<p>The dummy-based method is widely used to protect the user’s location privacy in location-based services (LBS) due to its ability to obtain precise query results without the need for a third party. However, if a user continuously enjoys LBSs and directly adopts existing dummy-based privacy protection schemes, the location service provider (LSP) may identify some of the dummies in the submitted location sets. In an extreme case, the LSP could even infer the user’s real locations. This vulnerability arises because the user’s real locations in subsequent queries are difficult to predict accurately, and previously submitted location sets cannot be modified. Therefore, as the number of consecutive queries increases, it becomes increasingly challenging to generate a sufficient number of dummies to effectively protect the user’s real locations. To address this problem, this paper proposes a strategy that randomly generates some fake queries containing only dummies between neighboring queries. By submitting the dummies through these fake queries, the correlation between real locations in neighboring queries is disrupted, thereby preventing the LSP from distinguishing the dummies. The security analysis and extensive experiments show that the proposed scheme achieves effective and efficient protection of the user’s location privacy in continuous LBSs. It also demonstrates strong resistance against path correlation and reachability attacks.</p>

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Location privacy protection in continuous LBSs: enhancing anonymity via fake queries

  • Hai Liu,
  • Shengqing Hu,
  • NaNa Zhou

摘要

The dummy-based method is widely used to protect the user’s location privacy in location-based services (LBS) due to its ability to obtain precise query results without the need for a third party. However, if a user continuously enjoys LBSs and directly adopts existing dummy-based privacy protection schemes, the location service provider (LSP) may identify some of the dummies in the submitted location sets. In an extreme case, the LSP could even infer the user’s real locations. This vulnerability arises because the user’s real locations in subsequent queries are difficult to predict accurately, and previously submitted location sets cannot be modified. Therefore, as the number of consecutive queries increases, it becomes increasingly challenging to generate a sufficient number of dummies to effectively protect the user’s real locations. To address this problem, this paper proposes a strategy that randomly generates some fake queries containing only dummies between neighboring queries. By submitting the dummies through these fake queries, the correlation between real locations in neighboring queries is disrupted, thereby preventing the LSP from distinguishing the dummies. The security analysis and extensive experiments show that the proposed scheme achieves effective and efficient protection of the user’s location privacy in continuous LBSs. It also demonstrates strong resistance against path correlation and reachability attacks.