A Framework for Generating Network-Based Moving Objects
Geoinformatica
A learning theory approach to non-interactive database privacy
STOC '08 Proceedings of the fortieth annual ACM symposium on Theory of computing
On the complexity of differentially private data release: efficient algorithms and hardness results
Proceedings of the forty-first annual ACM symposium on Theory of computing
Differential privacy under continual observation
Proceedings of the forty-second ACM symposium on Theory of computing
Differentially private aggregation of distributed time-series with transformation and encryption
Proceedings of the 2010 ACM SIGMOD International Conference on Management of data
Privacy integrated queries: an extensible platform for privacy-preserving data analysis
Communications of the ACM
Private and continual release of statistics
ICALP'10 Proceedings of the 37th international colloquium conference on Automata, languages and programming: Part II
Differentially private data release through multidimensional partitioning
SDM'10 Proceedings of the 7th VLDB conference on Secure data management
Boosting the accuracy of differentially private histograms through consistency
Proceedings of the VLDB Endowment
iReduct: differential privacy with reduced relative errors
Proceedings of the 2011 ACM SIGMOD International Conference on Management of data
Differential Privacy via Wavelet Transforms
IEEE Transactions on Knowledge and Data Engineering
An adaptive mechanism for accurate query answering under differential privacy
Proceedings of the VLDB Endowment
Calibrating noise to sensitivity in private data analysis
TCC'06 Proceedings of the Third conference on Theory of Cryptography
Differentially Private Spatial Decompositions
ICDE '12 Proceedings of the 2012 IEEE 28th International Conference on Data Engineering
Differentially Private Histogram Publication
ICDE '12 Proceedings of the 2012 IEEE 28th International Conference on Data Engineering
Real-time aggregate monitoring with differential privacy
Proceedings of the 21st ACM international conference on Information and knowledge management
Haze: privacy-preserving real-time traffic statistics
Proceedings of the 21st ACM SIGSPATIAL International Conference on Advances in Geographic Information Systems
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Sharing real-time traffic data can be of great value to understanding many important phenomena, such as congestion patterns or popular places. To this end, private user data must be aggregated and shared continuously over time with data privacy guarantee. However, releasing time series data with standard differential privacy mechanism can lead to high perturbation error due to the correlation between time stamps. In addition, data sparsity in the spatial domain imposes another challenge to user privacy as well as utility. To address the challenges, we propose a real-time framework that guarantees differential privacy for individual users and releases accurate data for research purposes. We present two estimation algorithms designed to utilize domain knowledge in order to mitigate the effect of perturbation error. Evaluations with simulated traffic data show our solutions outperform existing methods in both utility and computation efficiency, enabling real-time data sharing with strong privacy guarantee.