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Successive Trajectory Privacy Protection with Semantics Prediction Differential Privacy [PDF]
Entropy, 2022 The publication of trajectory data provides critical information for various location-based services, and it is critical to publish trajectory data safely while ensuring its availability.
Jing Zhang +4 more
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Trajectory-Differential Privacy-Protection Method with Interest Region
Jisuanji kexue yu tansuo, 2020 Trajectory data privacy protection method is a hot topic in data privacy protection research field. Most of existing trajectory data privacy protection methods adopt the strategy of adding noise to all locations, which reduces the availability of data ...
LAN Wei, LIN Ying, BAO Lingyan, LI Tong, CHEN Mengrong, SHAN Jinzhao
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LBS user location privacy protection scheme based on trajectory similarity
Scientific Reports, 2022 During the data set input or output, or the data set itself adds noise to enable data distortion to effectively reduce the risk of user privacy leakage.
Kun Qian, Xiaohui Li
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A location semantic privacy protection model based on spatial influence [PDF]
Scientific ReportsThe utilization of numerous location-based intelligent services yields massive traffic trajectory data. Mining such data unveils internal and external user features, offering significant application value across various domains.
Linghong Kuang +4 more
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KSDP scheme for trajectory data publishing
Shenzhen Daxue xuebao. Ligong ban, 2023 For clustering applications in the field of trajectory privacy protection, the k-means algorithm is sensitive to initial values and the number of clusters may be somewhat arbitrary.
ZHANG Jun +4 more
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A trajectory data publishing algorithm satisfying local suppression
International Journal of Distributed Sensor Networks, 2021 Suppressing the trajectory data to be released can effectively reduce the risk of user privacy leakage. However, the global suppression of the data set to meet the traditional privacy model method reduces the availability of trajectory data.
Xiaohui Li +3 more
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Sensors, 2023 With the popularity of location services and the widespread use of trajectory data, trajectory privacy protection has become a popular research area. k-anonymity technology is a common method for achieving privacy-preserved trajectory publishing.
Hua Shen, Yu Wang, Mingwu Zhang
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IFTS: A Location Privacy Protection Method Based on Initial and Final Trajectory Segments
IEEE Access, 2021 Privacy protection problem is one of the most concerning issues related to Location-Based Services (LBS) in our daily life. Privacy protection of LBS often requires anonymizing customer's trajectory data.
Jiuyun Xu +5 more
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High-Confidence Computing, 2023 With the rapid development of high-speed mobile network technology and high-precision positioning technology, the trajectory information of mobile users has received extensive attention from academia and industry in the field of Location-based Social ...
Weiqi Zhang +4 more
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Privacy Protection Algorithm Based on Optimized Local Suppression for Trajectory Data Publication [PDF]
Jisuanji gongcheng, 2020 To address the problem of privacy leakage caused by trajectory sequences in trajectory data publication,this paper proposes a privacy protection algorithm,TPL-Local,based on optimized local suppression.The algorithm identifies the minimal violating ...
YU Qingying, WANG Yanfei, YE Zitong, ZHANG Shuanggui, CHEN Chuanming
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