Publication | Closed Access
DataSynthesizer
137
Citations
6
References
2017
Year
Unknown Venue
EngineeringInformation SecurityData OwnersData ScienceStrong Privacy GuaranteesData AnonymizationManagementData IntegrationBig DataData SharingData ManagementData CreationData OwnerData PrivacyData ProtectionComputer SciencePrivacyData SecuritySynthetic DataData Modeling
To facilitate collaboration over sensitive data, we present DataSynthesizer, a tool that takes a sensitive dataset as input and generates a structurally and statistically similar synthetic dataset with strong privacy guarantees. The data owners need not release their data, while potential collaborators can begin developing models and methods with some confidence that their results will work similarly on the real dataset. The distinguishing feature of DataSynthesizer is its usability --- the data owner does not have to specify any parameters to start generating and sharing data safely and effectively.
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