Systems and methods of secure analytics using an encrypted analytics matrix are disclosed herein. An example method includes encoding an analytic parameter set using a homomorphic encryption scheme as a homomorphic analytic matrix; transmitting a processing set to a server system, the processing set including at least the homomorphic analytic matrix and a keyed hashing function; and receiving a homomorphic encrypted result from the server system, the server system having utilized the homomorphic encryption scheme and the keyed hashing function to evaluate the homomorphic analytic matrix over a datasource.

Secure analytics using an encrypted analytics matrix

Systems and methods for end-to-end encryption and dynamic resizing and encoding into grouped byte channels are described herein. A query is homomorphically encrypted at a client using dynamic channel techniques. The encrypted query is sent without a private key to a server for evaluation over target data to generate encrypted response without decrypting the encrypted query. The result elements of the encrypted response are grouped, co-located, and dynamically resized and encoded into grouped byte channels using the dynamic channel techniques, without decrypting the encrypted query or the encrypted response. The encrypted response is sent to the client where the client uses the private key and channel extraction techniques associated with the dynamic channel techniques to decrypt and perform channel extraction on the encrypted response to obtain the results of the query without revealing the query or results to a target data owner, an observer, or an attacker.

Dynamic channels in secure queries and analytics

Systems and methods that provide secure analytics using homomorphic and injective format-preserving encryption and an encrypted analytics matrix are disclosed herein. An example method includes encoding an analytic parameter set using a homomorphic encryption scheme as a homomorphic analytic matrix; transmitting a processing set to a server system, the processing set including at least the homomorphic analytic matrix and a keyed hashing function; and receiving a homomorphic encrypted result from the server system, the server system having utilized the homomorphic encryption scheme, the keyed hashing function, and a format preserving encryption scheme to evaluate the homomorphic analytic matrix over a datasource.

Secure analytics using homomorphic and injective format-preserving encryption and an encrypted analytics matrix

A hardware implementations of Montgomery modular multiplication are described. The number of components as well as the number of cycles may be reduced by using a lookup table and multiplexer for selecting terms to be added during calculations. Also a loop unrolling technique may be used improve performance. A chain of pipeline adder modules and a chain of delay and shift modules may be used to pipeline calculations of multiple sets of operands.

Reduced and pipelined hardware architecture for Montgomery Modular Multiplication

Methods and systems for performing a computational operation on a server host are provided. Exemplary methods include: receiving an encrypted service request from a client host, the client host encrypting a service request to produce the encrypted service request using a shared secret, the service request specifying the computational operation; decrypting, in a secure enclave, the encrypted service request using the shared secret to produce a decrypted service request, the secure enclave preventing other software running on the server host from accessing the shared secret and other data stored in a memory space; performing the computational operation, in the secure enclave, using the decrypted service request to generate a service result; encrypting, in the secure enclave, the service result using the shared secret to create an encrypted service result; and providing the encrypted service result to the client host, the client host decrypting the encrypted service result.

Computational operations in enclave computing environments

Systems and methods for an end-to-end secure operation from an expression in natural language. Exemplary methods include: receiving a set of queries from a natural language processor, the set of queries being produced by a method including: getting data schemas associated with a target data source; obtaining the expression in natural language; performing natural language processing on the expression to determine a desired operation; and generating the set of queries using at least one of matching and inference techniques over the desired operation with respect to the data schemas; encrypting the set of queries using a homomorphic encryption technique; providing the encrypted set of queries to a server, the server including the target data source; acquiring encrypted results, the encrypted results being responsive to the encrypted set of queries; and decrypting the encrypted results using a decryption key to produce desired results.

End-To-End Secure Operations from a Natural Language Expression

An example method for performing a secure probabilistic analytic includes acquiring, by a client, an analytic, at least one analytic parameter associated with the analytic, and an encryption scheme. The encryption scheme can include a public key for encryption and a private key for decryption. The method further includes generating, using the encryption scheme, at least one analytical vector based on the analytic and analytic parameter, and sending the analytical vector and the encryption scheme to at least one server. The method includes generating, by the server based on the encryption scheme, a set of terms from a data set, evaluating the analytical vector over the set of terms to obtain an encrypted result; estimating, by the server, a probabilistic error of the encrypted result; and sending, by the server, the encrypted result and the probabilistic error to the client where the encrypted result is decrypted.

Secure probabilistic analytics using homomorphic encryption

Systems and methods for an end-to-end secure operation using a query matrix Q_M having dimensions d×s. Exemplary methods include: extracting a set of term components {T} of the operation using a term generation function; partitioning a range of a keyed hash function H(T) into a set of vectors {c_T}; setting Q_M (j,m)=E(B_j,m) when c_T[j]=m for j=0, . . . , (d−1) and for m=0, . . . , (s−1), E(B_j,m) being a non-zero bitmask corresponding to element T from the set of term components {T} encrypted using a homomorphic encryption scheme E; and setting Q_M (j,m)=E(0) when c_T[j]≠m for j=0, . . . , (d−1) and for m=0, . . . , (s−1), E(0) being a zero bitmask encrypted using the homomorphic encryption scheme E.

End-To-End Secure Operations Using a Query Matrix

Provided are methods and systems for performing a secure probabilistic analytic using an encrypted analytics matrix. An example method includes acquiring, by a client, an analytic, analytic parameters associated with the analytic, and a homomorphic encryption scheme including a public key for encryption and a private key for decryption. The method further includes generating, using the encryption scheme, an analytic matrix based on the analytic and analytic parameters, and sending the analytic matrix and the encryption scheme to at least one server. The method includes generating, by the server and based on the encryption scheme, set of terms from a data set, evaluating the analytic matrix over the set of terms to obtain an encrypted result, and estimating a probabilistic error of the encrypted result. The method further includes sending, by the server, the encrypted result and the probabilistic error to the client where the encrypted result is decrypted.

Secure probabilistic analytics using an encrypted analytics matrix

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