EVOC: More efficient verifiable outsourced computation from any one-way trapdoor function

Abstract

Verifiable outsourced computation enables a computational resource-constrained mobile device to outsource the computation of a function F on multiple inputs x 1 , …, x n to the cloud that is generally assumed to possess abundant powers. The most existing work depends on Yao's Garbled Circuit and fully homomorphic encryptions that took considerable computational overhead on weak clients. In this paper, a more efficient verifiable outsourced computation of encrypted data EVOC supporting any functions from any one-way trapdoor function is proposed, based on our newly-devised privacy preserving data aggregation supporting both addition and multiplication operations without exploiting fully homomorphic encryption (FHE). It solves the open problem suggested by Gennaro et al. that how to devise a verifiable computation scheme that used a more efficient primitive than FHE. Finally, the formal security proof and extensive efficiency evaluations demonstrate our proposed EVOC satisfies the target security and privacy requirements and far outperforms the state-of-the-art in terms of computational and communication complexity.