Comparing Autoencoder and Isolation Forest in Network Anomaly Detection
Anomaly detection is essential to spot cyber-attacks within networks. Unsupervised anomaly detection methods are becoming more popular due to difficult and expensive process of labeling network data as well as their superior ability to detect unknown attacks when compared with supervised or signatur...
| Main Authors: | , |
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| Format: | Article |
| Language: | English |
| Published: |
FRUCT
2023-05-01
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| Series: | Proceedings of the XXth Conference of Open Innovations Association FRUCT |
| Subjects: | |
| Online Access: | https://www.fruct.org/publications/volume-33/fruct33/files/Smo.pdf |