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Improved Bootstrapping for Approximate Homomorphic Encryption

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Advances in Cryptology – EUROCRYPT 2019 (EUROCRYPT 2019)

Abstract

Since Cheon et al. introduced a homomorphic encryption scheme for approximate arithmetic (Asiacrypt ’17), it has been recognized as suitable for important real-life usecases of homomorphic encryption, including training of machine learning models over encrypted data. A follow up work by Cheon et al. (Eurocrypt ’18) described an approximate bootstrapping procedure for the scheme. In this work, we improve upon the previous bootstrapping result. We improve the amortized bootstrapping time per plaintext slot by two orders of magnitude, from \(\sim \)1 s to \(\sim \)0.01 s. To achieve this result, we adopt a smart level-collapsing technique for evaluating DFT-like linear transforms on a ciphertext. Also, we replace the Taylor approximation of the sine function with a more accurate and numerically stable Chebyshev approximation, and design a modified version of the Paterson-Stockmeyer algorithm for fast evaluation of Chebyshev polynomials over encrypted data.

Most of this work was done while the second author was an intern in the Cryptography Research group at Microsoft Research (Redmond, USA).

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Notes

  1. 1.

    The subsum algorithm can be understood as the evaluation of trace with respect to the field extension \({\mathbb Q}[X]/(X^N+1)\ge {\mathbb Q}[Y]/(Y^{2\ell }+1)\). It does nothing when \(\ell =N/2\).

References

  1. HEAAN with Faster Multiplication (2018). https://github.com/snucrypto/HEAAN/releases/tag/2.1

  2. Bajard, J.-C., Eynard, J., Hasan, M.A., Zucca, V.: A full RNS variant of FV like somewhat homomorphic encryption schemes. In: Avanzi, R., Heys, H. (eds.) SAC 2016. LNCS, vol. 10532, pp. 423–442. Springer, Cham (2017). https://doi.org/10.1007/978-3-319-69453-5_23

    Chapter  Google Scholar 

  3. Beckermann, B.: On the numerical condition of polynomial bases: estimates for the condition number of Vandermonde, Krylov and Hankel matrices. Ph.D. thesis, Verlag nicht ermittelbar (1997)

    Google Scholar 

  4. Bonte, C., Bootland, C., Bos, J.W., Castryck, W., Iliashenko, I., Vercauteren, F.: Faster homomorphic function evaluation using non-integral base encoding. In: Fischer, W., Homma, N. (eds.) CHES 2017. LNCS, vol. 10529, pp. 579–600. Springer, Cham (2017). https://doi.org/10.1007/978-3-319-66787-4_28

    Chapter  Google Scholar 

  5. Boura, C., Gama, N., Georgieva, M.: Chimera: a unified framework for B/FV, TFHE and HEAAN fully homomorphic encryption and predictions for deep learning. Cryptology ePrint Archive, Report 2018/758 (2018). https://eprint.iacr.org/2018/758

  6. Bourse, F., Minelli, M., Minihold, M., Paillier, P.: Fast homomorphic evaluation of deep discretized neural networks. In: Shacham, H., Boldyreva, A. (eds.) CRYPTO 2018. LNCS, vol. 10993, pp. 483–512. Springer, Cham (2018). https://doi.org/10.1007/978-3-319-96878-0_17

    Chapter  Google Scholar 

  7. Brakerski, Z., Gentry, C., Vaikuntanathan, V.: (Leveled) fully homomorphic encryption without bootstrapping. In: Proceedings of ITCS, pp. 309–325. ACM (2012)

    Google Scholar 

  8. Brakerski, Z., Vaikuntanathan, V.: Efficient fully homomorphic encryption from (standard) LWE. In: Proceedings of the 2011 IEEE 52nd Annual Symposium on Foundations of Computer Science, FOCS 2011, pp. 97–106. IEEE Computer Society (2011)

    Google Scholar 

  9. Brakerski, Z., Vaikuntanathan, V.: Fully homomorphic encryption from ring-LWE and security for key dependent messages. In: Rogaway, P. (ed.) CRYPTO 2011. LNCS, vol. 6841, pp. 505–524. Springer, Heidelberg (2011). https://doi.org/10.1007/978-3-642-22792-9_29

    Chapter  Google Scholar 

  10. Chen, H., et al.: Logistic regression over encrypted data from fully homomorphic encryption. BMC Med. Genomics 11(4), 81 (2018)

    Article  Google Scholar 

  11. 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_12

    Chapter  Google Scholar 

  12. Chen, H., Laine, K., Rindal, P.: Fast private set intersection from homomorphic encryption. In: Proceedings of the 2017 ACM SIGSAC Conference on Computer and Communications Security, pp. 1243–1255. ACM (2017)

    Google Scholar 

  13. Cheon, J.H., Han, K., Kim, A., Kim, M., Song, Y.: Implementation of boostrapping for HEAAN (2017). https://github.com/kimandrik/HEAANBOOT

  14. Cheon, J.H., Han, K., Kim, A., Kim, M., Song, Y.: Bootstrapping for approximate homomorphic encryption. In: Nielsen, J.B., Rijmen, V. (eds.) EUROCRYPT 2018. LNCS, vol. 10820, pp. 360–384. Springer, Cham (2018). https://doi.org/10.1007/978-3-319-78381-9_14

