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Authentication of Reverse k Nearest Neighbor Query

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Database Systems for Advanced Applications (DASFAA 2015)

Part of the book series: Lecture Notes in Computer Science ((LNISA,volume 9049))

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Abstract

In outsourced spatial databases, the LBS provides query services to the clients on behalf of the data owner. However, the LBS provider is not always trustworthy and it may send incomplete or incorrect query results to the clients. Therefore, ensuring spatial query integrity is critical. In this paper, we propose efficient RkNN query verification techniques which utilize the influence zone to check the integrity of query results. The methods in this work aim to verify both monochromatic and bichromatic RkNN queries results. Specifically, our methods can gain efficient performance on verifying bichromatic RkNN query results. Extensive experiments on both real and synthetic datasets demonstrate the efficiency of our proposed authenticating methods.

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Author information

Authors and Affiliations

  1. School of Computer Science and Technology, Huazhong University of Science and Technology, Wuhan, China

    Guohui Li, Changyin Luo & Jianjun Li

Authors
  1. Guohui Li
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  2. Changyin Luo
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  3. Jianjun Li
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Corresponding author

Correspondence to Changyin Luo .

Editor information

Editors and Affiliations

  1. Universität München, München, Germany

    Matthias Renz

  2. University of Southern California, Los Angeles, USA

    Cyrus Shahabi

  3. University of Queensland, Brisbane, Australia

    Xiaofang Zhou

  4. Monash University, Clayton, Australia

    Muhammad Aamir Cheema

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© 2015 Springer International Publishing Switzerland

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Li, G., Luo, C., Li, J. (2015). Authentication of Reverse k Nearest Neighbor Query. In: Renz, M., Shahabi, C., Zhou, X., Cheema, M. (eds) Database Systems for Advanced Applications. DASFAA 2015. Lecture Notes in Computer Science(), vol 9049. Springer, Cham. https://doi.org/10.1007/978-3-319-18120-2_36

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  • DOI: https://doi.org/10.1007/978-3-319-18120-2_36

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-18119-6

  • Online ISBN: 978-3-319-18120-2

  • eBook Packages: Computer ScienceComputer Science (R0)

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