PPMR: A privacy-preserving online medical service recommendation scheme in eHealthcare system

With the continuous development of eHealthcare systems, medical service recommendation has received great attention. However, although it can recommend doctors to users, there are still challenges in ensuring the accuracy and privacy of recommendation. In this paper, to ensure the accuracy of the recommendation, we consider doctors' reputation scores and similarities between users' demands and doctors' information as the basis of the medical service recommendation. The doctors' reputation scores are measured by multiple feedbacks from users. We propose two concrete algorithms to compute the similarity and the reputation scores in a privacy-preserving way based on the modified Paillier cryptosystem, truth discovery technology, and the Dirichlet distribution. Detailed security analysis is given to show its security prosperities. In addition, extensive experiments demonstrate the efficiency in terms of computational time for truth discovery and recommendation process.