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Outsourcing of scientific computations is attracting increasing attention since it enables the customers with limited computing resource and storage devices to outsource the sophisticated computation workloads into powerful service providers. However, it also comes up with some security and privacy concerns and challenges, such as the input and output privacy of the customers, and cheating behaviors of the cloud. Motivated by these issues, this paper focused on privacy-preserving Linear Fractional Programming (LFP) as a typical and practically relevant case for verifiable secure multiparty computation. We will investigate the secure and verifiable schema with correctness guarantees, by using normal multiparty techniques to compute the result of a computation and then using verifiable techniques only to verify that this result was correct.