The continuously increasing use of location-based services poses an important threat to the privacy of users. A natural defense is to employ an obfuscation mechanism, such as those providing geo-indistinguishability, a framework for obtaining formal privacy guarantees that has become popular in recent years.
Ideally, one would like to employ an optimal obfuscation mechanism, providing the best utility among those satisfying the required privacy level. In theory optimal mechanisms can be constructed via linear programming. In practice, however, this is only feasible for a radically small number of locations. As a consequence, all known applications of geo-indistinguishability simply use noise drawn from a planar Laplace distribution.
In this work, we study methods for substantially improving the utility of location obfuscation, while maintaining practical applicability as a main goal. We provide such solutions for both infinite (continuous or discrete) as well as large but finite domains of locations, using a Bayesian remapping procedure as a key ingredient. We evaluate our techniques in two real world complete datasets, without any restriction on the evaluation area, and show important utility improvements with respect to the standard planar Laplace approach.
If the inline PDF is not rendering correctly, you can download the PDF file here.
 K. Orland “Stalker Victims Should Check For GPS.” The Associated Press 2003. http://www.cbsnews.com/news/stalker-victims-should-check-for-gps/.
 J. Brownlee “This Creepy App Isn’t Just Stalking Women Without Their Knowledge It’s A Wake-Up Call About Facebook Privacy (Update)” 2012. http://www.cultofmac.com/157641/.
 J. Simerman “FasTrak to courthouse.” East Bay Times 2007. http://www.eastbaytimes.com/2007/06/05/fastrak-to-courthouse/.
 D. Ashbrook and T. Starner “Using gps to learn significant locations and predict movement across multiple users” Personal and Ubiquitous Computing vol. 7 no. 5 pp. 275–286 2003.
 R. Shokri G. Theodorakopoulos C. Troncoso J.-P. Hubaux and J.-Y. L. Boudec “Protecting location privacy: optimal strategy against localization attacks” in Proc. of CCS pp. 617–627 ACM 2012.
 M. E. Andrés N. E. Bordenabe K. Chatzikokolakis and C. Palamidessi “Geo-indistinguishability: differential privacy for location-based systems” in Proc. of CCS pp. 901–914 ACM 2013.
 N. E. Bordenabe K. Chatzikokolakis and C. Palamidessi “Optimal geo-indistinguishable mechanisms for location privacy” in Proc. of CCS 2014.
 R. Shokri “Privacy games: Optimal user-centric data obfuscation” Proceedings on Privacy Enhancing Technologies vol. 2015 no. 2 pp. 299–315 2015.
 C. Dwork “Differential privacy” in Proc. of ICALP vol. 4052 of LNCS pp. 1–12 Springer 2006.
 L. Pournajaf L. Xiong V. Sunderam and X. Xu “Stac: Spatial task assignment for crowd sensing with cloaked participant locations” in Proceedings of the 23rd SIGSPATIAL Int. Conf. on Advances in Geographic Information Systems GIS ’15 pp. 90:1–90:4 ACM 2015.
 Y. Xiao and L. Xiong “Protecting locations with differential privacy under temporal correlations” in Proc. of CCS pp. 1298–1309 ACM 2015.
 A. Ghosh T. Roughgarden and M. Sundararajan “Universally utility-maximizing privacy mechanisms” in Proc. of STOC pp. 351–360 ACM 2009.
 K. Chatzikokolakis C. Palamidessi and M. Stronati “Constructing elastic distinguishability metrics for location privacy” PoPETs vol. 2015 no. 2 pp. 156–170 2015.
 E. ElSalamouny K. Chatzikokolakis and C. Palamidessi “Generalized differential privacy: Regions of priors that admit robust optimal mechanisms” in Horizons of the Mind vol. 8464 of LNCS pp. 292–318 Springer Int. Publishing 2014.
 M. Gruteser and D. Grunwald “Anonymous usage of location-based services through spatial and temporal cloaking” in Proc. of MobiSys USENIX 2003.
 P. Samarati and L. Sweeney “Generalizing data to provide anonymity when disclosing information (abstract)” in Proc. of PODS pp. 188–188 ACM Press 1998.
 L. Sweeney “k-anonymity: A model for protecting privacy” Int. Journal of Uncertainty Fuzziness and Knowledge-Based Systems vol. 10 no. 5 pp. 557–570 2002.
