Privacy-Preserving Reconciliation Protocols: From Theory to Practice

  • Ulrike Meyer
  • Susanne Wetzel
Part of the Lecture Notes in Computer Science book series (LNCS, volume 8260)


In this paper we provide a brief summary of our work on privacy-preserving reconciliation protocols. The main focus of the paper is to review two of our two-party protocols. We detail the protocols and provide a comprehensive theoretical performance analysis. Furthermore, we briefly describe some of our work on multi-party protocols. We also show how we have translated our theoretical results into practice—including the design and implementation of a library as well as developing iPhone and Android apps.


Homomorphic Encryption Honest Party Composition Scheme Private Input Malicious Model 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


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  1. 1.
    Ben-David, A., Nisan, N., Pinkas, B.: FairplayMP: A System for Secure Multi-Party Computation. In: Conference on Computer and Communications Security (CCS). ACM (2008)Google Scholar
  2. 2.
    Blanton, M., Aguiar, E.: Private and Oblivious Set and Multiset Operations. In: Symposium on Information, Computer and Communications Security (ASIACCS). ACM (2012)Google Scholar
  3. 3.
    Bogdanov, D., Laur, S., Willemson, J.: Sharemind: A Framework for Fast Privacy-Preserving Computations. In: Jajodia, S., Lopez, J. (eds.) ESORICS 2008. LNCS, vol. 5283, pp. 192–206. Springer, Heidelberg (2008)CrossRefGoogle Scholar
  4. 4.
    Burkhart, M., Strasser, M., Many, D., Dimitropoulos, X.: SEPIA: Privacy-Preserving Aggregation of Multi-Domain Network Events and Statistics. In: USENIX Security Symposium. USENIX (2010)Google Scholar
  5. 5.
    Camenisch, J., Zaverucha, G.M.: Private Intersection of Certified Sets. In: Dingledine, R., Golle, P. (eds.) FC 2009. LNCS, vol. 5628, pp. 108–127. Springer, Heidelberg (2009)CrossRefGoogle Scholar
  6. 6.
    Dachman-Soled, D., Malkin, T., Raykova, M., Yung, M.: Efficient Robust Private Set Intersection. In: Abdalla, M., Pointcheval, D., Fouque, P.-A., Vergnaud, D. (eds.) ACNS 2009. LNCS, vol. 5536, pp. 125–142. Springer, Heidelberg (2009)CrossRefGoogle Scholar
  7. 7.
    De Cristofaro, E., Tsudik, G.: Experimenting with Fast Private Set Intersection. In: Katzenbeisser, S., Weippl, E., Camp, L.J., Volkamer, M., Reiter, M., Zhang, X. (eds.) Trust 2012. LNCS, vol. 7344, pp. 55–73. Springer, Heidelberg (2012)CrossRefGoogle Scholar
  8. 8.
    De Cristofaro, E., Tsudik, G.: Practical Private Set Intersection Protocols with Linear Complexity. In: Sion, R. (ed.) FC 2010. LNCS, vol. 6052, pp. 143–159. Springer, Heidelberg (2010)CrossRefGoogle Scholar
  9. 9.
    Freedman, M.J., Nissim, K., Pinkas, B.: Efficient Private Matching and Set Intersection. In: Cachin, C., Camenisch, J.L. (eds.) EUROCRYPT 2004. LNCS, vol. 3027, pp. 1–19. Springer, Heidelberg (2004)CrossRefGoogle Scholar
  10. 10.
    Frikken, K.B.: Privacy-Preserving Set Union. In: Katz, J., Yung, M. (eds.) ACNS 2007. LNCS, vol. 4521, pp. 237–252. Springer, Heidelberg (2007)CrossRefGoogle Scholar
  11. 11.
    Geisler, M.: Cryptographic Protocols: Theory and Implementation. PhD Thesis, Aarhus University (2010)Google Scholar
  12. 12.
    Goldreich, O.: Foundations of Cryptography, vol. 1. Press Syndicate of the University of Cambridge (2004)Google Scholar
  13. 13.
    Goldwasser, S., Micali, S.: Probabilistic Encryption & How to Play Mental Poker Keeping Secret all Partial Information. In: Symposium on Theory of Computing (STOC). ACM (1984)Google Scholar
  14. 14.
    Hazay, C., Nissim, K.: Efficient Set Operations in the Presence of Malicious Adversaries. In: Nguyen, P.Q., Pointcheval, D. (eds.) PKC 2010. LNCS, vol. 6056, pp. 312–331. Springer, Heidelberg (2010)CrossRefGoogle Scholar
  15. 15.
    Huang, Y., Evans, D., Katz, J.: Private Set Intersection: Are Garbled Circuits Better than Custom Protocols. In: Network and Distributed System Security Symposium (NDSS). Internet Societey (2012)Google Scholar
  16. 16.
    Kissner, L., Song, D.: Privacy-Preserving Set Operations. In: Shoup, V. (ed.) CRYPTO 2005. LNCS, vol. 3621, pp. 241–257. Springer, Heidelberg (2005)CrossRefGoogle Scholar
  17. 17.
