Cargando…
LDPCD: A Novel Method for Locally Differentially Private Community Detection
As one of the cores of data analysis in large social networks, community detection has become a hot research topic in recent years. However, user's real social relationship may be at risk of privacy leakage and threatened by inference attacks because of the semitrusted server. As a result, comm...
Autor principal: | Zhang, Zhejian |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Hindawi
2022
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8763540/ https://www.ncbi.nlm.nih.gov/pubmed/35047034 http://dx.doi.org/10.1155/2022/4080047 |
Ejemplares similares
-
Locally Differentially Private Heterogeneous Graph Aggregation with Utility Optimization
por: Liu, Zichun, et al.
Publicado: (2023) -
Sarve: synthetic data and local differential privacy for private frequency estimation
por: Varma, Gatha, et al.
Publicado: (2022) -
Deconvoluting kernel density estimation and regression for locally differentially private data
por: Farokhi, Farhad
Publicado: (2020) -
Differentially private distributed logistic regression using private and public data
por: Ji, Zhanglong, et al.
Publicado: (2014) -
Private haplotypes can reveal local adaptation
por: Sjöstrand, Agnès E, et al.
Publicado: (2014)