Stalker Victims Should Check For GPS The Associated Pressvictims-should-check-for-gps, 2003. ,
This Creepy App Isn't Just Stalking Women Without Their Knowledge, It's A Wake-Up Call About Facebook Privacy (Update), 2012. ,
FasTrak to courthouse East Bay Times, 2007. ,
Using GPS to learn significant locations and predict movement across multiple users, Personal and Ubiquitous Computing, pp.275-286, 2003. ,
DOI : 10.1007/s00779-003-0240-0
URL : http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.14.2603
Protecting location privacy, Proceedings of the 2012 ACM conference on Computer and communications security, CCS '12, pp.617-627, 2012. ,
DOI : 10.1145/2382196.2382261
Geo-indistinguishability, Proceedings of the 2013 ACM SIGSAC conference on Computer & communications security, CCS '13, pp.901-914, 2013. ,
DOI : 10.1145/2508859.2516735
Optimal Geo-Indistinguishable Mechanisms for Location Privacy, Proceedings of the 2014 ACM SIGSAC Conference on Computer and Communications Security, CCS '14, 2014. ,
DOI : 10.1145/1620545.1620550
URL : https://hal.archives-ouvertes.fr/hal-00950479
Abstract, Proceedings on Privacy Enhancing Technologies, pp.299-315, 2015. ,
DOI : 10.1515/popets-2015-0024
Differential Privacy, Proc. of ICALP, pp.1-12, 2006. ,
DOI : 10.1007/11787006_1
Location Privacy Protection for Smartphone Users, Proceedings of the 2014 ACM SIGSAC Conference on Computer and Communications Security, CCS '14, pp.239-250, 2014. ,
DOI : 10.1109/MWC.2012.6155874
Anatomization and protection of mobile apps' location privacy threats, Proc. of USENIX Security 2015, pp.753-768, 2015. ,
Nearby Friend Discovery with Geo-indistinguishability to Stalkers, Procedia Computer Science, vol.34, pp.352-359, 2014. ,
DOI : 10.1016/j.procs.2014.07.036
URL : http://doi.org/10.1016/j.procs.2014.07.036
STAC, Proceedings of the 23rd SIGSPATIAL International Conference on Advances in Geographic Information Systems, GIS '15, pp.901-90, 2015. ,
DOI : 10.1145/2810103.2813640
Protecting Locations with Differential Privacy under Temporal Correlations, Proceedings of the 22nd ACM SIGSAC Conference on Computer and Communications Security, CCS '15, pp.1298-1309, 2015. ,
DOI : 10.1126/science.1177170
URL : http://arxiv.org/abs/1410.5919
Universally utility-maximizing privacy mechanisms, Proc. of STOC, pp.351-360, 2009. ,
DOI : 10.1145/1536414.1536464
URL : http://arxiv.org/abs/0811.2841
Abstract, Proceedings on Privacy Enhancing Technologies, vol.2015, issue.2, pp.156-170, 2015. ,
DOI : 10.1515/popets-2015-0023
Generalized Differential Privacy: Regions of Priors That Admit Robust Optimal Mechanisms, Horizons of the Mind, pp.292-318, 2014. ,
DOI : 10.1145/2382196.2382261
URL : https://hal.archives-ouvertes.fr/hal-01006380
Anonymous Usage of Location-Based Services Through Spatial and Temporal Cloaking, Proceedings of the 1st international conference on Mobile systems, applications and services, MobiSys '03, 2003. ,
DOI : 10.1145/1066116.1189037
URL : http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.115.1445
Generalizing data to provide anonymity when disclosing information (abstract), Proceedings of the seventeenth ACM SIGACT-SIGMOD-SIGART symposium on Principles of database systems , PODS '98, pp.188-188, 1998. ,
DOI : 10.1145/275487.275508
k-ANONYMITY: A MODEL FOR PROTECTING PRIVACY, International Journal of Uncertainty, Fuzziness and Knowledge-Based Systems, vol.2, issue.3, pp.557-570, 2002. ,
DOI : 10.1109/RISP.1993.287632
ACHIEVING k-ANONYMITY PRIVACY PROTECTION USING GENERALIZATION AND SUPPRESSION, International Journal of Uncertainty, Fuzziness and Knowledge-Based Systems, vol.2, issue.3, pp.571-588, 2002. ,
DOI : 10.1142/S021848850200165X
