Detecting intrusive transactions in databases using partially-ordered sequential rule mining and fractional-distance based anomaly detection.
Indu SinghMinkush ManujaRishabh MathurMononito GoswamiPublished in: Int. J. Intell. Eng. Informatics (2020)
Keyphrases
- anomaly detection
- partially ordered
- rule mining
- databases
- detecting anomalies
- knowledge discovery
- partial order
- detecting anomalous
- detect anomalies
- database
- intrusion detection
- association rule mining
- association rules
- transaction databases
- network traffic
- anomalous behavior
- totally ordered
- intrusion detection system
- network intrusion detection
- one class support vector machines
- database systems
- misuse detection
- unsupervised learning
- network anomaly detection
- rule generation
- data mining
- negative selection algorithm
- frequent patterns
- data management
- image segmentation
- associative classification
- outlier detection