Publication | Closed Access
Linear dependent types for differential privacy
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Citations
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References
2013
Year
Unknown Venue
Privacy ProtectionEngineeringInformation SecurityFunctional AnalysisSingle RecordData ScienceSensitive InformationPrivacy SystemPrivacy EngineeringData ManagementStatisticsPrivacy By DesignData PrivacyComputer ScienceDifferential PrivacyPrivacyData SecurityCryptographyLinear Dependent Types
Differential privacy offers a way to answer queries about sensitive information while providing strong, provable privacy guarantees, ensuring that the presence or absence of a single individual in the database has a negligible statistical effect on the query's result. Proving that a given query has this property involves establishing a bound on the query's sensitivity---how much its result can change when a single record is added or removed.
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