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Private Conjunctive Query over Encrypted Data

  • Tushar Kanti SahaEmail author
  • Takeshi Koshiba
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 10239)

Abstract

In this paper, we propose an efficient protocol to process a private conjunctive query over encrypted data in the cloud using the somewhat homomorphic encryption (SwHE) scheme with a batch technique. In 2016, Cheon, Kim, and Kim (CKK) [IEEE Trans. Inf. Forensics Security] showed conjunctive query processing over encrypted data using search-and-compute circuits and an SwHE scheme and mentioned that their scheme should be improved in performance. To improve the performance of processing a private conjunctive query, we also propose a new packing method to support an efficient batch computation for our protocol using a few multiplications. Our implementation shows that our protocol works more than 50 times as fast as the CKK protocol for conjunctive query processing. In addition, the security level of our protocol is better than the security level of the CKK protocol.

Keywords

Private Conjunctive Query processing Encrypted Data Packing method Homomorphic encryption 

Notes

Acknowledgment

This research is supported by KAKENHI Grant Numbers JP26540002, JP-24106008, and JP16H0175.

References

  1. 1.
    Boneh, D., Gentry, C., Halevi, S., Wang, F., Wu, D.J.: Private database queries using somewhat homomorphic encryption. In: Jacobson, M., Locasto, M., Mohassel, P., Safavi-Naini, R. (eds.) ACNS 2013. LNCS, vol. 7954, pp. 102–118. Springer, Heidelberg (2013). doi: 10.1007/978-3-642-38980-1_7 CrossRefGoogle Scholar
  2. 2.
    Cheon, J.H., Kim, M., Kim, M.: Optimized search-and-compute circuits and their application to query evaluation on encrypted data. IEEE Trans. Inf. Forensics Security 11(1), 188–199 (2016)CrossRefGoogle Scholar
  3. 3.
    Kim, M., Lee, H.T., Ling, S., Wang, H.: On the efficiency of FHE-based private queries. In: IACR Cryptology ePrint Archive 2015: 1176 (2015)Google Scholar
  4. 4.
    Kim, M., Lee, H.T., Ling, H., Ren, S.Q., Tan, B.H.M., Wang, H.: Better security for queries on encrypted databases. In: IACR Cryptology ePrint Archive 2016: 470 (2016)Google Scholar
  5. 5.
    Gentry, C.: Fully homomorphic encryption using ideal lattices. In: Symposium on Theory of Computing - STOC 2009, pp. 169–178. ACM, New York (2009)Google Scholar
  6. 6.
    Hu, Y.: Improving the efficiency of homomorphic encryption schemes. Ph.D. diss., Worcester Polytechnic Institute, Massachusetts (2013)Google Scholar
  7. 7.
    Lyubashevsky, V., Peikert, C., Regev, O.: On ideal lattices and learning with errors over rings. In: Gilbert, H. (ed.) EUROCRYPT 2010. LNCS, vol. 6110, pp. 1–23. Springer, Heidelberg (2010). doi: 10.1007/978-3-642-13190-5_1 CrossRefGoogle Scholar
  8. 8.
    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). doi: 10.1007/978-3-642-22792-9_29 CrossRefGoogle Scholar
  9. 9.
    Brakerski, Z., Gentry, C., Vaikuntanathan, V.: (Leveled) Fully homomorphic encryption without bootstrapping. In: Proceedings of the 3rd Innovations in Theoretical Computer Science Conference, pp. 309–325. ACM (2012)Google Scholar
  10. 10.
    Lauter, K., Naehrig, M., Vaikuntanathan, V.: Can homomorphic encryption be practical? In: ACM Workshop on Cloud Computing Security Workshop, CCSW 2011, pp. 113–124. ACM, New York (2011)Google Scholar
  11. 11.
    Pappas, V., Vo, B., Krell, F., Choi, S., Kolesnikov, V., Keromytis, A., Malkin, T.: Blind Seer: a scalable private DBMS. In: 35th IEEE Symposium on Security and Privacy 2014, pp. 359–374. IEEE Computer Society Press (2014)Google Scholar
  12. 12.
    Fisch, B.A., Vo, B., Krell, F., Kumarasubramanian, A., Kolesnikov, V., Malkin, T., Bellovin, S.M.: Malicious-client security in Blind Seer: a scalable private DBMS. In: 36th IEEE Symposium on Security and Privacy, pp. 395–410. IEEE Computer Society Press (2015)Google Scholar
  13. 13.
    Yasuda, M., Shimoyama, T., Kogure, J., Yokoyama, K., Koshiba, T.: Practical packing method in somewhat homomorphic encryption. In: Garcia-Alfaro, J., Lioudakis, G., Cuppens-Boulahia, N., Foley, S., Fitzgerald, W.M. (eds.) DPM/SETOP -2013. LNCS, vol. 8247, pp. 34–50. Springer, Heidelberg (2014). doi: 10.1007/978-3-642-54568-9_3 CrossRefGoogle Scholar
  14. 14.
    Yasuda, M., Shimoyama, T., Kogure, J., Yokoyama, K., Koshiba, T.: Secure statistical analysis using RLWE-based homomorphic encryption. In: Foo, E., Stebila, D. (eds.) ACISP 2015. LNCS, vol. 9144, pp. 471–487. Springer, Cham (2015). doi: 10.1007/978-3-319-19962-7_27 CrossRefGoogle Scholar
  15. 15.
    Yasuda, M., Shimoyama, T., Kogure, J., Yokoyama, K., Koshiba, T.: Secure pattern matching using somewhat homomorphic encryption. In: ACM Workshop on Cloud Computing Security Workshop, CCSW 2013, pp. 65–76. ACM, New York (2013)Google Scholar
  16. 16.
    Castryck, W., Iliashenko, I., Vercauteren, F.: Provably weak instances of ring-LWE revisited. In: Fischlin, M., Coron, J.-S. (eds.) EUROCRYPT 2016. LNCS, vol. 9665, pp. 147–167. Springer, Heidelberg (2016). doi: 10.1007/978-3-662-49890-3_6 CrossRefGoogle Scholar
  17. 17.
    Barker, E.: Recommendation for key management. In: NIST Special Publication 800–57 Part 1 Revision 4. NIST (2016)Google Scholar
  18. 18.
    The PARI Group, PARI/GP version 2.7.5, Bordeaux (2014). http://pari.math.u-bordeaux.fr/

Copyright information

© Springer International Publishing AG 2017

Authors and Affiliations

  1. 1.Division of Mathematics, Electronics, and Informatics, Graduate School of Science and EngineeringSaitama UniversitySaitamaJapan
  2. 2.Faculty of Education and Integrated Arts and SciencesWaseda UniversityTokyoJapan

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