Revealing information while preserving privacy
Proceedings of the twenty-second ACM SIGMOD-SIGACT-SIGART symposium on Principles of database systems
Practical privacy: the SuLQ framework
Proceedings of the twenty-fourth ACM SIGMOD-SIGACT-SIGART symposium on Principles of database systems
Hiding the presence of individuals from shared databases
Proceedings of the 2007 ACM SIGMOD international conference on Management of data
Smooth sensitivity and sampling in private data analysis
Proceedings of the thirty-ninth annual ACM symposium on Theory of computing
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
A learning theory approach to non-interactive database privacy
STOC '08 Proceedings of the fortieth annual ACM symposium on Theory of computing
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
δ-Presence without Complete World Knowledge
IEEE Transactions on Knowledge and Data Engineering
Airavat: security and privacy for MapReduce
NSDI'10 Proceedings of the 7th USENIX conference on Networked systems design and implementation
ICALP'06 Proceedings of the 33rd international conference on Automata, Languages and Programming - Volume Part II
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
Proceedings of the 18th ACM SIGKDD international conference on Knowledge discovery and data mining
BLIP: non-interactive differentially-private similarity computation on bloom filters
SSS'12 Proceedings of the 14th international conference on Stabilization, Safety, and Security of Distributed Systems
Non-interactive differential privacy: a survey
Proceedings of the First International Workshop on Open Data
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Differential privacy is a recent notion, and while it is nice conceptually it has been difficult to apply in practice. The parameters of differential privacy have an intuitive theoretical interpretation, but the implications and impacts on the risk of disclosure in practice have not yet been studied, and choosing appropriate values for them is non-trivial. Although the privacy parameter ε in differential privacy is used to quantify the privacy risk posed by releasing statistics computed on sensitive data, ε is not an absolute measure of privacy but rather a relative measure. In effect, even for the same value of ε, the privacy guarantees enforced by differential privacy are different based on the domain of attribute in question and the query supported. We consider the probability of identifying any particular individual as being in the database, and demonstrate the challenge of setting the proper value of ε given the goal of protecting individuals in the database with some fixed probability.