Privacy Protection in Mobile Recommender Systems: A Survey

Kun Xu; Zheng Yan

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

Privacy Protection in Mobile Recommender Systems: A Survey

Kun Xu, Zheng Yan

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › Scientific › peer-review

12 Citations (Scopus)

Abstract

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.

Original language	English
Title of host publication	Security, privacy, and anonymity in computation, communication, and storage
Subtitle of host publication	9th International Conference, SpaCCS 2016, Zhangjiajie, China, November 16-18, 2016, proceedings
Editors	Guojun Wang, Indrakshi Ray, Jose M. Alcaraz Calero, Sabu M. Thampi
Publisher	SPRINGER
Number of pages	14
ISBN (Electronic)	978-3-319-49148-6
ISBN (Print)	978-3-319-49147-9
DOIs	https://doi.org/10.1007/978-3-319-49148-6_26
Publication status	Published - Nov 2016
MoE publication type	A4 Article in a conference publication
Event	International Conference on Security, Privacy and Anonymity in Computation, Communication and Storage - Zhangjiajie, China Duration: 16 Nov 2016 → 18 Nov 2016 Conference number: 9

Publication series

Name	Lecture notes in computer science
Publisher	Springer
Volume	10066
ISSN (Print)	0302-9743
ISSN (Electronic)	1611-3349

Conference

Conference	International Conference on Security, Privacy and Anonymity in Computation, Communication and Storage
Abbreviated title	SpaCCS
Country/Territory	China
City	Zhangjiajie
Period	16/11/2016 → 18/11/2016

Keywords

Recommender systems
Mobile recommender systems
Privacy risks
Privacy protection
Mobile applications

Access to Document

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

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Xu, K., & Yan, Z. (2016). Privacy Protection in Mobile Recommender Systems: A Survey. In G. Wang, I. Ray, J. M. Alcaraz Calero, & S. M. Thampi (Eds.), Security, privacy, and anonymity in computation, communication, and storage: 9th International Conference, SpaCCS 2016, Zhangjiajie, China, November 16-18, 2016, proceedings (Lecture notes in computer science; Vol. 10066). SPRINGER. https://doi.org/10.1007/978-3-319-49148-6_26

Xu, Kun ; Yan, Zheng. / Privacy Protection in Mobile Recommender Systems : A Survey. Security, privacy, and anonymity in computation, communication, and storage: 9th International Conference, SpaCCS 2016, Zhangjiajie, China, November 16-18, 2016, proceedings. editor / Guojun Wang ; Indrakshi Ray ; Jose M. Alcaraz Calero ; Sabu M. Thampi. SPRINGER, 2016. (Lecture notes in computer science).

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abstract = "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.",

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author = "Kun Xu and Zheng Yan",

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editor = "Wang, {Guojun } and Ray, {Indrakshi } and {Alcaraz Calero}, {Jose M.} and Thampi, {Sabu M.}",

booktitle = "Security, privacy, and anonymity in computation, communication, and storage",

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Xu, K & Yan, Z 2016, Privacy Protection in Mobile Recommender Systems: A Survey. in G Wang, I Ray, JM Alcaraz Calero & SM Thampi (eds), Security, privacy, and anonymity in computation, communication, and storage: 9th International Conference, SpaCCS 2016, Zhangjiajie, China, November 16-18, 2016, proceedings. Lecture notes in computer science, vol. 10066, SPRINGER, International Conference on Security, Privacy and Anonymity in Computation, Communication and Storage, Zhangjiajie, China, 16/11/2016. https://doi.org/10.1007/978-3-319-49148-6_26

Privacy Protection in Mobile Recommender Systems : A Survey. / Xu, Kun; Yan, Zheng.

Security, privacy, and anonymity in computation, communication, and storage: 9th International Conference, SpaCCS 2016, Zhangjiajie, China, November 16-18, 2016, proceedings. ed. / Guojun Wang; Indrakshi Ray; Jose M. Alcaraz Calero; Sabu M. Thampi. SPRINGER, 2016. (Lecture notes in computer science; Vol. 10066).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › Scientific › peer-review

TY - GEN

T1 - Privacy Protection in Mobile Recommender Systems

T2 - International Conference on Security, Privacy and Anonymity in Computation, Communication and Storage

AU - Xu, Kun

AU - Yan, Zheng

N1 - Conference code: 9

PY - 2016/11

Y1 - 2016/11

N2 - 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.

AB - 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.

KW - Recommender systems

KW - Mobile recommender systems

KW - Privacy risks

KW - Privacy protection

KW - Mobile applications

U2 - 10.1007/978-3-319-49148-6_26

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

M3 - Conference contribution

SN - 978-3-319-49147-9

T3 - Lecture notes in computer science

BT - Security, privacy, and anonymity in computation, communication, and storage

A2 - Wang, Guojun

A2 - Ray, Indrakshi

A2 - Alcaraz Calero, Jose M.

A2 - Thampi, Sabu M.

PB - SPRINGER

Y2 - 16 November 2016 through 18 November 2016

ER -

Xu K, Yan Z. Privacy Protection in Mobile Recommender Systems: A Survey. In Wang G, Ray I, Alcaraz Calero JM, Thampi SM, editors, Security, privacy, and anonymity in computation, communication, and storage: 9th International Conference, SpaCCS 2016, Zhangjiajie, China, November 16-18, 2016, proceedings. SPRINGER. 2016. (Lecture notes in computer science). doi: 10.1007/978-3-319-49148-6_26

Privacy Protection in Mobile Recommender Systems: A Survey

Abstract

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Conference

Keywords

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