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• W4285327059 abstract "With the popularity and development of Location-Based Services (LBS), location privacy-preservation has become a hot research topic in recent years, especially research on k-anonymity. Although previous studies have done a lot of work on privacy protection, they ignore the negative impact on the security of the knowledge of user-related semantic information of locations that attacker has. To solve this issue, we proposed a User-related Semantic Location Privacy Protection Mechanism (USPPM) based on k-anonymity. First, the anonymity set generation method that combines user-related mobile semantic feature of locations and semantic diversity entropy is proposed to improve the location semantic privacy safety. Second, we design an anonymity set optimization method which enhances sensitive semantic location privacy, through stackberg game model between attacker and protector. Finally, compared with other solutions, experiment on the real dataset shows that our algorithms can provide location privacy efficiently." @default.
• W4285327059 created "2022-07-14" @default.
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• W4285327059 date "2021-12-01" @default.
• W4285327059 modified "2023-09-26" @default.
• W4285327059 title "A User-related Semantic Location Privacy Protection Method In Location-based Service" @default.
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• W4285327059 doi "https://doi.org/10.1109/icpads53394.2021.00092" @default.
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