Computer Science ›› 2017, Vol. 44 ›› Issue (9): 178-183.doi: 10.11896/j.issn.1002-137X.2017.09.034

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P2P-based Privacy Protection Strategy in Mobile-commerce Recommender System

WANG Li-e, XU Yuan-xin, LI Xian-xian and LIU Peng   

  • Online:2018-11-13 Published:2018-11-13

Abstract: Mobile recommender systems have recently become one of the hottest topics in the domain of recommender systems.How to provide high-precision recommendations and privacy protection has become the main challenge in the development of mobile-commerce,since mobile device is privacy and mobile network is complex.Due to its weakness of computation power and bandwidth,recommender system of mobile-commerce is not able to use these privacy-preserving techniques which are initially designed for traditional recommender systems.To address above problems,a P2P-based privacy protection approach specifically for mobile-commerce recommender system was proposed in this paper.Our approach keeps incremental data intactly for guaranteeing high-precision recommendations while preserving privacy by constructing friends’ circles and forwarding data anonymously based on the model of k-anonymity.In the end,the experiment shows that the P2P-based privacy protection approach is feasible and effective.

Key words: P2P,Mobile-commerce recommender system,Privacy protection,K-anonymity

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