Location recommendation privacy protection method based on location sensitivity division

Location-based recommendation services can provide users with convenient services, but this requires monitoring and collecting a large amount of location information. In order to prevent location information from being leaked after monitoring and collection, location privacy must be effectively prot...

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Bibliographic Details
Published in:EURASIP journal on wireless communications and networking Vol. 2019; no. 1; pp. 1 - 13
Main Authors: Yin, Chunyong, Ju, Xiaokang, Yin, Zhichao, Wang, Jin
Format: Journal Article
Language:English
Published: Cham Springer International Publishing 10.12.2019
Springer Nature B.V
SpringerOpen
Subjects:
Communications Engineering
Differential privacy
Distributed Big Data Processing in SCADA Communication Networks
Engineering
Information Systems Applications (incl.Internet)
Laplace noise
Location based services
Location information
Location recommendation
Monitoring
Networks
Noise sensitivity
Privacy
Recommender systems
Sensitivity
Signal,Image and Speech Processing
Laplace noise
Differential privacy
Sensitivity
Location information
Location recommendation
ISSN:1687-1499, 1687-1472, 1687-1499
Online Access:Get full text
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Summary:Location-based recommendation services can provide users with convenient services, but this requires monitoring and collecting a large amount of location information. In order to prevent location information from being leaked after monitoring and collection, location privacy must be effectively protected. Therefore, this paper proposes a privacy protection method based on location sensitivity for location recommendation. This method uses location trajectories and check-in frequencies to set a threshold so as to classify location sensitivity levels. The corresponding privacy budget is then assigned based on the sensitivity to add Laplace noise that satisfies the differential privacy. Experimental results show that this method can effectively protect the user’s location privacy and reduce the impact of differential privacy noise on service quality.
Bibliography:ObjectType-Article-1
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content type line 14
ISSN:1687-1499
1687-1472
1687-1499
DOI:10.1186/s13638-019-1606-y