Abstract: In aspects of string matching in encrypted data, a computing device stores homomorphic encrypted data as a dataset, and implements a string matching application that receives an encrypted query string as a query of the homomorphic encrypted data. The string matching application can then apply algorithms to perform addition and multiplication operations, and determine whether there are matching strings of the encrypted query string in the dataset. The string matching application can compute, for each row of the dataset, a sum of some function of dataset bits and query bits for a row result, and multiply the row results of the computed rows to determine matching strings. Alternatively, the string matching application can compute, for each row of the dataset, a product over some function of the dataset bits and the query bits for a row result, and add the row results of the computed rows to determine matching strings.

Abstract: In aspects of string matching in encrypted data, a computing device stores homomorphic encrypted data as a dataset, and implements a string matching application that receives an encrypted query string as a query of the homomorphic encrypted data. The string matching application can then apply algorithms to perform addition and multiplication operations, and determine whether there are matching strings of the encrypted query string in the dataset. The string matching application can compute, for each row of the dataset, a sum of some function of dataset bits and query bits for a row result, and multiply the row results of the computed rows to determine matching strings. Alternatively, the string matching application can compute, for each row of the dataset, a product over some function of the dataset bits and the query bits for a row result, and add the row results of the computed rows to determine matching strings.

Abstract: Techniques and architectures may be used to provide an environment where a data owner storing private encrypted data in a cloud and a data evaluator may engage in a secure function evaluation on at least a portion of the data. Neither of these involved parties is able to learn anything beyond what the parties already know and what is revealed by the function, even if the parties are actively malicious. Such an environment may be useful for business transactions, research collaborations, or mutually beneficial computations on aggregated private data.