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“…There have also been other efforts to model user-specific privacy requirements [29]- [32]. [29]- [31]. For instance, [29] provides partitioning mechanism to group users with personalized privacy requirements into different ǫ partitions under a non-federated setting.…”
Section: Related Workmentioning
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“…There have also been other efforts to model user-specific privacy requirements [29]- [32]. [29]- [31]. For instance, [29] provides partitioning mechanism to group users with personalized privacy requirements into different ǫ partitions under a non-federated setting.…”
Section: Related Workmentioning
“…Yapılan testler sonucunda, önerilen modelin literatürdeki dört farklı modelden daha yüksek veri faydası sunduğu bildirilmiştir. Tian ve arkadaşları [20], mahremiyet duyarlı yörünge verisi yayınlamada kişiselleştirilmiş diferansiyel mahremiyet yaklaşımını uygulayan yeni bir model önermiştir. Yörünge verisinin karakteristiğini çıkarmak amacıyla Hilbert eğrisinin kullanıldığı çalışmada, önerilen modeli test etmek amacıyla Microsoft'un yayınladığı T-Drive veri kümesinden faydalanılmıştır.…”
Section: Li̇teratür Taramasi (Literature Review)unclassified
“…By dividing different time intervals and setting different privacy protection parameters for different trajectories, the anonymous trajectory equivalence class is constructed. In [34], the Hilbert curve was used to extract the distribution characteristics of trajectory data each time, and the personalized differential privacy publishing mechanism was designed according to the individual needs for different degrees of privacy. In [35], a collaborative trajectory privacy protection scheme for continuous query was proposed to confuse attackers by issuing false query, thus confusing users' actual trajectory.…”
Section: Related Workmentioning