Privacy and integrity preserving skyline queries in tiered sensor networks

Authors

  • Jinguo Li,

    Corresponding author
    1. College of Information Science and Engineering, Hunan University, Changsha, China
    2. Hunan Key Laboratory of Dependable System and Networks, Changsha, China
    • Correspondence: Jinguo Li, College of Information Science and Engineering, Hunan University, Changsha, China.

      E-mail: lijg@hnu.edu.cn

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  • Yaping Lin,

    1. College of Information Science and Engineering, Hunan University, Changsha, China
    2. Hunan Key Laboratory of Dependable System and Networks, Changsha, China
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  • Gang Wang,

    1. College of Information Science and Engineering, Hunan University, Changsha, China
    2. Hunan Key Laboratory of Dependable System and Networks, Changsha, China
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  • Rui Li,

    1. College of Information Science and Engineering, Hunan University, Changsha, China
    2. Hunan Key Laboratory of Dependable System and Networks, Changsha, China
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  • Bo Yin

    1. College of Information Science and Engineering, Hunan University, Changsha, China
    2. Hunan Key Laboratory of Dependable System and Networks, Changsha, China
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ABSTRACT

Storage nodes in two-tiered sensor networks are responsible for storing sensor-collected data and processing the sink-issued queries. Therefore, storage nodes are vulnerable to attack because of their importance. In this paper, we propose a privacy and integrity preserving protocol called SSQ, which is able to prevent compromised storage nodes from leaking sensitive data and allows the sink to detect the misbehaviors of compromised storage nodes. For privacy preserving, a size-limited bucketing technique is proposed to mix the data in a range, and a prefix membership verification technique based on Bloom filters is developed to perform skyline queries on encrypted data items. For integrity preserving, a Merkle hash tree-based technique is investigated to prevent compromised storage nodes from tampering and dropping data. Detailed performance evaluations confirm the high efficacy and efficiency of SSQ. Copyright © 2013 John Wiley & Sons, Ltd.

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