Server-Aided Secure Computation with Off-line Parties

  • Foteini Baldimtsi
  • Dimitrios Papadopoulos
  • Stavros Papadopoulos
  • Alessandra Scafuro
  • Nikos Triandopoulos
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 10492)


Online social networks (OSNs) allow users to jointly compute on each other’s data (e.g., profiles, geo-locations, etc.). Privacy issues naturally arise in this setting due to the sensitive nature of the exchanged information. Ideally, nothing about a user’s data should be revealed to the OSN provider or non-friends, and even her friends should only learn the output of a specific computation. A natural approach for achieving these strong privacy guarantees is via secure multi-party computation (MPC). However, existing MPC-based approaches do not capture two key properties of OSN setting: Users does not need to be online while their friends query the OSN server on their data; and, once uploaded, user’s data can be repeatedly queried by the server on behalf of user’s friends. In this work, we present two concrete MPC constructions that achieve these properties. The first is an adaptation of garbled circuits that converts inputs under different keys to ones under the same key, and the second is based on 2-party mixed protocols and involves a novel 2-party re-encryption module. Using state- of-the-art cryptographic tools, we provide a proof-of-concept implementation of our schemes for two concrete use cases, overall validating their efficiency and efficacy in protecting privacy in OSNs.



We would like to thank Payman Mohassel and Arash Afshar for sharing parts of their code from [4], and the anonymous reviewers for their detailed comments and suggestions. Work partially done while the first and second authors were at Boston University and the fourth author was at Boston University and Northeastern University. Research supported in part by the U.S. National Science Foundation under CNS grants 1012798, 1012910, 1347350, 1413964, and 1414119.


