Haze: Privacy-preserving real-time traffic statistics

GIS: Proceedings of the ACM International Symposium on Advances in Geographic Information Systems

Volumn , Issue , 2013, Pages 530-533

  Brown, Joshua W S ^a   Ohrimenko, Olga ^a   Tamassia, Roberto ^a  

^a BROWN UNIVERSITY   (United States)

Author keywords

privacy; private aggregation; traffic statistics

Indexed keywords

MOBILE APPLICATIONS; MOBILE SERVICE; PRIVACY PRESERVING; PRIVATE AGGREGATIONS; REAL TIME TRAFFICS; SENSITIVE INFORMATIONS; TRAFFIC CONDITIONS; TRAFFIC STATISTICS;

DATA PRIVACY; GEOGRAPHIC INFORMATION SYSTEMS;

TRAFFIC SURVEYS;

EID: 84893498172     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1145/2525314.2525323     Document Type: Conference Paper

References (15)

1. R. Assam, M. Hassani, and T. Seidl. Differential private trajectory protection of moving objects. In ACM SIGSPATIAL Workshop on GeoStreaming, IWGS, pages 68-77, 2012.
2. T. Bhattacharya, L. Kulik, and J. Bailey. Extracting significant places from mobile user GPS trajectories: a bearing change based approach. In ACM Conf. on Advances in Geographic Information Systems, SIGSPATIAL, pages 398-401, 2012.
3. J.W. S. Brown, O. Ohrimenko, and R. Tamassia. Haze: Privacy-preserving real-time traffic statistics. CoRR, abs/1309.3515, 2013.
4. M. Burkhart, M. Strasser, D. Many, and X. Dimitropoulos. SEPIA: privacy-preserving aggregation of multi-domain network events and statistics. In USENIX Conf. on Security, 2010.
5. B. Carbunar, M. Rahman, J. Ballesteros, and N. Rishe. Eat the cake and have it too: Privacy preserving location aggregates in geosocial networks. CoRR, abs/1304.3513, 2013.
6. A. M. Davis, D. Chmelev, and M. R. Clarkson. Civitas: Implementation of a threshold cryptosystem. Computing and Information Science Technical Report, Cornell U., 2008. http://hdl.handle.net/1813/11661.
7. C. Dwork, F. McSherry, K. Nissim, and A. Smith. Calibrating noise to sensitivity in private data analysis. In Theory of Cryptography, TCC, pages 265-284, 2006. (Pubitemid 43979853)
8. V. V. Elango, S. Khoeini, Y. Xu, and R. Guensler. Longitudinal GPS travel data and breach of privacy via enhanced spatial and demographic analysis. In Transportation Research Board 92nd Annual Meeting, 2013.
9. L. Fan, L. Xiong, and V. Sunderam. Differentially private multi-dimensional time series release for traffic monitoring. In 27th Annual IFIP WG 11.3 Conference, DBSec, pages 33-48, 2013.
10. TAPASCologne Project. Accessed in June, 2013.
11. J. Krumm. Inference attacks on location tracks. In Int. Conf. on Pervasive Computing, PERVASIVE, pages 127-143, 2007.
12. A. Monreale, W. Wang, F. Pratesi, S. Rinzivillo, D. Pedreschi, G. Andrienko, and N. Andrienko. Privacy-preserving distributed movement data aggregation. In Geographic Information Science at the Heart of Europe, AGILE, pages 225-245, 2013.
13. R. A. Popa, A. J. Blumberg, H. Balakrishnan, and F. H. Li. Privacy and accountability for location-based aggregate statistics. In ACM Conf. on Computer and Communications Security, CCS, pages 653-666, 2011.
14. V. Rastogi and S. Nath. Differentially private aggregation of distributed time-series with transformation and encryption. In ACM Conf. on Management of Data, SIGMOD, pages 735-746, 2010.
15. E. Shi, T.-H. H. Chan, E. G. Rieffel, R. Chow, and D. Song. Privacy-preserving aggregation of time-series data. In Symp. on Network and Distributed System Security, NDSS, 2011.