Securely outsourcing of large scale linear fractional programming problem to public cloud

Cloud computing provides resource-constrained clients to outsource their large-scale mathematical computations to a public cloud economically. Cloud has huge computational power, massive storage, and software which are provided to clients on demand. Clients can use cloud for reducing their computational overhead and storage limitation. Though it is highly beneficial, privacy of client's confidential data is a huge concern in case of outsourcing. We have designed a secure, verifiable and efficient protocol for outsourcing large scale Linear Fractional Programming (LFP) problem to a less-secured cloud. Large scale numerical experiment confirms the input/output data security, result verifiability and client's efficiency.

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