Advertisement

Privacy Preserving Group Linkage

  • Fengjun Li
  • Yuxin Chen
  • Bo Luo
  • Dongwon Lee
  • Peng Liu
Part of the Lecture Notes in Computer Science book series (LNCS, volume 6809)

Abstract

The problem of privacy preserving record linkage is to find the intersection of records from two parties, while not revealing any private records to each other. Recently, group linkage has been introduced to measure the similarity of groups of records [19]. When we extend the traditional privacy preserving record linkage methods to group linkage measurement, group membership privacy becomes vulnerable – record identity could be discovered from unlinked groups. In this paper, we introduce threshold privacy preserving group linkage (TPPGL) schemes, in which both parties only learn whether or not the groups are linked. Therefore, our approach is secure under group membership inference attacks. In experiments, we show that using the proposed TPPGL schemes, group membership privacy is well protected against inference attacks with a reasonable overhead.

Keywords

Group linkage privacy secure multi-party computation 

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. 1.
    Agrawal, R., Evfimievski, A., Srikant, R.: Information sharing across private databases. In: SIGMOD (2003)Google Scholar
  2. 2.
    Boneh, D., Goh, E.J., Nissim, K.: Evaluating 2-DNF formulas on ciphertexts. In: Kilian, J. (ed.) TCC 2005. LNCS, vol. 3378, pp. 325–341. Springer, Heidelberg (2005)Google Scholar
  3. 3.
    Elmagarmid, A.K., Ipeirotis, P.G., Verykios, V.S.: Duplicate record detection: A survey. IEEE TKDE, 19, 1–16 (2007)Google Scholar
  4. 4.
    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
  5. 5.
    El Gamal, T.: A public key cryptosystem and a signature scheme based on discrete logarithms. In: Blakely, G.R., Chaum, D. (eds.) CRYPTO 1984. LNCS, vol. 196, pp. 10–18. Springer, Heidelberg (1985)CrossRefGoogle Scholar
  6. 6.
    Gentry, C.: Fully homomorphic encryption using ideal lattices. In: STOC, pp. 169–178. ACM, New York (2009)Google Scholar
  7. 7.
    Goethals, B., Laur, S., Lipmaa, H., Mielikäinen, T.: On private scalar product computation for privacy-preserving data mining. In: Park, C.-s., Chee, S. (eds.) ICISC 2004. LNCS, vol. 3506, pp. 104–120. Springer, Heidelberg (2005)CrossRefGoogle Scholar
  8. 8.
    Goldwasser, S., Micali, S., Rackoff, C.: The knowledge complexity of interactive proof-systems. In: STOC 1985, pp. 291–304 (1985)Google Scholar
  9. 9.
    Guha, S.: Merging the results of approximate match operations. In: VLDB, pp. 636–647 (2004)Google Scholar
  10. 10.
    hai Do, H., Rahm, E.: Coma - a system for flexible combination of schema matching approaches. In: VLDB, pp. 610–621 (2002)Google Scholar
  11. 11.
    Hall, R., Fienberg, S.E.: Privacy-preserving record linkage. In: Domingo-Ferrer, J., Magkos, E. (eds.) PSD 2010. LNCS, vol. 6344, pp. 269–283. Springer, Heidelberg (2010)CrossRefGoogle Scholar
  12. 12.
    Hernández, M.A., Stolfo, S.J.: The merge/purge problem for large databases. In: SIGMOD (1995)Google Scholar
  13. 13.
    Inan, A., Kantarcioglu, M., Bertino, E., Scannapieco, M.: A hybrid approach to private record linkage. In: ICDE, pp. 496–505 (2008)Google Scholar
  14. 14.
    Inan, A., Kantarcioglu, M., Ghinita, G., Bertino, E.: Private record matching using differential privacy. In: EDBT, pp. 123–134 (2010)Google Scholar
  15. 15.
    Jaccard, P.: Étude comparative de la distribution florale dans une portion des alpes et des jura. Bulletin del la Société Vaudoise des Sciences Naturelles 37, 547–579 (1901)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.
    Murugesan, M., Jiang, W., Clifton, C., Si, L., Vaidya, J.: Efficient privacy-preserving similar document detection. The VLDB Journal 19, 457–475 (2010) 10.1007/s00778-009-0175-9CrossRefGoogle Scholar
  18. 18.
    Naccache, D., Stern, J.: A new public key cryptosystem based on higher residues. In: CCS, pp. 59–66. ACM, New York (1998)Google Scholar
  19. 19.
    On, B.-W., Koudas, N., Lee, D., Srivastava, D.: Group linkage. In: IEEE ICDE, Istanbul, Turkey, pp. 496–505 (April 2007)Google Scholar
  20. 20.
    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
  21. 21.
    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)CrossRefGoogle Scholar
  22. 22.
    Scannapieco, M., Figotin, I., Bertino, E., Elmagarmid, A.K.: Privacy preserving schema and data matching. In: SIGMOD, pp. 653–664. ACM, New York (2007)Google Scholar
  23. 23.
    Tang, J., Sun, J., Wang, C., Yang, Z.: Social influence analysis in large-scale networks. In: KDD, pp. 807–816 (2009)Google Scholar
  24. 24.
    Tejada, S., Knoblock, C.A.: Learning domain-independent string transformation weights for high accuracy object identification. In: ACM SIGKDD, pp. 350–359 (2002)Google Scholar
  25. 25.
    van Dijk, M., Gentry, C., Halevi, S., Vaikuntanathan, V.: Fully homomorphic encryption over the integers. In: Gilbert, H. (ed.) EUROCRYPT 2010. LNCS, vol. 6110, pp. 24–43. Springer, Heidelberg (2010)CrossRefGoogle Scholar
  26. 26.
    Verykios, V.S., Bertino, E., Fovino, I.N., Provenza, L.P., Saygin, Y., Theodoridis, Y.: State-of-the-art in privacy preserving data mining. SIGMOD Rec. 33(1), 50–57 (2004)CrossRefGoogle Scholar
  27. 27.
    Winkler, W.E.: Overview of record linkage and current research directions. Technical report, Bureau of the Census (2006)Google Scholar
  28. 28.
    Yao, A.C.: Protocols for secure computations. In: SFCS 1982: Proceedings of the 23rd Annual Symposium on Foundations of Computer Science, pp. 160–164. IEEE Computer Society, Washington, DC, USA (1982)Google Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2011

Authors and Affiliations

  • Fengjun Li
    • 1
  • Yuxin Chen
    • 1
  • Bo Luo
    • 1
  • Dongwon Lee
    • 2
  • Peng Liu
    • 2
  1. 1.Department of EECSUniversity of KansasUSA
  2. 2.College of ISTThe Pennsylvania State UniversityUSA

Personalised recommendations