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  • 标题:Non-deterministic K-anonymity Algorithm Based Untrusted Third Party for Location Privacy Protection in LBS
  • 本地全文:下载
  • 作者:Jinying Jia ; Fengli Zhang
  • 期刊名称:International Journal of Security and Its Applications
  • 印刷版ISSN:1738-9976
  • 出版年度:2015
  • 卷号:9
  • 期号:9
  • 页码:387-400
  • DOI:10.14257/ijsia.2015.9.9.33
  • 出版社:SERSC
  • 摘要:When people use the LBS, they will leak their location information to an untrusted LBS provider. A new technology named location privacy protection has been well studied by scholars. But in their researches, they supposed that there was a trusted third party which could provide anonymous services for the query user. However, it is very difficult to find a trusted third party in practice. In this paper, we proposed a non-deterministic k-anonymity algorithm based untrusted third party for location privacy protection in LBS. It moved the process of the generating anonymous spatial region (ASR) from the third party to the users, thereby reduced the credibility of the third party from trusted to untrusted. And introduced an incremental query for KNN. The experiments demonstrate that our proposed algorithm has better performance than existing algorithms.
  • 关键词:location based service; location privacy; spatial cloaking; k-anonymity
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