Geohash coding location privacy protection scheme based on entropy weight TOPSIS

被引:0
|
作者
Jing, Li [1 ,2 ,3 ]
Ke, Liu [1 ,2 ,3 ]
Lei, Zhang [1 ,2 ,3 ]
Yin, Xiaoya [1 ,2 ,3 ]
Jia, Yuanyuan [1 ,2 ,3 ]
Jia, Huinan [1 ,2 ,3 ]
机构
[1] Jiamusi Univ, Coll Informat & Elect Technol, Heilongjiang 154007, Peoples R China
[2] Key Lab Autonomous Intelligence & Informat Proc, Heilongjiang 154007, Peoples R China
[3] Key Lab Satellite Nav Technol & Equipment Engn Tec, Jiamusi 154007, Heilongjiang, Peoples R China
来源
JOURNAL OF SUPERCOMPUTING | 2025年 / 81卷 / 01期
关键词
Location privacy; Geohash; k-anonymity; Entropy weight method; Multi-attribute decision-making;
D O I
10.1007/s11227-024-06511-0
中图分类号
TP3 [计算技术、计算机技术];
学科分类号
0812 ;
摘要
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.
引用
收藏
页数:30
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