A Probabilistic Approach to Aggregating Anomalies for Unsupervised Anomaly Detection with Industrial Applications.
Tomas OlssonAnders HolstPublished in: FLAIRS Conference (2015)
Keyphrases
- industrial applications
- unsupervised anomaly detection
- anomaly detection
- semi supervised
- intrusion detection
- detecting anomalies
- anomalous behavior
- industrial systems
- probabilistic model
- generative model
- intrusion detection system
- pattern mining
- bayesian networks
- posterior probability
- unsupervised learning
- probability theory
- feature selection
- data mining
- systems engineering
- detect anomalies
- learning algorithm