A Hybrid Machine-Learning Ensemble for Anomaly Detection in Real-Time Industry 4.0 Systems.
David VelásquezEnrique PérezXabier OreguiArkaitz ArtetxeJorge MantecaJordi Escayola MansillaMauricio ToroMikel MaizaBasilio SierraPublished in: IEEE Access (2022)
Keyphrases
- anomaly detection
- machine learning
- one class support vector machines
- network anomaly detection
- intrusion detection
- network intrusion detection
- anomalous behavior
- network traffic
- network security
- intrusion prevention
- detecting anomalies
- behavior analysis
- unsupervised learning
- computer security
- detect anomalies
- intrusion detection system
- computational intelligence
- feature selection
- data assimilation
- text classification
- network intrusion
- pattern recognition
- learning algorithm
- negative selection algorithm
- neural network
- malware detection
- data mining