The method for approximate continuous Skyline query based on privacy protection in road network

Abstract Existing road network continuous Skyline queries often neglect user location privacy and data privacy protection. This paper proposes a method for Approximate Continuous Skyline Query with Privacy Protection in road network (ACPP) environments to address these issues. ACPP efficiently generates a privacy-preserving approximate continuous Skyline query result set, ensuring the protection of both user location privacy and data privacy. Firstly, ACPP introduces the construction of a Public Secure Approximate Area as an anonymous query area for query points, thereby safeguarding their location privacy. Based on the Public Secure Approximate Area, a Public Secure Approximate Dominance method is proposed. The method leverages a novel PWDG-Tree indexing structure. It also uses an associated filtering algorithm. These tools help to swiftly process continuous queries. The method minimizes redundant computations. It rapidly yields the approximate continuous Skyline query results. To address the issue of user privacy leakage in continuous queries, ACPP introduces a differential privacy-based continuous protection method, further enhancing data privacy protection. Theoretical analysis and experimental results indicate that ACPP is both efficient and practical, offering significant improvements in privacy protection for continuous Skyline queries in road network environments. By addressing the dual issues of location and data privacy, ACPP provides a viable solution for privacy-preserving continuous skyline queries to aid further research efforts.

Abstract licence: CC BY-NC-ND

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