RFG-HELAD: A Robust Fine-Grained Network Traffic Anomaly Detection Model Based on Heterogeneous Ensemble Learning.
Ying ZhongZhiliang WangXingang ShiJiahai YangKeqin LiPublished in: IEEE Trans. Inf. Forensics Secur. (2024)
Keyphrases
- fine grained
- anomaly detection
- network traffic
- ensemble learning
- intrusion detection
- intrusion detection system
- detecting anomalous
- network intrusion detection
- ensemble methods
- computer networks
- generalization ability
- access control
- detect anomalies
- concept drift
- network security
- traffic patterns
- unsupervised learning
- network intrusion
- information retrieval
- normal traffic
- knowledge discovery
- data streams
- pattern recognition
- feature extraction
- feature selection