Protection of Location Privacy Based on Distributed Collaborative Recommendations.

In the existing centralized location services system structure, the server is easily attracted and be the communication bottleneck. It caused the disclosure of users' location. For this, we presented a new distributed collaborative recommendation strategy that is based on the distributed system...

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Main Authors: Peng Wang, Jing Yang, Jian-Pei Zhang
Format: Article
Language:English
Published: Public Library of Science (PLoS) 2016-01-01
Series:PLoS ONE
Online Access:http://europepmc.org/articles/PMC5029899?pdf=render
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spelling doaj-5cfdd254d82a431186b268853326a6eb2020-11-25T00:08:53ZengPublic Library of Science (PLoS)PLoS ONE1932-62032016-01-01119e016305310.1371/journal.pone.0163053Protection of Location Privacy Based on Distributed Collaborative Recommendations.Peng WangJing YangJian-Pei ZhangIn the existing centralized location services system structure, the server is easily attracted and be the communication bottleneck. It caused the disclosure of users' location. For this, we presented a new distributed collaborative recommendation strategy that is based on the distributed system. In this strategy, each node establishes profiles of their own location information. When requests for location services appear, the user can obtain the corresponding location services according to the recommendation of the neighboring users' location information profiles. If no suitable recommended location service results are obtained, then the user can send a service request to the server according to the construction of a k-anonymous data set with a centroid position of the neighbors. In this strategy, we designed a new model of distributed collaborative recommendation location service based on the users' location information profiles and used generalization and encryption to ensure the safety of the user's location information privacy. Finally, we used the real location data set to make theoretical and experimental analysis. And the results show that the strategy proposed in this paper is capable of reducing the frequency of access to the location server, providing better location services and protecting better the user's location privacy.http://europepmc.org/articles/PMC5029899?pdf=render
collection DOAJ
language English
format Article
sources DOAJ
author Peng Wang
Jing Yang
Jian-Pei Zhang
spellingShingle Peng Wang
Jing Yang
Jian-Pei Zhang
Protection of Location Privacy Based on Distributed Collaborative Recommendations.
PLoS ONE
author_facet Peng Wang
Jing Yang
Jian-Pei Zhang
author_sort Peng Wang
title Protection of Location Privacy Based on Distributed Collaborative Recommendations.
title_short Protection of Location Privacy Based on Distributed Collaborative Recommendations.
title_full Protection of Location Privacy Based on Distributed Collaborative Recommendations.
title_fullStr Protection of Location Privacy Based on Distributed Collaborative Recommendations.
title_full_unstemmed Protection of Location Privacy Based on Distributed Collaborative Recommendations.
title_sort protection of location privacy based on distributed collaborative recommendations.
publisher Public Library of Science (PLoS)
series PLoS ONE
issn 1932-6203
publishDate 2016-01-01
description In the existing centralized location services system structure, the server is easily attracted and be the communication bottleneck. It caused the disclosure of users' location. For this, we presented a new distributed collaborative recommendation strategy that is based on the distributed system. In this strategy, each node establishes profiles of their own location information. When requests for location services appear, the user can obtain the corresponding location services according to the recommendation of the neighboring users' location information profiles. If no suitable recommended location service results are obtained, then the user can send a service request to the server according to the construction of a k-anonymous data set with a centroid position of the neighbors. In this strategy, we designed a new model of distributed collaborative recommendation location service based on the users' location information profiles and used generalization and encryption to ensure the safety of the user's location information privacy. Finally, we used the real location data set to make theoretical and experimental analysis. And the results show that the strategy proposed in this paper is capable of reducing the frequency of access to the location server, providing better location services and protecting better the user's location privacy.
url http://europepmc.org/articles/PMC5029899?pdf=render
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AT jingyang protectionoflocationprivacybasedondistributedcollaborativerecommendations
AT jianpeizhang protectionoflocationprivacybasedondistributedcollaborativerecommendations
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