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Range Query Processing for Monitoring Applications over Untrustworthy Clouds

Abstract : Privacy is a major concern in cloud computing since clouds are considered as untrusted environments. In this study, we address the problem of privacy-preserving range query processing on clouds. Several solutions have been proposed in this line of work, however, they become inefficient or impractical for many monitoring applications, including real-time monitoring and predicting the spatial spread of seasonal epidemics (e.g., H1N1 influenza). In this case, a system often confronts a high rate of incoming data. Prior schemes may thus suffer from potential performance issues, e.g., overload or bottleneck. In this paper, we introduce an extension of PINED-RQ to address these limitations. We also demonstrate experimentally that our solution outperforms PINED-RQ.
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https://hal.archives-ouvertes.fr/hal-02285562
Contributor : Laurent d'Orazio <>
Submitted on : Thursday, September 12, 2019 - 6:29:05 PM
Last modification on : Thursday, May 14, 2020 - 1:09:05 AM
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Hoang Tran, Tristan Allard, Laurent Orazio, Amr Abbadi. Range Query Processing for Monitoring Applications over Untrustworthy Clouds. International Conference on Extending Database Technology, Mar 2019, Lisbon, Portugal. ⟨10.5441/002/edbt.2019.82⟩. ⟨hal-02285562⟩

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