Model fusion of deep neural networks for anomaly detection

Model fusion of deep neural networks for anomaly detection

Abstract Network Anomaly Detection is still an open challenging task that aims to detect anomalous network traffic for security purposes. Usually, the network traffic data are large-scale and imbalanced. Additionally, they have noisy labels. This paper addresses the previous challenges and utilizes...

Full description

Bibliographic Details
Main Authors: Nouar AlDahoul, Hezerul Abdul Karim, Abdulaziz Saleh Ba Wazir
Format: Article
Language:English
Published: SpringerOpen 2021-08-01
Series:Journal of Big Data
Subjects:
Anomaly detection
Deep neural network
Highly imbalanced data
Model fusion
Class weight optimization
Online Access:https://doi.org/10.1186/s40537-021-00496-w

Internet

https://doi.org/10.1186/s40537-021-00496-w

Similar Items