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Revisiting Location Privacy from a Side-Channel Analysis Viewpoint

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Progress in Cryptology – AFRICACRYPT 2019 (AFRICACRYPT 2019)

Part of the book series: Lecture Notes in Computer Science ((LNSC,volume 11627))

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Abstract

Inspired by the literature on side-channel attacks against cryptographic implementations, we describe a framework for the analysis of location privacy. It allows us to revisit (continuous) re-identification attacks with a combination of information theoretic and security metrics. Our results highlight conceptual differences between re-identification attacks exploiting leakages that are internal or external to a pseudonymised database. They put forward the amount of data to collect in order to estimate a predictive model as an important – yet less discussed – dimension of privacy assessments. They finally leverage recent results on the security evaluations/certification of cryptographic implementations to connect information theoretic and security metrics, and to formally bound the risk of re-identification with external leakages.

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Notes

  1. 1.

    The word “independent” does not refer to the fact that these observations are truly independent, but only to the fact that such observations are exploited assuming it.

  2. 2.

    https://snap.stanford.edu/data/loc-brightkite.html (4/2008 - 10/2010).

  3. 3.

    This data set is not publicly available (1/2010 - 2/2016).

  4. 4.

    https://www.fordgobike.com/system-data (8/2013 - 8/2016).

  5. 5.

    With c a small constant depending on \(\mathrm {H[U]}\) and the target success rate (e.g., \(c=\mathrm {H[U]}\) is a usual heuristic that corresponds to a success rate of approximately 80%).

  6. 6.

    Note that the bound is here given for 1st-order independent models, as shown in the left part of the figure, the bound for the exshaustive models is stuck at \(\mathrm {H}[U]\).

References

  1. Andrés, M.E., Bordenabe, N.E., Chatzikokolakis, K., Palamidessi, C.: Geo-indistinguishability: differential privacy for location-based systems. In: Sadeghi, A.-R., Gligor, V.D., Yung, M. (eds.), ACM SIGSAC, pp. 901–914. ACM (2013)

    Google Scholar 

  2. Beresford, A.R., Stajano, F.: Location privacy in pervasive computing. IEEE Pervasive Comput. 2(1), 46–55 (2003)

    Article  Google Scholar 

  3. Bronchain, O., Hendrickx, J.M., Massart, C., Olshevsky, A., Standaert, F.-X.: Leakage certification revisited: Bounding model errors in side-channel security evaluations. IACR Cryptology ePrint Archive 2019:132 (2019)

    Google Scholar 

  4. Cho, E., Myers, S.A., Leskovec, J.: Friendship and mobility: user movement in location-based social networks. In: Apté, C., Ghosh, J., Smyth, P. (eds.) ACM SIGKDD, pp. 1082–1090. ACM (2011)

    Google Scholar 

  5. de Montjoye, Y.-A., Hidalgo, C.A., Verleysen, M., Blondel, V.: Unique in the crowd: the privacy bounds of human mobility. Nat. Sci. Rep. 3(1376), 5 (2013)

    Google Scholar 

  6. de Montjoye, Y.-A., Radaelli, L., Singh, V.K., Pentland, A.S.: Unique in the shopping mall: on the reidentifiability of credit card metadata. Science 347(6221), 536–539 (2015)

    Article  Google Scholar 

  7. Díaz, C., Seys, S., Claessens, J., Preneel, B.: Towards measuring anonymity. In: Dingledine, R., Syverson, P. (eds.) PET 2002. LNCS, vol. 2482, pp. 54–68. Springer, Heidelberg (2003). https://doi.org/10.1007/3-540-36467-6_5

    Chapter  Google Scholar 

  8. Duc, A., Faust, S., Standaert, F.-X.: Making masking security proofs concrete. In: Oswald, E., Fischlin, M. (eds.) EUROCRYPT 2015. LNCS, vol. 9056, pp. 401–429. Springer, Heidelberg (2015). https://doi.org/10.1007/978-3-662-46800-5_16

    Chapter  Google Scholar 

  9. Durvaux, F., Standaert, F.-X., Pozo, S.M.D.: Towards easy leakage certification: extended version. J. Cryptographic Engineering 7(2), 129–147 (2017)

    Article  Google Scholar 

  10. Durvaux, F., Standaert, F.-X., Veyrat-Charvillon, N.: How to certify the leakage of a chip? In: Nguyen, P.Q., Oswald, E. (eds.) EUROCRYPT 2014. LNCS, vol. 8441, pp. 459–476. Springer, Heidelberg (2014). https://doi.org/10.1007/978-3-642-55220-5_26

