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Towards Video Compression in the Encrypted Domain: A Case-Study on the H264 and HEVC Macroblock Processing Pipeline

  • Donald Nokam Kuate
  • Sebastien Canard
  • Renaud Sirdey
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 11124)

Abstract

Image/video compression is a widely used operation in our everyday life. Such an operation usually proceeds independantly on small rectangular portions, so-called macroblocks, and is mainly divided into four operations: color conversion, Discrete Cosine Transform (DCT), quantization and entropic encoding. This operation is carried out easily on non-encrypted image. In this paper, we consider the case where such an execution is done in the encrypted domain. In fact, this is today one central question related to individuals’ privacy since such image/video compression is most of the time done on the premises of a service provider data center, and pictures are potentially sensitive personal data. Thus, the capacity for such entity to perform an action “blindfolded”, that is not knowing the underlying input in plain, is an important topic since it permits to obtain both individual privacy and data usability.

In this context, one of the main cryptographic tool is (fully) homomorphic encryption (FHE), that permits to perform operations while keeping the data encrypted. We here consider two different instantiations of FHE, one for which the plaintext space is binary (\(\mathbb {Z}_2\)) and the other a modular space (\(\mathbb {Z}_p\) for an integer \(p> 2 \)), and compare them when running the well-known H264 and HEVC macroblock processing pipelines.

Our contribution is twofold. On one hand, we provide an exhaustive comparison between FHEs over \(\mathbb {Z}_2\) and FHEs over \(\mathbb {Z}_p\) (\(p>2\)) in terms of functional capabilities, multiplicative depth and real performances using several existing FHE implementations, over libraries such as Cingulata, SEAL and TFHE. On the other hand, we apply this to image compression in the encrypted domain, being the first to “crypto-compress” a full encrypted photograph with practically relevant performances.

