Privacy Protection in Mobile Recommender Systems: A Survey

被引：14

作者：

Xu, Kun ^{[1
]}

Yan, Zheng ^{[1
,2
]}

机构：

[1] Xidian Univ, State Key Lab Integrated Serv Networks, Sch Cyber Engn, Xian 710071, Peoples R China

[2] Aalto Univ, Dept Commun & Networking, Espoo 02150, Finland

来源：

SECURITY, PRIVACY, AND ANONYMITY IN COMPUTATION, COMMUNICATION, AND STORAGE | 2016年 / 10066卷

关键词：

Recommender systems; Mobile recommender systems; Privacy risks; Privacy protection; Mobile applications;

D O I：

10.1007/978-3-319-49148-6_26

中图分类号：

TP301 [理论、方法];

学科分类号：

081202 ;

摘要：

A Mobile Recommender System (MRS) is a system that provides personalized recommendations for mobile users. It solves the problem of information overload in a mobile environment with the support of a smart mobile device. MRS has three fundamental characteristics relevant to the mobile Internet: mobility, portability and wireless connectivity. MRS aims to generate accurate recommendations by utilizing detailed personal data and extracting user preferences. However, collecting and processing personal data may intrude user privacy. The privacy issues in MRS are more complex than traditional recommender system due to its specific characteristics and various personal data collection. Privacy protection in MRS is a crucial research topic, which is widely studied in the literature, but it still lacks a comprehensive survey to summarize its current status and indicate open research issues for further investigation. This paper reviews existing work in MRS in terms of privacy protection. Challenges and future research directions are discussed based on the literature survey.

引用

页码：305 / 318

页数：14

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