Abstract
Homomorphic secret sharing (HSS) allows multiple input clients to secret-share their data among multiple servers such that each server is able to locally compute a function on its shares to obtain a partial result and all partial results enable the reconstruction of the function’s value on the outsourced data by an output client. The existing HSS schemes for high-degree polynomials either require a large number of servers or lack verifiability, which is essential for ensuring the correctness of the outsourced computations. In this paper, we propose a two-server verifiable HSS (VHSS) model and construct a scheme that supports the computation of high-degree polynomials. The degree of the outsourced polynomials can be as high as a polynomial in the system’s security parameter. Despite of using only 2 servers, our VHSS ensures that each single server learns no information about the outsourced data and no single server is able to persuade the client to output a wrong function value. Our VHSS is significantly more efficient. When computing degree-7 polynomials, our scheme could be 3–10 times faster than the previously best construction.
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References
Albrecht, M.R., Player, R., Scott, S.: On the concrete hardness of learning with errors. J. Math. Crypt. 9(3), 169–203 (2015)
Benaloh, J.C.: Secret sharing homomorphisms: keeping shares of a secret secret (Extended Abstract). In: Odlyzko, A.M. (ed.) CRYPTO 1986. LNCS, vol. 263, pp. 251–260. Springer, Heidelberg (1987). https://doi.org/10.1007/3-540-47721-7_19
Boyle, E., Couteau, G., Gilboa, N., Ishai, Y., Orrú, M.: Homomorphic secret sharing: optimizations and applications. In: ACM CCS 2017. ACM Press, October/November 2017
Barbosa, M., Catalano, D., Fiore, D.: Labeled homomorphic encryption: scalable and privacy-preserving processing of outsourced data. IACR Cryptol. ePrint Arch. 2017, 326 (2017)
Boyle, E., Gilboa, N., Ishai, Y.: Function secret sharing. In: Oswald, E., Fischlin, M. (eds.) EUROCRYPT 2015. LNCS, vol. 9057, pp. 337–367. Springer, Heidelberg (2015). https://doi.org/10.1007/978-3-662-46803-6_12
Boyle, E., Gilboa, N., Ishai, Y.: Breaking the circuit size barrier for secure computation under DDH. In: Robshaw, M., Katz, J. (eds.) CRYPTO 2016. LNCS, vol. 9814, pp. 509–539. Springer, Heidelberg (2016). https://doi.org/10.1007/978-3-662-53018-4_19
Brakerski, Z., Gentry, C., Vaikuntanathan, V.: (Leveled) fully homomorphic encryption without bootstrapping. TOCT 6(3), 13 (2014)
Beimel, A., Ishai, Y., Kushilevitz, E., Orlov, I.: Share conversion and private information retrieval. IEEE Conf. Comput. Complex. 2012, 258–268 (2012)
Boyle, E., Kohl, L., Scholl, P.: Homomorphic secret sharing from lattices without FHE. In: Ishai, Y., Rijmen, V. (eds.) EUROCRYPT 2019. LNCS, vol. 11477, pp. 3–33. Springer, Cham (2019). https://doi.org/10.1007/978-3-030-17656-3_1
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
Brakerski, Z., Vaikuntanathan, V.: Efficient fully homomorphic encryption from (standard) LWE. In: 2011 IEEE 52nd Annual Symposium on Foundations of Computer Science, pp. 97–106, October 2011
Corrigan-Gibbs, H., Boneh, D., Mazières, D.: Riposte: an anonymous messaging system handling millions of users. In: Symposium on Security and Privacy (2015)
Catalano, D., Fiore, D.: Using linearly-homomorphic encryption to evaluate degree-2 functions on encrypted data. In: CCS 2015 (2015)