References

  1. 1.
    Budagavi, M., Fuldseth, A., Bjøntegaard, G., Sze, V., Sadafale, M.: Core transform design in the high efficiency video coding (HEVC) standard. J. Sel. Top. Sig. Process. 7(6), 1029–1041 (2013)CrossRefGoogle Scholar
  2. 2.
    Cintra, R.J., Bayer, F.M., Coutinho, V.A., Kulasekera, S., Madanayake, A.: DCT-like transform for image and video compression requires 10 additions only. CoRR abs/1402.5979 (2014)Google Scholar
  3. 3.
    Brakerski, Z., Gentry, C., Vaikuntanathan, V.: (Leveled) fully homomorphic encryption without bootstrapping. In: ITCS (2012)Google Scholar
  4. 4.
    Recommendation ITU-R BT. Studio encoding parameters of digital television for standard 4: 3 and wide-screen 16:9 aspect ratios (1995)Google Scholar
  5. 5.
    Recommendation ITU-T BT. ITU-T H.265: High efficiency video coding (2013)Google Scholar
  6. 6.
    Canard, S., Carpov, S., Kuate, D.N., Sirdey, R.: Running compression algorithms in the encrypted domain: a case-study on the homomorphic execution of RLE. In: Proceedings of Privacy, Security and Trust (2017, to appear)Google Scholar
  7. 7.
    Chen, H., Han, K.: Homomorphic lower digits removal and improved FHE bootstrapping. In: Nielsen, J.B., Rijmen, V. (eds.) EUROCRYPT 2018. LNCS, vol. 10820, pp. 315–337. Springer, Cham (2018).  https://doi.org/10.1007/978-3-319-78381-9_12CrossRefGoogle Scholar
  8. 8.
    Chen, H., Laine, K., Player, R.: Simple encrypted arithmetic library (SEAL). https://www.microsoft.com/en-us/research/project/simple-encrypted-arithmetic-library/
  9. 9.
    Chen, H., Laine, K., Player, R.: Simple encrypted arithmetic library - SEAL v2.1. In: Brenner, M. (ed.) FC 2017. LNCS, vol. 10323, pp. 3–18. Springer, Cham (2017).  https://doi.org/10.1007/978-3-319-70278-0_1CrossRefGoogle Scholar
  10. 10.
    Chillotti, I., Gama, N., Georgieva, M., Izabachène, M.: TFHE: fast fully homomorphic encryption library over the torus. https://github.com/tfhe/tfhe
  11. 11.
    Chillotti, I., Gama, N., Georgieva, M., Izabachène, M.: Improving TFHE: faster packed homomorphic operations and efficient circuit bootstrapping (2017). https://eprint.iacr.org/2017/430
  12. 12.
    Costache, A., Smart, N.P.: Which ring based somewhat homomorphic encryption scheme is best? In: Sako, K. (ed.) CT-RSA 2016. LNCS, vol. 9610, pp. 325–340. Springer, Cham (2016).  https://doi.org/10.1007/978-3-319-29485-8_19CrossRefGoogle Scholar
  13. 13.
    Costache, A., Smart, N.P., Vivek, S., Waller, A.: Fixed-point arithmetic in SHE schemes. In: Avanzi, R., Heys, H. (eds.) SAC 2016. LNCS, vol. 10532, pp. 401–422. Springer, Cham (2017).  https://doi.org/10.1007/978-3-319-69453-5_22CrossRefzbMATHGoogle Scholar
  14. 14.
    Damgård, I., Geisler, M., Krøigaard, M.: Homomorphic encryption and secure comparison. Int. J. Appl. Crypt. 1(1), 22–31 (2008)MathSciNetCrossRefGoogle Scholar
  15. 15.
    Fan, J., Vercauteren, F.: Somewhat practical fully homomorphic encryption (2012). https://eprint.iacr.org/2012/144
  16. 16.
    Garay, J., Schoenmakers, B., Villegas, J.: Practical and secure solutions for integer comparison. In: Okamoto, T., Wang, X. (eds.) PKC 2007. LNCS, vol. 4450, pp. 330–342. Springer, Heidelberg (2007).  https://doi.org/10.1007/978-3-540-71677-8_22CrossRefGoogle Scholar
  17. 17.
    Gentry, C.: A fully homomorphic encryption scheme. Ph.D. (2009)Google Scholar
  18. 18.
    Halevi, S., Shoup, V.: HElib an implementation of homomorphic encryption. https://github.com/shaih/HElib
  19. 19.
    Lepoint, T., Naehrig, M.: A comparison of the homomorphic encryption schemes FV and YASHE. In: Pointcheval, D., Vergnaud, D. (eds.) AFRICACRYPT 2014. LNCS, vol. 8469, pp. 318–335. Springer, Cham (2014).  https://doi.org/10.1007/978-3-319-06734-6_20CrossRefGoogle Scholar
  20. 20.
    CEA LIST. Cingulata: compiler toolchain and RTE for running programs over encrypted data. https://github.com/CEA-LIST/Cingulata
  21. 21.
    Malvar, H.S., Hallapuro, A., Karczewicz, M., Kerofsky, L.: Low-complexity transform and quantization in H.264/AVC. IEEE Trans. Circuits Syst. Video Technol. 13(7), 598–603 (2003)CrossRefGoogle Scholar
  22. 22.
    Richardson, I.E.: H. 264 and MPEG-4 Video Compression: Video Coding for Next-Generation Multimedia. Wiley, New York (2004)Google Scholar
  23. 23.
    Rivest, R.L., Adleman, L., Dertouzos, M.L.: On data banks and privacy homomorphisms (1978)Google Scholar
  24. 24.
    Xu, C., Chen, J., Wu, W., Feng, Y.: Homomorphically encrypted arithmetic operations over the integer ring. In: Bao, F., Chen, L., Deng, R.H., Wang, G. (eds.) ISPEC 2016. LNCS, vol. 10060, pp. 167–181. Springer, Cham (2016).  https://doi.org/10.1007/978-3-319-49151-6_12CrossRefGoogle Scholar
  25. 25.
    Yang, P., Gui, X., An, J., Tian, F., Wang, J.: An encrypted image editing scheme based on homomorphic encryption. In: INFOCOM WKSHPS. IEEE (2015)Google Scholar
  26. 26.
    Zheng, P., Huang, J.: An efficient image homomorphic encryption scheme with small ciphertext expansion. In: ACMMULTIMEDIA. ACM (2013)Google Scholar

Copyright information

© Springer Nature Switzerland AG 2018

Authors and Affiliations

  • Donald Nokam Kuate
    • 1
    • 2
  • Sebastien Canard
    • 1
  • Renaud Sirdey
    • 2
  1. 1.Orange Labs, Applied Crypto GroupCaenFrance
  2. 2.CEA, LISTGif-sur-YvetteFrance

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