Biblio

Most of the existing calculation method of expert evaluation ability directly call data onto calculation, which leads to the risk of privacy leakage of expert review information and affects the peer review environment. With regard to this problem, a privacy protection method of experts' evaluation ability calculation of peer review is proposed. Privacy protection and data usability are adjusted according to privacy preferences. Using Gauss distribution and combining with the distributive law of real evaluation data, the virtual projects are generated, and the project data are anonymized according to the virtual projects. Laplace distribution is used to add noise to the evaluation sub score for perturbation, and the evaluation data are obfuscation according to the perturbation sub score. Based on the protected project data and evaluation data, the expert evaluation ability is calculated, and the review privacy is protected. The experimental results show that the proposed method can effectively balance the privacy protection and the accuracy of the calculation results.