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: A differentially private security system communicatively coupled to a database storing restricted data receives a database query from a client. The database query includes a relation indicative of data to perform the query upon and at least one privacy parameter indicative of a level of differential privacy with which to perform the query. The differentially private security system determines a noise type for the query. The differentially private security system determines a representation of probabilistic privacy loss for the query based on the determined noise type. The differentially private security system determines a privacy spend for the query using the generated representation of probabilistic privacy loss. The differentially private security system determines whether the determined privacy spend exceeds a privacy budget associated with the client.

Abstract: A hardware database privacy device is communicatively coupled to a private database system. The hardware database privacy device receives a request from a client device to perform a query of the private database system and identifies a level of differential privacy corresponding to the request. The identified level of differential privacy includes privacy parameters (?,?) indicating the degree of information released about the private database system. The hardware database privacy device identifies a set of operations to be performed on the set of data that corresponds to the requested query. After the set of data is accessed, the set of operations is modified based on the identified level of differential privacy such that a performance of the modified set of operations produces a result set that is (?,?)-differentially private.

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.

Abstract: A differentially private system receives a request from a client to perform a query on data stored in a database. The differentially private system establishes a set of permissions of the client with respect to the data in the database. The differentially private system deconstructs the query into query components. The query components include at least one relation that identifies a dataset in the database and at least one expressions specifying an operation to be performed in the identified dataset. The differentially private system identifies permissions necessary to perform the specified operation on the identified dataset. The differentially private system determines whether the established permissions grants of the client include the identified permissions necessary to perform the specified operation on the identified dataset. The differentially private system selectively executes the query responsive to the determination.

Abstract: A hardware database privacy device is communicatively coupled to a private database system. The hardware database privacy device receives a request from a client device to perform a query of the private database system and identifies a level of differential privacy corresponding to the request. The identified level of differential privacy includes privacy parameters (?,?) indicating the degree of information released about the private database system. The hardware database privacy device identifies a set of operations to be performed on the set of data that corresponds to the requested query. After the set of data is accessed, the set of operations is modified based on the identified level of differential privacy such that a performance of the modified set of operations produces a result set that is (?,?)-differentially private.

Abstract: A request from a client is received to generate a differentially private random forest classifier trained using a set of restricted data. The differentially private random forest classifier is generated in response to the request. Generating the differentially private random forest classifier includes determining a number of decision trees and generating the determined number of decision trees. Generating a decision tree includes generating a set of splits based on the restricted data, determining an information gain for each split, selecting a split from the set using an exponential mechanism, and adding the split to the decision tree. The differentially private random forest classifier is provided to the client.

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 a relation indicative of data to perform the query upon and at least one privacy parameter indicative of a level of differential privacy with which to perform the query. The differentially private security system determines a noise type for the query. The differentially private security system determines a representation of probabilistic privacy loss for the query based on the determined noise type. The differentially private security system determines a privacy spend for the query using the generated representation of probabilistic privacy loss. The differentially private security system determines whether the determined privacy spend exceeds a privacy budget associated with the client.

Abstract: A hardware database privacy device is communicatively coupled to a private database system. The hardware database privacy device receives a request from a client device to perform a query of the private database system and identifies a level of differential privacy corresponding to the request. The identified level of differential privacy includes privacy parameters (?,?) indicating the degree of information released about the private database system. The hardware database privacy device identifies a set of operations to be performed on the set of data that corresponds to the requested query. After the set of data is accessed, the set of operations is modified based on the identified level of differential privacy such that a performance of the modified set of operations produces a result set that is (?,?)-differentially private.

Abstract: Techniques are described for responding to queries of a private database system. A request is received from a client device to perform a query of the private database system. A level of differential privacy corresponding to the request is identified comprising privacy parameters ? and ?. A set of data stored in the private database system and a set of operations corresponding to the query are identified. The set of operations comprises generating a density plot visualization for one or more subsets of the set of data. The set of data is segmented into disjoint regions. For each disjoint region, a density is identified, and the density is plotted in a differentially private density plot visualization using one or more graphical elements.

Abstract: A differentially private security system is communicatively coupled to a database. The differentially private security system receives a request from a client device to perform a query of the database and identifies a level of differential privacy corresponding to the request. The identified level of differential privacy includes privacy parameters (?,?) indicating the degree of information released about the database. The differentially private security system performs a differentially private query upon a set of data in the database such that the performance of the query produces a result that is (?,?)-differentially private.

Abstract: A differentially private system receives a request from a client to perform a query on data stored in a database. The differentially private system establishes a set of permissions of the client with respect to the data in the database. The differentially private system deconstructs the query into query components. The query components include at least one relation that identifies a dataset in the database and at least one expressions specifying an operation to be performed in the identified dataset. The differentially private system identifies permissions necessary to perform the specified operation on the identified dataset. The differentially private system determines whether the established permissions grants of the client include the identified permissions necessary to perform the specified operation on the identified dataset. The differentially private system selectively executes the query responsive to the determination.

Abstract: A hardware database privacy device is communicatively coupled to a private database system. The hardware database privacy device receives a request from a client device to perform a query of the private database system and identifies a level of differential privacy corresponding to the request. The identified level of differential privacy includes privacy parameters (?,?) indicating the degree of information released about the private database system. The hardware database privacy device identifies a set of operations to be performed on the set of data that corresponds to the requested query. After the set of data is accessed, the set of operations is modified based on the identified level of differential privacy such that a performance of the modified set of operations produces a result set that is (?,?)-differentially private.

Abstract: A hardware database privacy device is communicatively coupled to a private database system. The hardware database privacy device receives a request from a client device to perform a query of the private database system and identifies a level of differential privacy corresponding to the request. The identified level of differential privacy includes privacy parameters (?,?) indicating the degree of information released about the private database system. The hardware database privacy device identifies a set of operations to be performed on the set of data that corresponds to the requested query. After the set of data is accessed, the set of operations is modified based on the identified level of differential privacy such that a performance of the modified set of operations produces a result set that is (?,?)-differentially private.

Abstract: A hardware database privacy device is communicatively coupled to a private database system. The hardware database privacy device receives a request from a client device to perform a query of the private database system and identifies a level of differential privacy corresponding to the request. The identified level of differential privacy includes privacy parameters (?,?) indicating the degree of information released about the private database system. The hardware database privacy device identifies a set of operations to be performed on the set of data that corresponds to the requested query. After the set of data is accessed, the set of operations is modified based on the identified level of differential privacy such that a performance of the modified set of operations produces a result set that is (?,?)-differentially private.