Privacy-Preserving Computation and Verification of Aggregate Queries on Outsourced Databases
PETS '09 Proceedings of the 9th International Symposium on Privacy Enhancing Technologies
Accurate and large-scale privacy-preserving data mining using the election paradigm
Data & Knowledge Engineering
Self-enforcing Private Inference Control
ProvSec '09 Proceedings of the 3rd International Conference on Provable Security
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We study private inference control for aggregate queries, such as those provided by statistical databases or modern database languages, to a database in a way that satisfies privacy requirements and inference control requirements. For each query, the client learns the value of the function for that query if and only if the query passes a specified in- ference control rule. The server learns nothing about the queries, and the client learns nothing other than the query output for passing queries. We present general protocols for aggregate queries with private inference control.