Abstract: A server module evaluates a circuit based on concealed inputs provided by respective participant modules, to provide a concealed output. By virtue of this approach, no party to the transaction (including the sever module) discovers any other party's non-concealed inputs. In a first implementation, the server module evaluates a garbled Boolean circuit. This implementation also uses a three-way oblivious transfer technique to provide a concealed input from one of the participant modules to the server module. In a second implementation, the server module evaluates an arithmetic circuit based on ciphertexts that have been produced using a fully homomorphic encryption technique. This implementation modifies multiplication operations that are performed in the evaluation of the arithmetic circuit by a modifier factor; this removes bounds placed on the number of the multiplication operations that can be performed.

Abstract: A server module evaluates a circuit based on concealed inputs provided by respective participant modules, to provide a concealed output. By virtue of this approach, no party to the transaction (including the sever module) discovers any other party's non-concealed inputs. In a first implementation, the server module evaluates a garbled Boolean circuit. This implementation also uses a three-way oblivious transfer technique to provide a concealed input from one of the participant modules to the serer module. In a second implementation, the server module evaluates an arithmetic circuit based on ciphertexts that have been produced using a fully homomorphic encryption technique. This implementation modifies multiplication operations that are performed in the evaluation of the arithmetic circuit by a modifier factor; this removes bounds placed on the number of the multiplication operations that can be performed.

Abstract: Counting values can be encrypted as a set of counting value cyphertexts according to a hidden vector encryption scheme using sample values of a set of samples, where each of the samples can include multiple sample values. Additionally, tokens can be generated. The tokens can be configured according to the hidden vector encryption scheme, such that each of the tokens can enable decryption of matching cyphertexts. Processing of the counting value cyphertexts and the tokens can be delegated to a map-reduce computer cluster. The cluster can run a map-reduce program to produce and return count representations. Each count representation can represent a count of a set of the counting value cyphertext(s) whose decryption was enabled by one or more of the token(s). For example, the counts may be counts that can be used in constructing a data structure such as a decision tree.

Abstract: Shares for one or more data values in a dataset can be computed using evaluation point values and sharing polynomials. Lagrangian coefficients can also be computed for the evaluation point values. The shares and the Lagrangian coefficients may be used to evaluate the polynomials on the data values. The technique can also include encrypting the Lagrangian coefficients according to an encryption scheme that provides for addition operations between encrypted values. An operation on representations of coefficients of the evaluation polynomial, representations of the shares, and the encrypted representations of the Lagrangian coefficients can be delegated to a remote computing environment. The operation can be performed at the remote computing environment, such as by performing a map-reduce operation. Results of the delegated operation can be received from the remote computing environment and processed to produce representation(s) of evaluation(s) of the polynomial on the data value(s).

Abstract: Counting values can be encrypted as a set of counting value cyphertexts according to a hidden vector encryption scheme using sample values of a set of samples, where each of the samples can include multiple sample values. Additionally, tokens can be generated. The tokens can be configured according to the hidden vector encryption scheme, such that each of the tokens can enable decryption of matching cyphertexts. Processing of the counting value cyphertexts and the tokens can be delegated to a map-reduce computer cluster. The cluster can run a map-reduce program to produce and return count representations. Each count representation can represent a count of a set of the counting value cyphertext(s) whose decryption was enabled by one or more of the token(s). For example, the counts may be counts that can be used in constructing a data structure such as a decision tree.

Abstract: A server module evaluates a circuit based on concealed inputs provided by respective participant modules, to provide a concealed output. By virtue of this approach, no party to the transaction (including the sever module) discovers any other party's non-concealed inputs. In a first implementation, the server module evaluates a garbled Boolean circuit. This implementation also uses a three-way oblivious transfer technique to provide a concealed input from one of the participant modules to the serer module. In a second implementation, the server module evaluates an arithmetic circuit based on ciphertexts that have been produced using a fully homomorphic encryption technique. This implementation modifies multiplication operations that are performed in the evaluation of the arithmetic circuit by a modifier factor; this removes bounds placed on the number of the multiplication operations that can be performed.