Multi-View Cluster Structure Guided One-Class BLS-Autoencoder for Intrusion Detection
Intrusion detection systems are crucial for cybersecurity applications. Network traffic data originate from diverse terminal sources, exhibiting multi-view feature spaces, while the collection of unknown intrusion data is costly. Current one-class classification (OCC) approaches are mainly designed...
Saved in:
| Main Authors: | Qifan Yang, Yu-Ang Chen, Yifan Shi |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
MDPI AG
2025-07-01
|
| Series: | Applied Sciences |
| Subjects: | |
| Online Access: | https://www.mdpi.com/2076-3417/15/14/8094 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
-
Exploring Dynamic Hierarchical Fusion for Multi-View Clustering
by: Zhenshan Chen, et al.
Published: (2025-01-01) -
Load identification method based on one class classification combined with fuzzy broad learning
by: Wang Yi, et al.
Published: (2022-05-01) -
Tensor-Based Uncoupled and Incomplete Multi-View Clustering
by: Yapeng Liu, et al.
Published: (2025-05-01) -
A Comparative Analysis of Single and Multi-View Deep Learning for Cybersecurity Anomaly Detection
by: Min Li, et al.
Published: (2025-01-01) -
View-label driven cross-space structure alignment for incomplete multi-view partial multi-label classification
by: Shenrun Ding, et al.
Published: (2025-07-01)