Quantitative Approaches to the Protection of Private Information: State of the Art and Some Open Challenges

  • Catuscia Palamidessi
Part of the Lecture Notes in Computer Science book series (LNCS, volume 9036)


Privacy is a broad concept affecting a variety of modern-life activities. As a consequence, during the last decade there has been a vast amount of research on techniques to protect privacy, such as communication anonymizers [9], electronic voting systems [8], Radio-Frequency Identification (RFID) protocols [13] and private information retrieval schemes [7], to name a few.


  1. 1.
    Alvim, M.S., Chatzikokolakis, K., McIver, A., Morgan, C., Palamidessi, C., Smith, G.: Additive and multiplicative notions of leakage, and their capacities. In: IEEE 27th Computer Security Foundations Symposium, CSF 2014, Vienna, Austria, July 19-22, pp. 308–322. IEEE (2014)Google Scholar
  2. 2.
    Alvim, M.S., Chatzikokolakis, K., Palamidessi, C., Smith, G.: Measuring information leakage using generalized gain functions. In: Proceedings of the 25th IEEE Computer Security Foundations Symposium (CSF), pp. 265–279 (2012)Google Scholar
  3. 3.
    Andrés, M.E., Bordenabe, N.E., Chatzikokolakis, K., Palamidessi, C.: Geo-indistinguishability: differential privacy for location-based systems. In: Proceedings of the 20th ACM Conference on Computer and Communications Security (CCS 2013), pp. 901–914. ACM (2013)Google Scholar
  4. 4.
    Bordenabe, N.E., Chatzikokolakis, K., Palamidessi, C.: Optimal geo-indistinguishable mechanisms for location privacy. In: Proceedings of the 21th ACM Conference on Computer and Communications Security, CCS 2014 (2014)Google Scholar
  5. 5.
    Chatzikokolakis, K., Andrés, M.E., Bordenabe, N.E., Palamidessi, C.: Broadening the Scope of Differential Privacy Using Metrics. In: De Cristofaro, E., Wright, M. (eds.) PETS 2013. LNCS, vol. 7981, pp. 82–102. Springer, Heidelberg (2013)CrossRefGoogle Scholar
  6. 6.
    Chatzikokolakis, K., Palamidessi, C., Stronati, M.: A Predictive Differentially-Private Mechanism for Mobility Traces. In: De Cristofaro, E., Murdoch, S.J. (eds.) PETS 2014. LNCS, vol. 8555, pp. 21–41. Springer, Heidelberg (2014)CrossRefGoogle Scholar
  7. 7.
    Chor, B., Goldreich, O., Kushilevitz, E., Sudan, M.: Private information retrieval. In: Proceedings of the 36th Annual Symposium on Foundations of Computer Science, pp. 41–50. IEEE (1995)Google Scholar
  8. 8.
    Delaune, S., Kremer, S., Ryan, M.: Verifying privacy-type properties of electronic voting protocols. Journal of Computer Security 17(4), 435–487 (2009)Google Scholar
  9. 9.
    Dingledine, R., Mathewson, N., Syverson, P.F.: Tor: The second-generation onion router. In: Proceedings of the 13th USENIX Security Symposium, pp. 303–320. USENIX (2004)Google Scholar
  10. 10.
    Dwork, C.: Differential Privacy. In: Bugliesi, M., Preneel, B., Sassone, V., Wegener, I. (eds.) ICALP 2006. LNCS, vol. 4052, pp. 1–12. Springer, Heidelberg (2006)CrossRefGoogle Scholar
  11. 11.
    Dwork, C.: A firm foundation for private data analysis. Communications of the ACM 54(1), 86–96 (2011)CrossRefGoogle Scholar
  12. 12.
    Dwork, C., Lei, J.: Differential privacy and robust statistics. In: Mitzenmacher, M. (ed.) Proceedings of the 41st Annual ACM Symposium on Theory of Computing (STOC), Bethesda, MD, USA, May 31-June 2, pp. 371–380. ACM (2009)Google Scholar
  13. 13.
    Juels, A.: Rfid security and privacy: A research survey. IEEE Journal on Selected Areas in Communications 24(2), 381–394 (2006)CrossRefMathSciNetGoogle Scholar
  14. 14.
    McIver, A., Morgan, C., Smith, G., Espinoza, B., Meinicke, L.: Abstract Channels and Their Robust Information-Leakage Ordering. In: Abadi, M., Kremer, S. (eds.) POST 2014 (ETAPS 2014). LNCS, vol. 8414, pp. 83–102. Springer, Heidelberg (2014)CrossRefGoogle Scholar
  15. 15.
    Narayanan, A., Shmatikov, V.: De-anonymizing social networks. In: Proceedings of the 30th IEEE Symposium on Security and Privacy, pp. 173–187. IEEE Computer Society (2009)Google Scholar
  16. 16.
    Samarati, P.: Protecting respondents’ identities in microdata release. IEEE Trans. Knowl. Data. Eng. 13(6), 1010–1027 (2001)CrossRefGoogle Scholar
  17. 17.
    Samarati, P., Sweeney, L.: Generalizing data to provide anonymity when disclosing information (abstract). In: ACM (ed.) PODS 1998. Proceedings of the ACM SIGACT–SIGMOD–SIGART Symposium on Principles of Database Systems, Seattle, Washington, June 1-3, pp. 188–188. ACM Press (1998)Google Scholar

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© Springer-Verlag Berlin Heidelberg 2015

Authors and Affiliations

  • Catuscia Palamidessi
    • 1
  1. 1.INRIA Saclay and LIX, École PolytechniqueLe Chesnay CedexFrance

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