Machine-Learning Based Approaches for Anomaly Detection and Classification in Cellular Networks.
Pedro CasasPierdomenico FiadinoAlessandro D'AlconzoPublished in: TMA (2016)
Keyphrases
- anomaly detection
- machine learning
- cellular networks
- one class support vector machines
- intrusion detection
- pattern recognition
- unsupervised learning
- network anomaly detection
- anomalous behavior
- detecting anomalies
- network traffic
- decision trees
- text classification
- feature selection
- support vector machine
- network intrusion detection
- intrusion detection system
- supervised learning
- model selection
- wireless networks
- negative selection algorithm
- text mining
- data mining
- supply chain management
- mobile networks
- mobile users
- computational intelligence
- end to end
- data warehouse
- expectation maximization
- computer systems