Frequency Estimation of Internet Packet Streams with Limited Space
ESA '02 Proceedings of the 10th Annual European Symposium on Algorithms
Revealing information while preserving privacy
Proceedings of the twenty-second ACM SIGMOD-SIGACT-SIGART symposium on Principles of database systems
Approximate frequency counts over data streams
VLDB '02 Proceedings of the 28th international conference on Very Large Data Bases
Robust De-anonymization of Large Sparse Datasets
SP '08 Proceedings of the 2008 IEEE Symposium on Security and Privacy
New Efficient Attacks on Statistical Disclosure Control Mechanisms
CRYPTO 2008 Proceedings of the 28th Annual conference on Cryptology: Advances in Cryptology
Vanity fair: privacy in querylog bundles
Proceedings of the 17th ACM conference on Information and knowledge management
Releasing search queries and clicks privately
Proceedings of the 18th international conference on World wide web
The Differential Privacy Frontier (Extended Abstract)
TCC '09 Proceedings of the 6th Theory of Cryptography Conference on Theory of Cryptography
Differentially private recommender systems: building privacy into the net
Proceedings of the 15th ACM SIGKDD international conference on Knowledge discovery and data mining
Differential privacy under continual observation
Proceedings of the forty-second ACM symposium on Theory of computing
A firm foundation for private data analysis
Communications of the ACM
Differential privacy in new settings
SODA '10 Proceedings of the twenty-first annual ACM-SIAM symposium on Discrete Algorithms
ICALP'06 Proceedings of the 33rd international conference on Automata, Languages and Programming - Volume Part II
Efficient computation of frequent and top-k elements in data streams
ICDT'05 Proceedings of the 10th international conference on Database Theory
Calibrating noise to sensitivity in private data analysis
TCC'06 Proceedings of the Third conference on Theory of Cryptography
Boosting the accuracy of differentially private histograms through consistency
Proceedings of the VLDB Endowment
Compressive mechanism: utilizing sparse representation in differential privacy
Proceedings of the 10th annual ACM workshop on Privacy in the electronic society
Probabilistic relational reasoning for differential privacy
POPL '12 Proceedings of the 39th annual ACM SIGPLAN-SIGACT symposium on Principles of programming languages
Optimal private halfspace counting via discrepancy
STOC '12 Proceedings of the forty-fourth annual ACM symposium on Theory of computing
Differentially private continual monitoring of heavy hitters from distributed streams
PETS'12 Proceedings of the 12th international conference on Privacy Enhancing Technologies
Real-time aggregate monitoring with differential privacy
Proceedings of the 21st ACM international conference on Information and knowledge management
Private decayed predicate sums on streams
Proceedings of the 16th International Conference on Database Theory
Efficient and accurate strategies for differentially-private sliding window queries
Proceedings of the 16th International Conference on Extending Database Technology
The geometry of differential privacy: the sparse and approximate cases
Proceedings of the forty-fifth annual ACM symposium on Theory of computing
Probabilistic Relational Reasoning for Differential Privacy
ACM Transactions on Programming Languages and Systems (TOPLAS)
Pufferfish: A framework for mathematical privacy definitions
ACM Transactions on Database Systems (TODS)
Differentially private multi-dimensional time series release for traffic monitoring
DBSec'13 Proceedings of the 27th international conference on Data and Applications Security and Privacy XXVII
Monitoring web browsing behavior with differential privacy
Proceedings of the 23rd international conference on World wide web
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We ask the question - how can websites and data aggregators continually release updated statistics, and meanwhile preserve each individual user's privacy? Given a stream of 0's and 1's, we propose a differentially private continual counter that outputs at every time step the approximate number of 1's seen thus far. Our counter construction has error that is only poly-log in the number of time steps. We can extend the basic counter construction to allow websites to continually give top-k and hot items suggestions while preserving users' privacy.