Cleve, R.: Towards optimal simulations of formulas by bounded-width programs. Comput. Complex. 1(1), 91–105 (1991). https://doi.org/10.1007/BF01200059
Cachin, C., Micali, S., Stadler, M.: Computationally private information retrieval with polylogarithmic communication. In: Stern, J. (ed.) EUROCRYPT 1999. LNCS, vol. 1592, pp. 402–414. Springer, Heidelberg (1999). https://doi.org/10.1007/3-540-48910-X_28
Chen X., Zhang L. F.: Two-Server Delegation of Computation on Label-Encrypted Data. IEEE Transactions on Cloud Computing (2019)
Efremenko, K.: 3-query locally decodable codes of subexponential length. Proc. STOC 2009, 39–44 (2009)
Gentry, C.: Fully homomorphic encryption using ideal lattices. In: STOC 2009, pp. 169–178. ACM, New York (2009)
Goldwasser, S., Micali, S.: Probabilistic encryption. J. Comput. Syst. Sci. 28(2), 270–299 (1984)
He, Y., Zhang, L.F.: Cheater-identifiable homomorphic secret sharing for outsourcing computations. J. Ambient Intell. Humanized Comput. 1–11 (2020). https://doi.org/10.1007/s12652-020-01814-5
Lai, R.W.F., Malavolta, G., Schröder, D.: Homomorphic secret sharing for low degree polynomials. In: Peyrin, T., Galbraith, S. (eds.) ASIACRYPT 2018. LNCS, vol. 11274, pp. 279–309. Springer, Cham (2018). https://doi.org/10.1007/978-3-030-03332-3_11
Lyubashevsky, V., Peikert, C., Regev, O.: A toolkit for ring-LWE cryptography. In: Johansson, T., Nguyen, P.Q. (eds.) EUROCRYPT 2013. LNCS, vol. 7881, pp. 35–54. Springer, Heidelberg (2013). https://doi.org/10.1007/978-3-642-38348-9_3
Khurana, H., Hadley, M., Lu, N., et al.: Smart-grid security issues. IEEE Symp. Secur. Priv. 8(1), 81–85 (2010)
Lauter, K., Naehrig, M., Vaikuntanathan, V.: Can homomorphic encryption be practical? In: CCSW, pp. 113–124. ACM (2011)
Martins, P., Sousa, L., Mariano, A.: A survey on fully homomorphic encryption: an engineering perspective. ACM Comput. Surv. 50(6), 83:1–83:33 (2017)
Paillier, P.: Public-key cryptosystems based on composite degree residuosity classes. In: Stern, J. (ed.) EUROCRYPT 1999. LNCS, vol. 1592, pp. 223–238. Springer, Heidelberg (1999). https://doi.org/10.1007/3-540-48910-X_16
Sharma, S., Chen, K., Sheth, A.: Towards practical privacy-preserving analytics for IoT and cloud based healthcare systems. IEEE Internet Comput. 22(2), 42–51 (2018)
Sadeghi, A.R., Wachsmann, C., Waidner, M.: Security and privacy challenges in industrial internet of things. In: Annual Design Automation Conference. ACM (2015)
Tsaloli, G., Liang, B., Mitrokotsa, A.: Verifiable homomorphic secret sharing. In: ProvSec, pp. 40–55 (2018)
Yoshida, M., Obana, S.: Verifiably multiplicative secret sharing. In: Shikata, J. (ed.) ICITS 2017. LNCS, vol. 10681, pp. 73–82. Springer, Cham (2017). https://doi.org/10.1007/978-3-319-72089-0_5
Zheng L., Chen C., Liu Y., et al.: Industrial scale privacy preserving deep neural network. arXiv preprint arXiv:2003.05198 (2020)
LWE estimator tool Homepage. https://bitbucket.org/malb/lwe-estimator. Accessed 8 Jul 2020
Acknowledgments
The research was supported by Singapore Ministry of Education under Research Grant RG12/19 and National Natural Science Foundation of China (No. 61602304).
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Chen, X., Zhang, L.F. (2020). Two-Server Verifiable Homomorphic Secret Sharing for High-Degree Polynomials. In: Susilo, W., Deng, R.H., Guo, F., Li, Y., Intan, R. (eds) Information Security. ISC 2020. Lecture Notes in Computer Science(), vol 12472. Springer, Cham. https://doi.org/10.1007/978-3-030-62974-8_5
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