    Chapter  Google Scholar 

  15. Cheon, J.H., Han, K., Kim, A., Kim, M., Song, Y.: A full RNS variant of approximate homomorphic encryption. In: Cid, C., Jacobson Jr., M. (eds.) SAC 2018. LNCS, vol. 11349, pp. 347–368. Springer, Cham (2018). https://doi.org/10.1007/978-3-030-10970-7_16

    Chapter  Google Scholar 

  16. Cheon, J.H., Kim, A., Kim, M., Song, Y.: Homomorphic encryption for arithmetic of approximate numbers. In: Takagi, T., Peyrin, T. (eds.) ASIACRYPT 2017. LNCS, vol. 10624, pp. 409–437. Springer, Cham (2017). https://doi.org/10.1007/978-3-319-70694-8_15

    Chapter  Google Scholar 

  17. Chillotti, I., Gama, N., Georgieva, M., Izabachène, M.: Faster fully homomorphic encryption: bootstrapping in less than 0.1 seconds. In: Cheon, J.H., Takagi, T. (eds.) ASIACRYPT 2016. LNCS, vol. 10031, pp. 3–33. Springer, Heidelberg (2016). https://doi.org/10.1007/978-3-662-53887-6_1

    Chapter  MATH  Google Scholar 

  18. Chillotti, I., Gama, N., Georgieva, M., Izabachène, M.: Faster packed homomorphic operations and efficient circuit bootstrapping for TFHE. In: Takagi, T., Peyrin, T. (eds.) ASIACRYPT 2017. LNCS, vol. 10624, pp. 377–408. Springer, Cham (2017). https://doi.org/10.1007/978-3-319-70694-8_14

    Chapter  Google Scholar 

  19. Crawford, J.L., Gentry, C., Halevi, S., Platt, D., Shoup, V.: Doing real work with FHE: the case of logistic regression. In: Proceedings of the 6th Workshop on Encrypted Computing & Applied Homomorphic Cryptography, pp. 1–12. ACM (2018)

    Google Scholar 

  20. Ducas, L., Micciancio, D.: FHEW: bootstrapping homomorphic encryption in less than a second. In: Oswald, E., Fischlin, M. (eds.) EUROCRYPT 2015. LNCS, vol. 9056, pp. 617–640. Springer, Heidelberg (2015). https://doi.org/10.1007/978-3-662-46800-5_24

    Chapter  MATH  Google Scholar 

  21. Ehlich, H., Zeller, K.: Auswertung der normen von interpolationsoperatoren. Math. Ann. 164(2), 105–112 (1966)

    Article  MathSciNet  Google Scholar 

  22. Fan, J., Vercauteren, F.: Somewhat practical fully homomorphic encryption. IACR Cryptology ePrint Archive 2012:144 (2012)

    Google Scholar 

  23. Gentry, C.: Fully homomorphic encryption using ideal lattices. In: Proceedings of the 41st Annual ACM Symposium on Theory of Computing, pp. 169–178. ACM (2009)

    Google Scholar 

  24. Gentry, C., Halevi, S., Smart, N.P.: Better bootstrapping in fully homomorphic encryption. In: Fischlin, M., Buchmann, J., Manulis, M. (eds.) PKC 2012. LNCS, vol. 7293, pp. 1–16. Springer, Heidelberg (2012). https://doi.org/10.1007/978-3-642-30057-8_1

    Chapter  Google Scholar 

  25. Gilad-Bachrach, R., et al.: CryptoNets: applying neural networks to encrypted data with high throughput and accuracy. In: International Conference on Machine Learning, pp. 201–210 (2016)

    Google Scholar 

  26. Giroux, A.: Approximation of entire functions over bounded domains. J. Approx. Theory 28(1), 45–53 (1980)

    Article  MathSciNet  Google Scholar 

  27. Halevi, S., Shoup, V.: Algorithms in HElib. In: Garay, J.A., Gennaro, R. (eds.) CRYPTO 2014. LNCS, vol. 8616, pp. 554–571. Springer, Heidelberg (2014). https://doi.org/10.1007/978-3-662-44371-2_31

    Chapter  MATH  Google Scholar 

  28. Halevi, S., Shoup, V.: Bootstrapping for HElib. In: Oswald, E., Fischlin, M. (eds.) EUROCRYPT 2015. LNCS, vol. 9056, pp. 641–670. Springer, Heidelberg (2015). https://doi.org/10.1007/978-3-662-46800-5_25

    Chapter  Google Scholar 

  29. Han, K., Hong, S., Cheon, J.H., Park, D.: Efficient logistic regression on large encrypted data. Cryptology ePrint Archive, Report 2018/662 (2018). https://eprint.iacr.org/2018/662

  30. Kim, A., Song, Y., Kim, M., Lee, K., Cheon, J.H.: Logistic regression model training based on the approximate homomorphic encryption. BMC Med. Genomics 11(4), 83 (2018)

    Article  Google Scholar 

  31. Paterson, M.S., Stockmeyer, L.J.: On the number of nonscalar multiplications necessary to evaluate polynomials. SIAM J. Comput. 2(1), 60–66 (1973)

    Article  MathSciNet  Google Scholar 

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Chen, H., Chillotti, I., Song, Y. (2019). Improved Bootstrapping for Approximate Homomorphic Encryption. In: Ishai, Y., Rijmen, V. (eds) Advances in Cryptology – EUROCRYPT 2019. EUROCRYPT 2019. Lecture Notes in Computer Science(), vol 11477. Springer, Cham. https://doi.org/10.1007/978-3-030-17656-3_2

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  • DOI: https://doi.org/10.1007/978-3-030-17656-3_2

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