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A New Spatial Transformation Scheme for Preventing Location Data Disclosure in Cloud Computing

    Research output: Contribution to conferenceChapterpeer-review

    Abstract

    Because much interest in spatial database for cloud computing has been attracted, studies on preserv-ing location data privacy have been actively done. However, since the existing spatial transformation schemes are weak to a proximity attack, they cannot preserve the privacy of users who enjoy location-based services in the cloud computing. Therefore, a transformation scheme is required for providing a safe service to users. We, in this chapter, propose a new transformation scheme based on a line sym-metric transformation (LST). The proposed scheme performs both LST-based data distribution and error injection transformation for preventing a proximity attack effectively. Finally, we show from our performance analysis that the proposed scheme greatly reduces the success rate of the proximity attack while performing the spatial transformation in an efficient way.

    Original languageEnglish
    Title of host publicationGeospatial Research
    Subtitle of host publicationConcepts, Methodologies, Tools, and Applications
    PublisherIGI Global
    Pages1752-1776
    Number of pages25
    Volume3
    ISBN (Electronic)9781466698468
    ISBN (Print)9781466698451
    DOIs
    StatePublished - 2016.01.1

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