Cargando…
An improved density peaks clustering algorithm based on grid screening and mutual neighborhood degree for network anomaly detection
With the rapid development of network technologies and the increasing amount of network abnormal traffic, network anomaly detection presents challenges. Existing supervised methods cannot detect unknown attack, and unsupervised methods have low anomaly detection accuracy. Here, we propose a clusteri...
Autores principales: | Chen, Liangchen, Gao, Shu, Liu, Baoxu |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Nature Publishing Group UK
2022
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8792034/ https://www.ncbi.nlm.nih.gov/pubmed/35082307 http://dx.doi.org/10.1038/s41598-021-02038-z |
Ejemplares similares
-
Superpixel Segmentation Based on Grid Point Density Peak Clustering
por: Chen, Xianyi, et al.
Publicado: (2021) -
Quantum Density Peak Clustering Algorithm
por: Wu, Zhihao, et al.
Publicado: (2022) -
A Neighborhood Grid Clustering Algorithm for Solving Localization Problem in WSN Using Genetic Algorithm
por: Chen, Junfeng, et al.
Publicado: (2022) -
An Improved Density Peak Clustering Algorithm for Multi-Density Data
por: Yin, Lifeng, et al.
Publicado: (2022) -
An efficient density peak cluster algorithm for improving policy evaluation performance
por: Yu, Zhenhua, et al.
Publicado: (2022)