Privacy Preserving Reputation Scheme

Abstract

The privacy-preserving recommendation system enables us to evaluate the recommended value without leaking the private information of users to service providers. The large overhead in performing cryptographic operations in proportion to the number of users and the number of items is the current issue. In this article, we propose an efficient scheme by reducing the dimension user evaluation matrix in the sets of items and users.