy-Wheeler F, Dupont F (2015) Just noticeable distortion profile for flat-shaded 3d mesh surfaces. IEEE Trans Visual Comput Graph 22(11):2423–2436

    Google Scholar 

  65. Bors A-G, Luo M (2012) Optimized 3d watermarking for minimal surface distortion. IEEE Trans Image Process 22(5):1822–1835

    Article  Google Scholar 

  66. Mun S-M, Jang H-U, Kim D-G, Choi S, Lee H-K (2015) A robust 3d mesh watermarking scheme against crop**. In: 2015 international conference on 3D imaging (IC3D), pp 1–6

    Google Scholar 

  67. Seo Y-S, Joo S, Jung H-Y (2003) An efficient quantization watermarking on the lowest wavelet subband. IEICE Trans Fundam Electron Commun Comput Sci 86(8):2053–2055

    Google Scholar 

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Correspondence to Ruchi Agarwal .

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Verma, A., Agarwal, R., Borah, B. (2024). A Recent Survey of Reversible Data Hiding Techniques for 2D and 3D Object Models. In: Roy, B.K., Chaturvedi, A., Tsaban, B., Hasan, S.U. (eds) Cryptology and Network Security with Machine Learning. ICCNSML 2022. Algorithms for Intelligent Systems. Springer, Singapore. https://doi.org/10.1007/978-981-99-2229-1_24

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  • DOI: https://doi.org/10.1007/978-981-99-2229-1_24

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