Abstract
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.
Sign-in/Register to access full text options 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