    Mayer, D.: Design and Implementation of Efficient Privacy-Preserving and Unbiased Reconciliation Protocols. PhD Thesis, Stevens Institute of Technology (2012)Google Scholar
  18. 18.
    Mayer, D., Neugebauer, G., Meyer, U., Wetzel, S.: Enabling Fair and Privacy-Preserving Applications Using Reconciliation Protocols on Ordered Sets. In: Sarnoff Symposium. IEEE (2011)Google Scholar
  19. 19.
    Mayer, D.A., Steele, O., Wetzel, S., Meyer, U.: CaPTIF: Comprehensive Performance TestIng Framework. In: Nielsen, B., Weise, C. (eds.) ICTSS 2012. LNCS, vol. 7641, pp. 55–70. Springer, Heidelberg (2012)CrossRefGoogle Scholar
  20. 20.
    Mayer, D.A., Teubert, D., Wetzel, S., Meyer, U.: Implementation and Performance Evaluation of Privacy-Preserving Fair Reconciliation Protocols on Ordered Sets. In: Conference on Data and Application Security and Privacy (CODASPY). ACM (2011)Google Scholar
  21. 21.
    Mayer, D.A., Wetzel, S.: Verifiable Private Equality Test: Enabling Unbiased 2-Party Reconciliation on Ordered Sets in the Malicious Model. In: Symposium on Information, Computer and Communications Security (ASIACCS). ACM (2012)Google Scholar
  22. 22.
    Meyer, U.: Secure Roaming and Handover Procedures in Wireless Access Networks. PhD Thesis, Darmstadt University of Technology (2005)Google Scholar
  23. 23.
    Meyer, U., Wetzel, S., Ioannidis, S.: Distributed Privacy-Preserving Policy Reconciliation. In: International Conference on Communications (ICC). IEEE (2007)Google Scholar
  24. 24.
    Meyer, U., Wetzel, S., Ioannidis, S.: New Advances on Privacy-preserving Policy Reconciliation. Cryptology ePrint Archive, 2010/064 (2010)Google Scholar
  25. 25.
    Narayanan, G.S., Aishwarya, T., Agrawal, A., Patra, A., Choudhary, A., Rangan, C.P.: Multi Party Distributed Private Matching, Set Disjointness and Cardinality of Set Intersection with Information Theoretic Security. In: Garay, J.A., Miyaji, A., Otsuka, A. (eds.) CANS 2009. LNCS, vol. 5888, pp. 21–40. Springer, Heidelberg (2009)CrossRefGoogle Scholar
  26. 26.
    Neugebauer, G., Brutschy, L., Meyer, U., Wetzel, S.: Design and Implementation of Privacy-Preserving Reconciliation Protocols. In: International Workshop on Privacy and Anonymity in the Information Society (PAIS). ACM (2013)Google Scholar
  27. 27.
    Neugebauer, G., Brutschy, L., Meyer, U., Wetzel, S.: Privacy-Preserving Multi-Party Reconciliation Secure in the Malicious Model. In: International Workshop on Data Privacy Management (DPM). ACM (2013)Google Scholar
  28. 28.
    Neugebauer, G., Meyer, U.: SMC-MuSe: A Framework for Secure Multi-Party Computation on MultiSets, RWTH Aachen University Technical Report AIB-2012-16 (2012)Google Scholar
  29. 29.
    Neugebauer, G., Meyer, U., Wetzel, S.: Fair and Privacy-Preserving Multi-Party Protocols for Reconciling Ordered Input Sets. In: Burmester, M., Tsudik, G., Magliveras, S., Ilić, I. (eds.) ISC 2010. LNCS, vol. 6531, pp. 136–151. Springer, Heidelberg (2011)CrossRefGoogle Scholar
  30. 30.
    Neugebauer, G., Meyer, U., Wetzel, S.: Fair and Privacy-Preserving Multi-Party Protocols for Reconciling Ordered Input Sets (Extended Version) (2011),
  31. 31.
    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)CrossRefGoogle Scholar
  32. 32.
    PreFairAppl—Private and Fair Applications (2013),
  33. 33.
    Sang, Y., Shen, H.: Privacy Preserving Set Intersection Based on Bilinear Groups. In: Proc. of the Thirty-First AACCS. Australian Computer Science Conference (ACSC), vol. 74, Australian Computer Society, Inc. (2008)Google Scholar
  34. 34.
    Weingarten, F., Neugebauer, G., Meyer, U., Wetzel, S.: Privacy-Preserving Multi-Party Reconciliation using Fully Homomorphic Encryption. In: Lopez, J., Huang, X., Sandhu, R. (eds.) NSS 2013. LNCS, vol. 7873, pp. 493–506. Springer, Heidelberg (2013)CrossRefGoogle Scholar
  35. 35.
    Yao, A.C.: Protocols for Secure Computations. In: Symposium on Foundations of Computer Science (SFCS). IEEE (1982)Google Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2013

Authors and Affiliations

  • Ulrike Meyer
    • 1
  • Susanne Wetzel
    • 2
  1. 1.Department of Computer ScienceRWTH AachenAachenGermany
  2. 2.Department of Computer ScienceStevens Institute of TechnologyHobokenUSA

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