  1. 1.
    CPABE (Ciphertext-Policy Attribute-Based Encryption) toolkit.
  2. 2.
    MIRACL cryptographic SDK.
  3. 3.
    OpenSSL cryptography and SSL/TLS toolkit.
  4. 4.
    Afshar, A., Mohassel, P., Pinkas, B., Riva, B.: Non-interactive secure computation based on cut-and-choose. In: Nguyen, P.Q., Oswald, E. (eds.) EUROCRYPT 2014. LNCS, vol. 8441, pp. 387–404. Springer, Heidelberg (2014). doi: 10.1007/978-3-642-55220-5_22 CrossRefGoogle Scholar
  5. 5.
    Aono, Y., Boyen, X., Phong, L.T., Wang, L.: Key-private proxy re-encryption under LWE. In: Paul, G., Vaudenay, S. (eds.) INDOCRYPT 2013. LNCS, vol. 8250, pp. 1–18. Springer, Cham (2013). doi: 10.1007/978-3-319-03515-4_1 CrossRefGoogle Scholar
  6. 6.
    Ateniese, G., Fu, K., Green, M., Hohenberger, S.: Improved proxy re-encryption schemes with applications to secure distributed storage. ACM TISSEC 9(1), 1–30 (2006)CrossRefzbMATHGoogle Scholar
  7. 7.
    Baldimtsi, F., Ohrimenko, O.: Sorting and searching behind the curtain. In: Böhme, R., Okamoto, T. (eds.) FC 2015. LNCS, vol. 8975, pp. 127–146. Springer, Heidelberg (2015). doi: 10.1007/978-3-662-47854-7_8 CrossRefGoogle Scholar
  8. 8.
    Baldimtsi, F., Papadopoulos, D., Papadopoulos, S., Scafuro, A., Triandopoulos, N.: Secure computation in online social networks. Cryptology ePrint Archive, Report 2016/948 (2016)Google Scholar
  9. 9.
    Bellare, M., Hoang, V.T., Keelveedhi, S., Rogaway, P.: Efficient garbling from a fixed-key blockcipher. In: IEEE SP (2013)Google Scholar
  10. 10.
    Ben-Efraim, A., Lindell, Y., Omri, E.: Optimizing semi-honest secure multiparty computation for the Internet. In: ACM CCS (2016)Google Scholar
  11. 11.
    Ben-Or, M., Goldwasser, S., Wigderson, A.: Completeness theorems for non-cryptographic fault-tolerant distributed computation. In: STOC (1988)Google Scholar
  12. 12.
    Blaze, M., Bleumer, G., Strauss, M.: Divertible protocols and atomic proxy cryptography. In: Nyberg, K. (ed.) EUROCRYPT 1998. LNCS, vol. 1403, pp. 127–144. Springer, Heidelberg (1998). doi: 10.1007/BFb0054122 Google Scholar
  13. 13.
    Bogdanov, D., Laud, P., Randmets, J.: Domain-polymorphic language for privacy-preserving applications. In: CCS-PETShop (2013)Google Scholar
  14. 14.
    Bogetoft, P., Christensen, D.L., Damgård, I., Geisler, M., Jakobsen, T., Krøigaard, M., Nielsen, J.D., Nielsen, J.B., Nielsen, K., Pagter, J., Schwartzbach, M., Toft, T.: Secure multiparty computation goes live. In: FC (2009)Google Scholar
  15. 15.
    Bost, R., Popa, R.A., Tu, S., Goldwasser, S.: Machine learning classification over encrypted data. In: NDSS (2015)Google Scholar
  16. 16.
    Canetti, R.: Security and composition of multiparty cryptographic protocols. J. Cryptol. 13(1), 143–202 (2000)MathSciNetCrossRefzbMATHGoogle Scholar
  17. 17.
    Carmer, B., Rosulek, M.: Linicrypt: a model for practical cryptography. In: Robshaw, M., Katz, J. (eds.) CRYPTO 2016. LNCS, vol. 9816, pp. 416–445. Springer, Heidelberg (2016). doi: 10.1007/978-3-662-53015-3_15 CrossRefGoogle Scholar
  18. 18.
    Carter, H., Mood, B., Traynor, P., Butler, K.R.B.: Secure outsourced garbled circuit evaluation for mobile devices. In: USENIX Security (2013)Google Scholar
  19. 19.
    Choi, S.G., Katz, J., Kumaresan, R., Cid, C.: Multi-client non-interactive verifiable computation. In: Sahai, A. (ed.) TCC 2013. LNCS, vol. 7785, pp. 499–518. Springer, Heidelberg (2013). doi: 10.1007/978-3-642-36594-2_28 CrossRefGoogle Scholar
  20. 20.
    Damgård, I., Ishai, Y.: Constant-round multiparty computation using a black-box pseudorandom generator. In: Shoup, V. (ed.) CRYPTO 2005. LNCS, vol. 3621, pp. 378–394. Springer, Heidelberg (2005). doi: 10.1007/11535218_23 CrossRefGoogle Scholar
  21. 21.
    Demmler, D., Schneider, T., Zohner, M.: ABY - a framework for efficient mixed-protocol secure two-party computation. In: NDSS (2015)Google Scholar
  22. 22.
    Erkin, Z., Franz, M., Guajardo, J., Katzenbeisser, S., Lagendijk, I., Toft, T.: Privacy-preserving face recognition. In: Goldberg, I., Atallah, M.J. (eds.) PETS 2009. LNCS, vol. 5672, pp. 235–253. Springer, Heidelberg (2009). doi: 10.1007/978-3-642-03168-7_14 CrossRefGoogle Scholar
  23. 23.
    Feige, U., Kilian, J., Naor, M.: A minimal model for secure computation (extended abstract). In: STOC (1994)Google Scholar
  24. 24.
    Goldreich, O.: Foundations of Cryptography: Basic Applications, vol. 2. Cambridge University Press, New York (2004)CrossRefzbMATHGoogle Scholar
  25. 25.
    Goldreich, O., Micali, S., Wigderson, A.: How to play ANY mental game. In: STOC (1987)Google Scholar
  26. 26.
    Gueron, S.: Intel advanced encryption standard AES instruction set white paper. Intel Corporation, August 2008Google Scholar
  27. 27.
