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Geohash coding location privacy protection scheme based on entropy weight TOPSIS

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Abstract

The traditional k-anonymity technique does not consider comprehensive factors when choosing anonymous locations, resulting in a high risk of privacy leakage in the final generated anonymous set. In order to construct a secure anonymous set, this paper proposed a Geohash coding location privacy protection scheme based on entropy weight TOPSIS (GLPPS-EWT). First, in order to reduce unnecessary time consumption caused by repeated encoding of historical locations, locations are cached into prefix tree based on Geohash codes. Second, considering attackers may have background knowledge so that locations initially filtered according to historical query probability and semantic distance. Finally, considering the semantic diversity, semantic sensitivity and anonymous area of anonymous set, the entropy weight method is used to determine the index weight and make multi-attribute decision on the candidate set. The optimal anonymous location is selected to construct secure anonymous set. The experimental results show that GLPPS-EWT has good performance and high privacy.

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Data Availability

No datasets were generated or analysed during the current study.

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Acknowledgements

This work was supported by the Basic Scientific Research Operating Expenses of Heilongjiang Provincial Universities and Colleges for Excellent Innovation Team (2022-KYYWF-0654), the National Fund cultivation project of Jiamusi University (JMSUGPZR2022-014), the Open Research Topics of Heilongjiang Province Key Laboratory of Autonomous Intelligence and Information Processing (ZZXC202302), the “Dongji” Academic Team of Jiamusi University(Team Code: DJXSTD202417), the Excellent Discipline Team Project of Jiamusi University (JDXKTDG2019008) and the Natural Science Fund of Heilongjiang Province (LH2021F054).

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Authors and Affiliations

  1. College of Information and Electronic Technology, Jiamusi University, Heilongjiang, 154007, China

    Li Jing, Liu Ke, Zhang Lei, Yin Xiaoya, Jia Yuanyuan & Jia Huinan

  2. Key Laboratory of Autonomous Intelligence and Information Processing, Heilongjiang, 154007, China

    Li Jing, Liu Ke, Zhang Lei, Yin Xiaoya, Jia Yuanyuan & Jia Huinan

  3. Key Laboratory of Satellite Navigation Technology and Equipment Engineering Technology, Jiamusi, 154007, Heilongjiang, China

    Li Jing, Liu Ke, Zhang Lei, Yin Xiaoya, Jia Yuanyuan & Jia Huinan

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  1. Li Jing
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Contributions

lijing: conceptualization, methodology; liuke: Writing-Original Draft, Software, validation; zhanglei: resources, Supervision; yinxiaoya: data Curation; jiayuanyuan: data Curation; jiahuinan: data Curation.

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Correspondence to Zhang Lei.

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Jing, L., Ke, L., Lei, Z. et al. Geohash coding location privacy protection scheme based on entropy weight TOPSIS. J Supercomput 81, 85 (2025). https://doi.org/10.1007/s11227-024-06511-0

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