    Chapter  Google Scholar 

  11. Dwork, C.: Differential privacy: a survey of results. In: Agrawal, M., Du, D., Duan, Z., Li, A. (eds.) TAMC 2008. LNCS, vol. 4978, pp. 1–19. Springer, Heidelberg (2008). https://doi.org/10.1007/978-3-540-79228-4_1

    Chapter  MATH  Google Scholar 

  12. Fung, B.C.M., Wang, K., Chen, R., Yu, P.S.: Privacy-preserving data publishing: a survey of recent developments. ACM Comput. Surv. 42(4), 1–53 (2010)

    Article  Google Scholar 

  13. Gambs, S., Killijian, M.-O., del Prado Cortez, M.N.: Next place prediction using mobility markov chains. In: Proceedings of the First Workshop on Measurement, Privacy, and Mobility, MPM 2012, pp. 3:1–3:6 (2012)

    Google Scholar 

  14. Machanavajjhala, A., Kifer, D., Gehrke, J., Venkitasubramaniam, M.: L-diversity: privacy beyond k-anonymity. TKDD 1(1), 3 (2007)

    Article  Google Scholar 

  15. Maouche, M., Ben Mokhtar, S., Bouchenak, S.: Ap-attack: a novel re-identification attack on mobility datasets. In: Kaafar, D., Zhou, G. (eds.) MobiQuitous. ACM (2017)

    Google Scholar 

  16. Oya, S., Troncoso, C., Pérez-González, F.: Is geo-indistinguishability what you are looking for? In: Thuraisingham, B.M., Lee, A.J. (eds.) Proceedings of the 2017 on Workshop on Privacy in the Electronic Society, pp. 137–140. ACM (2017)

    Google Scholar 

  17. Samarati, P., Sweeney, L.: Generalizing data to provide anonymity when disclosing information (abstract). In: Mendelzon, A.O., Paredaens, J. (eds.) ACM SIGACT-SIGMOD-SIGART, p. 188. ACM Press (1998)

    Google Scholar 

  18. Serjantov, A., Danezis, G.: Towards an information theoretic metric for anonymity. In: Dingledine, R., Syverson, P. (eds.) PET 2002. LNCS, vol. 2482, pp. 41–53. Springer, Heidelberg (2003). https://doi.org/10.1007/3-540-36467-6_4

    Chapter  Google Scholar 

  19. Shokri, R., Theodorakopoulos, G., Le Boudec, J.-Y., Hubaux, J.-P.: IEEE s&p. pp. 247–262. IEEE Computer Society (2011)

    Google Scholar 

  20. Standaert, F.-X., Malkin, T.G., Yung, M.: A unified framework for the analysis of side-channel key recovery attacks. In: Joux, A. (ed.) EUROCRYPT 2009. LNCS, vol. 5479, pp. 443–461. Springer, Heidelberg (2009). https://doi.org/10.1007/978-3-642-01001-9_26

    Chapter  Google Scholar 

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Acknowledgments

François-Xavier Standaert is a Senior Research Associate of the Belgian Fund for Scientific Research (FNRS-F.R.S.). This work has been funded in parts by the ERC project SWORD (Consolidator Grant 724725).

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Authors and Affiliations

  1. ICTEAM - Crypto Group, Université Catholique de Louvain, Louvain-la-Neuve, Belgium

    Clément Massart & François-Xavier Standaert

Authors
  1. Clément Massart
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  2. François-Xavier Standaert
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Corresponding author

Correspondence to Clément Massart .

Editor information

Editors and Affiliations

  1. Technical University of Darmstadt, Darmstadt, Germany

    Johannes Buchmann

  2. Université de Caen, Caen, France

    Abderrahmane Nitaj

  3. Al Akhawayn University, Ifrane, Morocco

    Tajjeeddine Rachidi

A Additional Figure

A Additional Figure

Fig. 8.
figure 8

Daily usage of BikeShare stations for three users (ZIP codes).

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Massart, C., Standaert, FX. (2019). Revisiting Location Privacy from a Side-Channel Analysis Viewpoint. In: Buchmann, J., Nitaj, A., Rachidi, T. (eds) Progress in Cryptology – AFRICACRYPT 2019. AFRICACRYPT 2019. Lecture Notes in Computer Science(), vol 11627. Springer, Cham. https://doi.org/10.1007/978-3-030-23696-0_17

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  • DOI: https://doi.org/10.1007/978-3-030-23696-0_17

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  • Online ISBN: 978-3-030-23696-0

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