Efficiently Verifiable Computation on Encrypted Data
Dario Fiore, Rosario Gennaro, Valerio Pastro · 2014
We study the task of verifiable delegation of computation on encrypted data. We improve previous definitions in order to tolerate adversaries that learn whether or not clients accept the result of a delegated computation. In this strong model, we construct a scheme for arbitrary computations and highly efficient schemes for delegation of various classes of functions, such as linear combinations, high-degree univariate polynomials, and multivariate quadratic polynomials. Notably, the latter class includes many useful statistics. Using our solution, a client can store a large encrypted dataset on a server, query statistics over this data, and receive encrypted results that can be efficiently verified and decrypted.