Advertisement

Private Membership Test Protocol with Low Communication Complexity

  • Sara Ramezanian
  • Tommi Meskanen
  • Masoud Naderpour
  • Valtteri Niemi
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 10394)

Abstract

We introduce a practical method to perform private membership test. In this method, clients are able to test whether an item is in a set controlled by the server, without revealing their query items to the server. After executing the queries, the content of server’s set remains secret. We apply Bloom filter and Cuckoo filter in the membership test procedure. In order to achieve privacy properties, we present a novel protocol based on homomorphic encryption schemes. We have implemented our method in a realistic scenario where a client of an anti-malware company wants to privately check a file hash value through the company’s database.

Keywords

Privacy enhancing technologies Applied cryptography Private information retrieval Private membership test Homomorphic encryption Bloom filter Cuckoo filter 

Notes

Acknowledgments

We thank the anonymous reviewers of NSS-2017 for their helpful comments. This work was supported in part by Tekes project “Cloud-assisted Security Services”.

References

  1. 1.
    Kosinski, M., Stillwell, D., Graepel, T.: Private traits and attributes are predictable from digital records of human behavior. Proc. Nat. Acad. Sci. 110(15), 5802–5805 (2013)CrossRefGoogle Scholar
  2. 2.
    Seneviratne, S., Seneviratne, A., Mohapatra, P., Mahanti, A.: Predicting user traits from a snapshot of apps installed on a smartphone. ACM SIGMOBILE Mob. Comput. Commun. Rev. 18(2), 1–8 (2014)CrossRefGoogle Scholar
  3. 3.
    Bloom, B.H.: Space/time trade-offs in hash coding with allowable errors. Commun. ACM 13(7), 422–426 (1970)CrossRefMATHGoogle Scholar
  4. 4.
    Fan, B., Andersen, D.G., Kaminsky, M., Mitzenmacher, M.D.: Cuckoo filter: practically better than bloom. In: Proceedings of the 10th ACM International on Conference on Emerging Networking Experiments and Technologies, pp. 75–88. ACM (2014)Google Scholar
  5. 5.
    Bonomi, F., Mitzenmacher, M., Panigrahy, R., Singh, S., Varghese, G.: An improved construction for counting bloom filters. In: Azar, Y., Erlebach, T. (eds.) ESA 2006. LNCS, vol. 4168, pp. 684–695. Springer, Heidelberg (2006). doi: 10.1007/11841036_61 CrossRefGoogle Scholar
  6. 6.
    Rivest, R.L., Adleman, L., Dertouzos, M.L.: On data banks and privacy homomorphisms. Found. Secur. Comput. 4(11), 169–180 (1978)MathSciNetGoogle Scholar
  7. 7.
    Paillier, P., Pointcheval, D.: Efficient public-key cryptosystems provably secure against active adversaries. In: Lam, K.-Y., Okamoto, E., Xing, C. (eds.) ASIACRYPT 1999. LNCS, vol. 1716, pp. 165–179. Springer, Heidelberg (1999). doi: 10.1007/978-3-540-48000-6_14 CrossRefGoogle Scholar
  8. 8.
    Chang, Y.-C.: Single database private information retrieval with logarithmic communication. In: Wang, H., Pieprzyk, J., Varadharajan, V. (eds.) ACISP 2004. LNCS, vol. 3108, pp. 50–61. Springer, Heidelberg (2004). doi: 10.1007/978-3-540-27800-9_5 CrossRefGoogle Scholar
  9. 9.
    Chor, B., Gilboa, N., Naor, M.: Private information retrieval by keywords. CiteSeer (1997)Google Scholar
  10. 10.
    Kushilevitz, E., Ostrovsky, R.: Replication is not needed: single database, computationally-private information retrieval. In: Proceedings of the 38th Annual Symposium on Foundations of Computer Science, pp. 364–373. IEEE (1997)Google Scholar
  11. 11.
    Gasarch, W.: A survey on private information retrieval. Bull. EATCS 82, 72–107 (2004)MathSciNetMATHGoogle Scholar
  12. 12.
    Gentry, C., Ramzan, Z.: Single-database private information retrieval with constant communication rate. In: Caires, L., Italiano, G.F., Monteiro, L., Palamidessi, C., Yung, M. (eds.) ICALP 2005. LNCS, vol. 3580, pp. 803–815. Springer, Heidelberg (2005). doi: 10.1007/11523468_65 CrossRefGoogle Scholar
  13. 13.
    Pinkas, B., Schneider, T., Zohner, M.: Scalable private set intersection based on OT extension (2016). http://eprint.iacr.org/2016/930. (in submission)
  14. 14.
    Rabin, M.O.: How to exchange secrets with oblivious transfer. IACR Cryptology ePrint Archive 2005, 187 (2005)Google Scholar
  15. 15.
    Tamrakar, S., Liu, J., Paverd, A., Ekberg, J.E., Pinkas, B., Asokan, N.: The circle game: Scalable private membership test using trusted hardware (2016). arXiv preprint: arXiv:1606.01655
  16. 16.
    Meskanen, T., Liu, J., Ramezanian, S., Niemi, V.: Private membership test for bloom filters. In: 2015 IEEE Trustcom/BigDataSE/ISPA, vol. 1, pp. 515–522. IEEE (2015)Google Scholar

Copyright information

© Springer International Publishing AG 2017

Authors and Affiliations

  • Sara Ramezanian
    • 1
  • Tommi Meskanen
    • 1
  • Masoud Naderpour
    • 1
  • Valtteri Niemi
    • 1
  1. 1.Department of Computer ScienceUniversity of HelsinkiHelsinkiFinland

Personalised recommendations