Secure and Verifiable Outsourcing of Large-Scale Nonnegative Matrix Factorization (NMF)

Nowadays, cloud computing platforms are becoming increasingly prevalent and readily available, providing alternative and economic services for resource-constrained clients to perform large-scale computations. This work addresses the problem of secure outsourcing of large-scale nonnegative matrix factorization (NMF) to a cloud in a way that the client can verify the correctness of the results with small overhead. The protection of the input matrix is achieved by a random permutation and scaling encryption mechanism. By exploiting the iterative nature of NMF computation, we propose a single-round verification strategy, which can be proved to be quite effective. Theoretical and experimental results are provided to show the superior performance of the proposed scheme.

Automated summary

This work addresses the issue of secure outsourcing large-scale nonnegative matrix factorization (NMF) to the cloud by proposing a scheme that allows clients to verify results with small overhead. The protection of input matrix is achieved through a random permutation and scaling encryption mechanism, and a single-round verification strategy is proposed based on the iterative nature of NMF computation. Theoretical and experimental results demonstrate the superior performance of the proposed scheme.