Utility-Aware Synthesis of Differentially Private and Attack-Resilient Location Traces
Author:
Affiliation:
1. Georgia Institute of Technology, Atlanta, GA, USA
Funder
Research Coordination Network (RCN) on Big Data and Smart Cities
National Science Foundation
IBM Faculty Award
Publisher
ACM
Link
https://dl.acm.org/doi/pdf/10.1145/3243734.3243741
Reference53 articles.
1. Gergely Acs and Claude Castelluccia. 2014. A case study: Privacy preserving release of spatio-temporal density in paris Proceedings of the 20th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining. ACM 1679--1688. 10.1145/2623330.2623361 Gergely Acs and Claude Castelluccia. 2014. A case study: Privacy preserving release of spatio-temporal density in paris Proceedings of the 20th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining. ACM 1679--1688. 10.1145/2623330.2623361
2. Geo-indistinguishability
3. Supporting anonymous location queries in mobile environments with privacygrid
4. Nicolás E Bordenabe Konstantinos Chatzikokolakis and Catuscia Palamidessi. 2014. Optimal geo-indistinguishable mechanisms for location privacy Proceedings of the 2014 ACM SIGSAC Conference on Computer and Communications Security. ACM 251--262. 10.1145/2660267.2660345 Nicolás E Bordenabe Konstantinos Chatzikokolakis and Catuscia Palamidessi. 2014. Optimal geo-indistinguishable mechanisms for location privacy Proceedings of the 2014 ACM SIGSAC Conference on Computer and Communications Security. ACM 251--262. 10.1145/2660267.2660345
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