Protecting respondents identities in microdata release, IEEE Transactions on Knowledge and Data Engineering, vol.13, issue.6, pp.1010-1027, 2001. ,
DOI : 10.1109/69.971193
URL : http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.226.7472
-diversity, ACM Transactions on Knowledge Discovery from Data, vol.1, issue.1, p.3, 2007. ,
DOI : 10.1145/1217299.1217302
t-Closeness: Privacy Beyond k-Anonymity and l-Diversity, 2007 IEEE 23rd International Conference on Data Engineering, pp.106-115, 2007. ,
DOI : 10.1109/ICDE.2007.367856
URL : http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.157.824
Microaggregation-based heuristics for p-sensitive k-anonymity: one step beyond, Proc. of PAIS 2008, ACM Int. Conf. Proceeding Series, pp.61-69, 2008. ,
DOI : 10.1145/1379287.1379300
Location privacy in pervasive computing, IEEE Pervasive Computing, vol.2, issue.1, pp.46-55, 2003. ,
DOI : 10.1109/MPRV.2003.1186725
Privacy: Theory meets Practice on the Map, 2008 IEEE 24th International Conference on Data Engineering, pp.277-286, 2008. ,
DOI : 10.1109/ICDE.2008.4497436
URL : http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.119.9568
Differential privacy for location pattern mining, Proceedings of the 4th ACM SIGSPATIAL International Workshop on Security and Privacy in GIS and LBS, SPRINGL '11, pp.17-24, 2011. ,
DOI : 10.1145/2071880.2071884
Local Differential Perturbations: Location Privacy under Approximate Knowledge Attackers, PrePrints, 2012. ,
DOI : 10.1109/TMC.2012.208
Position sharing for location privacy in non-trusted systems Differential privacy models for location-based services, Proc. of PerCom, pp.189-196, 2011. ,
Location Privacy Protection Through Obfuscation-Based Techniques, Proc. of DAS, pp.47-60, 2007. ,
DOI : 10.1109/69.971193
URL : http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.73.9916
Supporting anonymous location queries in mobile environments with privacygrid, Proc. of WWW, pp.237-246, 2008. ,
DOI : 10.1145/1367497.1367531
URL : http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.119.4944
A Formal Model of Obfuscation and Negotiation for Location Privacy, Proc. of PERVA- SIVE, pp.152-170, 2005. ,
DOI : 10.1007/11428572_10
Location Diversity: Enhanced Privacy Protection in Location Based Services, Proc. of LoCA, pp.70-87, 2009. ,
DOI : 10.1007/978-3-642-01721-6_5
Location Privacy in Mobile Systems: A Personalized Anonymization Model, 25th IEEE International Conference on Distributed Computing Systems (ICDCS'05), pp.620-629, 2005. ,
DOI : 10.1109/ICDCS.2005.48
URL : http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.126.2697
Broadening the Scope of Differential Privacy Using Metrics, Proc. of PETS, pp.82-102, 2013. ,
DOI : 10.1007/978-3-642-39077-7_5
URL : https://hal.archives-ouvertes.fr/hal-00767210
The algorithmic foundations of differential privacy Foundations and Trends® in Theor, Comp. Sci, vol.9, pp.3-4, 2014. ,
The Weber problem revisited, Computers & Mathematics with Applications, vol.7, issue.3, pp.225-234, 1981. ,
DOI : 10.1016/0898-1221(81)90082-1
URL : http://doi.org/10.1016/0898-1221(81)90082-1
Our Data, Ourselves: Privacy Via Distributed Noise Generation, Proc. of EUROCRYPT, pp.486-503, 2006. ,
DOI : 10.1007/11761679_29
URL : http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.140.3527
Quantifying Location Privacy, 2011 IEEE Symposium on Security and Privacy, pp.247-262, 2011. ,
DOI : 10.1109/SP.2011.18
URL : https://hal.archives-ouvertes.fr/hal-01266229
A Predictive Differentially-Private Mechanism for Mobility Traces, Proc. of PETS, pp.21-41, 2014. ,
DOI : 10.1007/978-3-319-08506-7_2
URL : https://hal.archives-ouvertes.fr/hal-01011260