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Achieving Privacy-Preserving Group Recommendation with Local Differential Privacy and Random Transmission
Joint Authors
Li, Fenghua
Yin, Lihua
He, Kun
Wang, Hanyi
Niu, Ben
Source
Wireless Communications and Mobile Computing
Issue
Vol. 2020, Issue 2020 (31 Dec. 2020), pp.1-10, 10 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2020-09-05
Country of Publication
Egypt
No. of Pages
10
Main Subjects
Information Technology and Computer Science
Abstract EN
Group activities on social networks are increasing rapidly with the development of mobile devices and IoT terminals, creating a huge demand for group recommendation.
However, group recommender systems are facing an important problem of privacy leakage on user’s historical data and preference.
Existing solutions always pay attention to protect the historical data but ignore the privacy of preference.
In this paper, we design a privacy-preserving group recommendation scheme, consisting of a personalized recommendation algorithm and a preference aggregation algorithm.
With the carefully introduced local differential privacy (LDP), our personalized recommendation algorithm can protect user’s historical data in each specific group.
We also propose an Intra-group transfer Privacy-preserving Preference Aggregation algorithm (IntPPA).
IntPPA protects each group member’s personal preference against either the untrusted servers or other users.
It could also defend long-term observation attack.
We also conduct several experiments to measure the privacy-preserving effect and usability of our scheme with some closely related schemes.
Experimental results on two datasets show the utility and privacy of our scheme and further illustrate its advantages.
American Psychological Association (APA)
Wang, Hanyi& He, Kun& Niu, Ben& Yin, Lihua& Li, Fenghua. 2020. Achieving Privacy-Preserving Group Recommendation with Local Differential Privacy and Random Transmission. Wireless Communications and Mobile Computing،Vol. 2020, no. 2020, pp.1-10.
https://search.emarefa.net/detail/BIM-1214659
Modern Language Association (MLA)
Wang, Hanyi…[et al.]. Achieving Privacy-Preserving Group Recommendation with Local Differential Privacy and Random Transmission. Wireless Communications and Mobile Computing No. 2020 (2020), pp.1-10.
https://search.emarefa.net/detail/BIM-1214659
American Medical Association (AMA)
Wang, Hanyi& He, Kun& Niu, Ben& Yin, Lihua& Li, Fenghua. Achieving Privacy-Preserving Group Recommendation with Local Differential Privacy and Random Transmission. Wireless Communications and Mobile Computing. 2020. Vol. 2020, no. 2020, pp.1-10.
https://search.emarefa.net/detail/BIM-1214659
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-1214659