    Halevi, S., Lindell, Y., Pinkas, B.: Secure computation on the web: computing without simultaneous interaction. In: Rogaway, P. (ed.) CRYPTO 2011. LNCS, vol. 6841, pp. 132–150. Springer, Heidelberg (2011). doi: 10.1007/978-3-642-22792-9_8 CrossRefGoogle Scholar
  28. 28.
    Henecka, W., Kögl, S., Sadeghi, A.-R., Schneider, T., Wehrenberg, I.: TASTY: tool for automating secure two-party computations. In: CCS (2010)Google Scholar
  29. 29.
    Ishai, Y., Kilian, J., Nissim, K., Petrank, E.: Extending oblivious transfers efficiently. In: Boneh, D. (ed.) CRYPTO 2003. LNCS, vol. 2729, pp. 145–161. Springer, Heidelberg (2003). doi: 10.1007/978-3-540-45146-4_9 CrossRefGoogle Scholar
  30. 30.
    Ivan, A., Dodis, Y.: Proxy cryptography revisited. In: NDSS (2003)Google Scholar
  31. 31.
    Jakobsen, T.P., Nielsen, J.B., Orlandi, C.: A framework for outsourcing of secure computation. In: CCSW (2014)Google Scholar
  32. 32.
    Kamara, S., Mohassel, P., Raykova, M.: Outsourcing multi-party computation. Cryptology ePrint Archive, Report 2011/272 (2011)Google Scholar
  33. 33.
    Kamara, S., Mohassel, P., Riva, B.: Salus: a system for server-aided secure function evaluation. In: CCS (2012)Google Scholar
  34. 34.
    Kerschbaum, F., Schneider, T., Schröpfer, A.: Automatic protocol selection in secure two-party computations. In: Boureanu, I., Owesarski, P., Vaudenay, S. (eds.) ACNS 2014. LNCS, vol. 8479, pp. 566–584. Springer, Cham (2014). doi: 10.1007/978-3-319-07536-5_33 Google Scholar
  35. 35.
    Kirshanova, E.: Proxy re-encryption from lattices. In: Krawczyk, H. (ed.) PKC 2014. LNCS, vol. 8383, pp. 77–94. Springer, Heidelberg (2014). doi: 10.1007/978-3-642-54631-0_5 CrossRefGoogle Scholar
  36. 36.
    Kolesnikov, V., Mohassel, P., Rosulek, M.: FleXOR: flexible garbling for XOR gates that beats free-XOR. In: Garay, J.A., Gennaro, R. (eds.) CRYPTO 2014. LNCS, vol. 8617, pp. 440–457. Springer, Heidelberg (2014). doi: 10.1007/978-3-662-44381-1_25 CrossRefGoogle Scholar
  37. 37.
    Kolesnikov, V., Schneider, T.: Improved garbled circuit: free XOR gates and applications. In: ICALP (2008)Google Scholar
  38. 38.
    Kreuter, B., Shelat, A., Shen, C.: Billion-gate secure computation with malicious adversaries. In: USENIX Security (2012)Google Scholar
  39. 39.
    López-Alt, A., Tromer, E., Vaikuntanathan, V.: On-the-fly multiparty computation on the cloud via multikey fully homomorphic encryption. In: STOC (2012)Google Scholar
  40. 40.
    Lu, S., Ostrovsky, R.: How to garble RAM programs. In: EUROCRYPT (2013)Google Scholar
  41. 41.
    Malkhi, D., Nisan, N., Pinkas, B., Sella, Y.: Fairplay: a secure two-party computation system. In: USENIX Security (2004)Google Scholar
  42. 42.
    Mohassel, P., Rosulek, M., Zhang, Y.: Fast and secure three-party computation: the garbled circuit approach. In: ACM CCS (2015)Google Scholar
  43. 43.
    Mood, B., Gupta, D., Butler, K.R.B., Feigenbaum, J.: Reuse it or lose it: more efficient secure computation through reuse of encrypted values. In: CCS (2014)Google Scholar
  44. 44.
    Naor, M., Pinkas, B.: Efficient oblivious transfer protocols. In: SODA (2001)Google Scholar
  45. 45.
    Naor, M., Pinkas, B., Sumner, R.: Privacy preserving auctions and mechanism design. In: EC (1999)Google Scholar
  46. 46.
    Nikolaenko, V., Weinsberg, U., Ioannidis, S., Joye, M., Boneh, D., Taft, N.: Privacy-preserving ridge regression on hundreds of millions of records. In: IEEE SP (2013)Google Scholar
  47. 47.
    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). doi: 10.1007/3-540-48910-X_16 Google Scholar
  48. 48.
    Schneider, T., Zohner, M.: GMW vs. yao? efficient secure two-party computation with low depth circuits. In: Sadeghi, A.-R. (ed.) FC 2013. LNCS, vol. 7859, pp. 275–292. Springer, Heidelberg (2013). doi: 10.1007/978-3-642-39884-1_23 CrossRefGoogle Scholar
  49. 49.
    Yao, A.C.: How to generate and exchange secrets. In: FOCS (1986)Google Scholar
  50. 50.
    Yao, A.C.: Protocols for secure computations. In: FOCS (1982)Google Scholar
  51. 51.
    Zahur, S., Rosulek, M., Evans, D.: Two halves make a whole. In: Oswald, E., Fischlin, M. (eds.) EUROCRYPT 2015. LNCS, vol. 9057, pp. 220–250. Springer, Heidelberg (2015). doi: 10.1007/978-3-662-46803-6_8 Google Scholar
  52. 52.
    Zohner, M.: OTExtension library.

Copyright information

© Springer International Publishing AG 2017

Authors and Affiliations

  • Foteini Baldimtsi
    • 1
  • Dimitrios Papadopoulos
    • 2
  • Stavros Papadopoulos
    • 3
  • Alessandra Scafuro
    • 4
  • Nikos Triandopoulos
    • 5
  1. 1.George Mason UniversityFairfaxUSA
  2. 2.Hong Kong University of Science and TechnologySai KungHong Kong
  3. 3.Intel LabsMITCambridgeUSA
  4. 4.North Carolina State UniversityRaleighUSA
  5. 5.Stevens Institute of TechnologyHobokenUSA

Personalised recommendations