EFFECT: An End-to-End Framework for Evaluating Strategies for Parallel AI Anomaly Detection.
Matthias StammlerJulian HöferDavid KrausPatrick SchmidtTim HotfilterTanja HarbaumJürgen BeckerPublished in: INNS DLIA@IJCNN (2023)
Keyphrases
- end to end
- anomaly detection
- intrusion detection
- detecting anomalies
- unsupervised anomaly detection
- anomalous behavior
- intrusion detection system
- one class support vector machines
- machine learning
- admission control
- connectionist systems
- negative selection algorithm
- probabilistic model
- congestion control
- application layer
- network anomaly detection
- feature space
- object recognition