Abstract: A differentially private security system communicatively coupled to a database storing restricted data receives a database query from a client. The database query includes an operation, a target accuracy, and a maximum privacy spend for the query. The system performs the operation to produce a result, then injects the result with noise sampled from a Laplace distribution to produce a differentially private result. The system iteratively calibrates the noise value of the differentially private result using a secondary distribution different from the Laplace distribution and a new fractional privacy spend. The system ceases to iterate when an iteration uses the maximum privacy spend or a relative error of the differentially private result is determined to satisfy the target accuracy, or both. The system sends the differentially private result to the client.

Abstract: Techniques are described for budget tracking in a differentially private security system. A request to perform a query of a private database system is received by a privacy device from a client device. The request is associated with a level of differential privacy. A privacy budget corresponding to the received request is accessed by the privacy device. The privacy budget includes a cumulative privacy spend and a maximum privacy spend, the cumulative privacy spend representative of previous queries of the private database system. A privacy spend associated with the received request is determined by the privacy device based at least in part on the level of differential privacy associated with the received request. If a sum of the determined privacy spend and the cumulative privacy spend is less than the maximum privacy spend, the query is performed. Otherwise a security action is performed based on a security policy.