 L. Sweeney “Achieving k-anonymity privacy protection using generalization and suppression” Int. Journal of Uncertainty Fuzziness and Knowledge-Based Systems vol. 10 no. 5 pp. 571–588 2002.
 P. Samarati “Protecting respondents’ identities in microdata release” IEEE Trans. Knowl. Data Eng vol. 13 no. 6 pp. 1010–1027 2001.
 A. Machanavajjhala D. Kifer J. Gehrke and M. Venkitasubramaniam “l-diversity: Privacy beyond k-anonymity” ACM Trans. on Knowledge Discovery from Data (TKDD) vol. 1 no. 1 p. 3 2007.
 N. Li T. Li and S. Venkatasubramanian “t-closeness: Privacy beyond k-anonymity and l-diversity.” in ICDE vol. 7 pp. 106–115 2007.
 A. Solanas F. Sebé and J. Domingo-Ferrer “Microaggregation-based heuristics for p-sensitive k-anonymity: one step beyond” in Proc. of PAIS 2008 ACM Int. Conf. Proceeding Series pp. 61–69 ACM 2008.
 A. R. Beresford and F. Stajano “Location privacy in pervasive computing” IEEE Pervasive Computing vol. 2 no. 1 pp. 46–55 2003.
 A. Machanavajjhala D. Kifer J. M. Abowd J. Gehrke and L. Vilhuber “Privacy: Theory meets practice on the map” in Proc. of ICDE pp. 277–286 IEEE 2008.
 S.-S. Ho and S. Ruan “Differential privacy for location pattern mining” in Proc. of SPRINGL pp. 17–24 ACM 2011.
 R. Dewri “Local differential perturbations: Location privacy under approximate knowledge attackers” IEEE Trans. on Mobile Computing vol. 99 no. PrePrints p. 1 2012.
 F. Durr P. Skvortsov and K. Rothermel “Position sharing for location privacy in non-trusted systems” in Proc. of PerCom 2011 pp. 189–196 IEEE 2011.
 E. ElSalamouny and S. Gambs “Differential privacy models for location-based services” Trans. on Data Privacy vol. 9 no. 1 pp. 15–48 2016.
 C. A. Ardagna M. Cremonini E. Damiani S. D. C. di Vimercati and P. Samarati “Location privacy protection through obfuscation-based techniques” in Proc. of DAS vol. 4602 of LNCS pp. 47–60 Springer 2007.
 B. Bamba L. Liu P. Pesti and T. Wang “Supporting anonymous location queries in mobile environments with privacygrid” in Proc. of WWW pp. 237–246 ACM 2008.
 M. Duckham and L. Kulik “A formal model of obfuscation and negotiation for location privacy” in Proc. of PERVASIVE vol. 3468 of LNCS pp. 152–170 Springer 2005.
 M. Xue P. Kalnis and H. Pung “Location diversity: Enhanced privacy protection in location based services” in Proc. of LoCA vol. 5561 of LNCS pp. 70–87 Springer 2009.
 B. Gedik and L. Liu “Location privacy in mobile systems: A personalized anonymization model” in Proc. of ICDCS pp. 620–629 IEEE 2005.
 K. Chatzikokolakis M. E. Andrés N. E. Bordenabe and C. Palamidessi “Broadening the scope of Differential Privacy using metrics” in Proc. of PETS vol. 7981 of LNCS pp. 82–102 Springer 2013.
 C. Dwork A. Roth et al. “The algorithmic foundations of differential privacy” Foundations and Trends® in Theor. Comp. Sci. vol. 9 no. 3–4 pp. 211–407 2014.
 L. Cooper and I. Katz “The weber problem revisited” Computers & Mathematics with Applications vol. 7 no. 3 pp. 225 – 234 1981.
 C. Dwork K. Kenthapadi F. McSherry I. Mironov and M. Naor “Our data ourselves: Privacy via distributed noise generation” in Proc. of EUROCRYPT vol. 4004 of LNCS pp. 486–503 Springer 2006.
 R. Shokri G. Theodorakopoulos J.-Y. L. Boudec and J.-P. Hubaux “Quantifying location privacy” in Proc. of S&P pp. 247–262 IEEE 2011.
 K. Chatzikokolakis C. Palamidessi and M. Stronati “A predictive differentially-private mechanism for mobility traces” in Proc. of PETS vol. 8555 of LNCS pp. 21–41 Springer 2014.