EPVM: efficient and publicly verifiable computation for matrix multiplication with privacy preservation

With the rapid development of cloud computing, clients and users with limited computing resources can outsource their computation-intensive tasks to the Cloud Service Providers (CSPs). However, as the CSPs are commercial in nature and aim to increase their profits, some security challenges are still attached to them. In this paper, we propose an efficient publicly verifiable computation scheme (EPVM) for large-scale matrix multiplication with privacy preservation. Based on the theory of discrete logarithm problem and the techniques of privacy-preserving matrix transformation, our scheme not only protects the privacy of the client’s matrices but also significantly reduces the computation overhead on the client end as well as the CSP side. Our detailed security analysis and proofs show that the proposed scheme can achieve the established security requirements. The experimental evaluation also demonstrates that the proposed scheme works efficiently as compared to other existing solutions.