RcDT: Privacy Preservation Based on R-Constrained Dummy Trajectory in Mobile Social Networks
The boom of mobile devices and location-based services (LBSs) greatly enriches the mobile social network (MSN) applications, which bring convenience to our daily life and, meanwhile, raise serious privacy concerns due to the potential disclosure risk of location privacy. Besides the single-location...
Guardado en:
Autores principales: | Jinquan Zhang, Xiao Wang, Yanfeng Yuan, Lina Ni |
---|---|
Formato: | article |
Lenguaje: | EN |
Publicado: |
IEEE
2019
|
Materias: | |
Acceso en línea: | https://doaj.org/article/cfb7d0c475e14e1e92cc131bde246fc8 |
Etiquetas: |
Agregar Etiqueta
Sin Etiquetas, Sea el primero en etiquetar este registro!
|
Ejemplares similares
-
Review: Privacy-Preservation in the Context of Natural Language Processing
por: Darshini Mahendran, et al.
Publicado: (2021) -
Location privacy protection scheme for LBS users based ondifferential privacy
por: Naiwen YU, et al.
Publicado: (2021) -
Privacy-Preserving Computation for Large-Scale Security-Constrained Optimal Power Flow Problem in Smart Grid
por: Xiangyu Niu, et al.
Publicado: (2021) -
Sport Location-Based User Clustering With Privacy-Preservation in Wireless IoT-Driven Healthcare
por: Qiyun Zhang, et al.
Publicado: (2021) -
Differential Privacy for IoT-Enabled Critical Infrastructure: A Comprehensive Survey
por: Muhammad Akbar Husnoo, et al.
Publicado: (2021)