Enabling Efficient and Flexible Interpretability of Data-driven Anomaly Detection in Industrial Processes with AcME-AD.
Valentina ZaccariaChiara MasieroDavid DandoloGian Antonio SustoPublished in: CoRR (2024)
Keyphrases
- anomaly detection
- data driven
- industrial processes
- intrusion detection
- anomalous behavior
- network intrusion detection
- intrusion detection system
- industrial process
- detecting anomalies
- fault detection
- network security
- quality improvement
- unsupervised anomaly detection
- detecting anomalous
- network anomaly detection
- one class support vector machines
- network traffic
- detect anomalies
- object recognition
- negative selection algorithm
- cumulative sum
- unsupervised learning
- network intrusion
- supervised learning
- hidden markov models
- pattern recognition
- connectionist systems
- genetic algorithm