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Authenticating location-based skyline queries in arbitrary subspaces

  • Xin Lin
  • , Jianliang Xu
  • , Haibo Hu
  • , Wang Chien Lee
  • Hong Kong Baptist University
  • Pennsylvania State University

科研成果: 期刊稿件文章同行评审

摘要

With the ever-increasing use of smartphones and tablet devices, location-based services (LBSs) have experienced explosive growth in the past few years. To scale up services, there has been a rising trend of outsourcing data management to Cloud service providers, which provide query services to clients on behalf of data owners. However, in this data-outsourcing model, the service provider can be untrustworthy or compromised, thereby returning incorrect or incomplete query results to clients, intentionally or not. Therefore, empowering clients to authenticate query results is imperative for outsourced databases. In this paper, we study the authentication problem for location-based arbitrary-subspace skyline queries (LASQs), which represent an important class of LBS applications. We propose a basic Merkle Skyline R-tree method and a novel Partial S4-tree method to authenticate one-shot LASQs. For the authentication of continuous LASQs, we develop a prefetching-based approach that enables clients to compute new LASQ results locally during movement, without frequently contacting the server for query re-evaluation. Experimental results demonstrate the efficiency of our proposed methods and algorithms under various system settings.

源语言英语
文章编号6574865
页(从-至)1479-1493
页数15
期刊IEEE Transactions on Knowledge and Data Engineering
26
6
DOI
出版状态已出版 - 6月 2014

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