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Pan Xiao, Chen Weizhang, Sun Yige, Wu Lei. Continuous Queries Privacy Protection Algorithm Based on Spatial-Temporal Similarity Over Road Networks[J]. Journal of Computer Research and Development, 2017, 54(9): 2092-2101. DOI: 10.7544/issn1000-1239.2017.20160551
Citation: Pan Xiao, Chen Weizhang, Sun Yige, Wu Lei. Continuous Queries Privacy Protection Algorithm Based on Spatial-Temporal Similarity Over Road Networks[J]. Journal of Computer Research and Development, 2017, 54(9): 2092-2101. DOI: 10.7544/issn1000-1239.2017.20160551

Continuous Queries Privacy Protection Algorithm Based on Spatial-Temporal Similarity Over Road Networks

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  • Published Date: August 31, 2017
  • Continuous queries are one of the most common queries in location-based services (LBSs), although particularly useful, such queries raise serious privacy concerns. However, most of the existing location cloaking approaches over road networks are only applicable for snapshots queries. If these algorithms are applied on continuous queries directly, due to continuous location frequently updated, continuous query privacy will be disclosed. Moreover, combined with the network topology and other network parameters (limited speed etc.), the attackers are knowledgeable, which can easily lead to precise location privacy disclosure. We observe that mobile objects have similar spatial and temporal features due to the existing of network topology. In order to resist continuous query attacks and location-dependent attacks simultaneously, we propose a continuous queries privacy protection algorithm based on spatial-temporal similarity over road networks. The algorithm adopts user grouping and K-sharing privacy requirement strategies to constitute cloaking user sets, which is used to resist continuous queries attack. Then, with the same premise of cloaking user sets, a continuous cloaking segment sets generating algorithm is proposed to resist location-dependent attacks, which makes a balance between location privacy and service quality. Finally, we conduct series of experiments to verify our algorithm with four evaluation measures, and the experimental results show the effectiveness of the proposed algorithm.
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