Improved collaborative filtering recommendation algorithm based on differential privacy protection

  • Chunyong Yin
  • Lingfeng Shi
  • Ruxia Sun
  • Jin Wang


In order to receive efficient personalized recommendation, users have to provide personal information to service providers. However, in this process, personal private data are in an extremely dangerous situation. Personalized recommendation technology based on privacy protection can enable users to enjoy personalized recommendations, while private data are also protected. In this paper, an efficient privacy-preserving collaborative filtering algorithm is proposed, which is based on differential privacy protection and time factor. The proposed method used the MovieLens data set in the experiment. Experimental results showed that the proposed method can effectively protect the private data, but the accuracy of recommendation is slightly inferior than the traditional collaborative filtering algorithm.


Collaborative filtering Differential privacy DiffGen Time factor 



This work was funded by the National Natural Science Foundation of China (61772282, 61772454, 61811530332). It was also supported by the Priority Academic Program Development of Jiangsu Higher Education Institutions (PAPD), Postgraduate Research & Practice Innovation Program of Jiangsu Province (KYCX18_1032), Chongqing Research Program of Basic Research and Frontier Technology (No. cstc2015jcyjA40026, No. cstc2016jcyjA0568), Natural Science Foundation of Jiangsu Province (BK20150460) and Jiangsu Collaborative Innovation Center on Atmospheric Environment and Equipment Technology (CICAEET). It was also funded by the open research fund of Key Lab of Broadband Wireless Communication and Sensor Network Technology (Nanjing University of Posts and Telecommunications), Ministry of Education. Professor Jin Wang is the corresponding author.


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© Springer Science+Business Media, LLC, part of Springer Nature 2019

Authors and Affiliations

  1. 1.School of Computer and Software, Jiangsu Engineering Center of Network MonitoringNanjing University of Information Science and TechnologyNanjingChina
  2. 2.School of Computer and Communication EngineeringChangsha University of Science and TechnologyChangshaChina

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