Deep Learning Anomaly Classification Using Multi-Attention Residual Blocks for Industrial Control Systems

This paper proposes a novel method monitoring network packets to classify anomalies in industrial control systems (ICSs). The proposed method combines different mechanisms. It is flow-based as it obtains new features through aggregating packets of the same flow. It then builds a deep neural network...

Descripción completa

Detalles Bibliográficos
Autores principales: Jiang, Jehn-Ruey, Lin, Yan-Ting
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2022
Materias:
Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9737659/
https://www.ncbi.nlm.nih.gov/pubmed/36501784
http://dx.doi.org/10.3390/s22239084

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9737659/
https://www.ncbi.nlm.nih.gov/pubmed/36501784
http://dx.doi.org/10.3390/s22239084

Ejemplares similares