Categorical anomaly detection in heterogeneous data using minimum description length clustering.
James CheneyXavier GombauGhita BerradaSidahmed BenabderrahmanePublished in: CoRR (2020)
Keyphrases
- anomaly detection
- heterogeneous data
- minimum description length
- numerical and categorical attributes
- data integration
- information theoretic
- detecting anomalies
- network intrusion detection
- intrusion detection
- mdl principle
- data management
- data sources
- categorical data
- network traffic
- anomalous behavior
- detect anomalies
- metadata
- complex data
- databases
- intrusion detection system
- unsupervised learning
- one class support vector machines
- high dimensional data
- information sources
- data model
- network anomaly detection
- nearest neighbor
- normal behavior
- knowledge discovery
- clustering algorithm