Lin Zhang, Mingxuan Yuan, Yao Guo, Xiangqun Chen, Lei Chen
{"title":"Preserving Location-Related Privacy Collaboratively in Geo-social Networks","authors":"Lin Zhang, Mingxuan Yuan, Yao Guo, Xiangqun Chen, Lei Chen","doi":"10.1109/COMPSAC.2014.94","DOIUrl":null,"url":null,"abstract":"The emerging geo-social networks bring us attractive location-based services as well as serious location-related privacy threats. Location information of users in geo-social networks might be revealed by friends carelessly, or deduced by users curiously or even maliciously. In order to avoid location leakages, we propose collaborative privacy management in geo-social networks. Users specify and broadcast their preferences on location-related privacies in advance, so that potential leakages can be reported automatically when new resources arrive. If necessary, the associated spatial and/or temporal information of resources will be tweaked according to the privacy preferences of involving users, so that \"old\" leakages can be eliminated while ensuring that \"new\" ones are not introduced. We design algorithms for such tweaks and construct experiments on a simulated dataset to demonstrate their usability and applicability.","PeriodicalId":106871,"journal":{"name":"2014 IEEE 38th Annual Computer Software and Applications Conference","volume":"22 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2014-07-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2014 IEEE 38th Annual Computer Software and Applications Conference","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/COMPSAC.2014.94","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
Abstract
The emerging geo-social networks bring us attractive location-based services as well as serious location-related privacy threats. Location information of users in geo-social networks might be revealed by friends carelessly, or deduced by users curiously or even maliciously. In order to avoid location leakages, we propose collaborative privacy management in geo-social networks. Users specify and broadcast their preferences on location-related privacies in advance, so that potential leakages can be reported automatically when new resources arrive. If necessary, the associated spatial and/or temporal information of resources will be tweaked according to the privacy preferences of involving users, so that "old" leakages can be eliminated while ensuring that "new" ones are not introduced. We design algorithms for such tweaks and construct experiments on a simulated dataset to demonstrate their usability and applicability.