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Mathematical Problems in Engineering
Volume 2016 (2016), Article ID 8575187, 12 pages
Research Article

PRUB: A Privacy Protection Friend Recommendation System Based on User Behavior

University of Electronic Science and Technology of China, Chengdu 611731, China

Received 13 February 2016; Accepted 2 August 2016

Academic Editor: Salvatore Alfonzetti

Copyright © 2016 Wei Jiang et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.


The fast developing social network is a double-edged sword. It remains a serious problem to provide users with excellent mobile social network services as well as protecting privacy data. Most popular social applications utilize behavior of users to build connection with people having similar behavior, thus improving user experience. However, many users do not want to share their certain behavioral information to the recommendation system. In this paper, we aim to design a secure friend recommendation system based on the user behavior, called PRUB. The system proposed aims at achieving fine-grained recommendation to friends who share some same characteristics without exposing the actual user behavior. We utilized the anonymous data from a Chinese ISP, which records the user browsing behavior, for 3 months to test our system. The experiment result shows that our system can achieve a remarkable recommendation goal and, at the same time, protect the privacy of the user behavior information.