ASIACRYPT '96 Proceedings of the International Conference on the Theory and Applications of Cryptology and Information Security: Advances in Cryptology
Privacy, accuracy, and consistency too: a holistic solution to contingency table release
Proceedings of the twenty-sixth ACM SIGMOD-SIGACT-SIGART symposium on Principles of database systems
Releasing search queries and clicks privately
Proceedings of the 18th international conference on World wide web
Privacy integrated queries: an extensible platform for privacy-preserving data analysis
Proceedings of the 2009 ACM SIGMOD International Conference on Management of data
Differential privacy: a survey of results
TAMC'08 Proceedings of the 5th international conference on Theory and applications of models of computation
Towards an axiomatization of statistical privacy and utility
Proceedings of the twenty-ninth ACM SIGMOD-SIGACT-SIGART symposium on Principles of database systems
Differentially private aggregation of distributed time-series with transformation and encryption
Proceedings of the 2010 ACM SIGMOD International Conference on Management of data
Collaborative, privacy-preserving data aggregation at scale
PETS'10 Proceedings of the 10th international conference on Privacy enhancing technologies
Boosting the accuracy of differentially private histograms through consistency
Proceedings of the VLDB Endowment
P4P: practical large-scale privacy-preserving distributed computation robust against malicious users
USENIX Security'10 Proceedings of the 19th USENIX conference on Security
A new untraceable off-line electronic cash system
Electronic Commerce Research and Applications
Privad: practical privacy in online advertising
Proceedings of the 8th USENIX conference on Networked systems design and implementation
Anonygator: privacy and integrity preserving data aggregation
Proceedings of the ACM/IFIP/USENIX 11th International Conference on Middleware
ICALP'06 Proceedings of the 33rd international conference on Automata, Languages and Programming - Volume Part II
Differential privacy with information flow control
Proceedings of the ACM SIGPLAN 6th Workshop on Programming Languages and Analysis for Security
Our data, ourselves: privacy via distributed noise generation
EUROCRYPT'06 Proceedings of the 24th annual international conference on The Theory and Applications of Cryptographic Techniques
Calibrating noise to sensitivity in private data analysis
TCC'06 Proceedings of the Third conference on Theory of Cryptography
Detecting and defending against third-party tracking on the web
NSDI'12 Proceedings of the 9th USENIX conference on Networked Systems Design and Implementation
Towards statistical queries over distributed private user data
NSDI'12 Proceedings of the 9th USENIX conference on Networked Systems Design and Implementation
Language-based information-flow security
IEEE Journal on Selected Areas in Communications
SplitX: high-performance private analytics
Proceedings of the ACM SIGCOMM 2013 conference on SIGCOMM
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Today, websites commonly use third party web analytics services t obtain aggregate information about users that visit their sites. This information includes demographics and visits to other sites as well as user behavior within their own sites. Unfortunately, to obtain this aggregate information, web analytics services track individual user browsing behavior across the web. This violation of user privacy has been strongly criticized, resulting in tools that block such tracking as well as anti-tracking legislation and standards such as Do-Not-Track. These efforts, while improving user privacy, degrade the quality of web analytics. This paper presents the first design of a system that provides web analytics without tracking. The system gives users differential privacy guarantees, can provide better quality analytics than current services, requires no new organizational players, and is practical to deploy. This paper describes and analyzes the design, gives performance benchmarks, and presents our implementation and deployment across several hundred users.