Supervised and Unsupervised Neural Networks: Experimental Study for Anomaly Detection in Electrical Consumption.
Joel GarcíaErik ZamoraHumberto SossaPublished in: MICAI (1) (2018)
Keyphrases
- experimental study
- anomaly detection
- unsupervised learning
- neural network
- unsupervised anomaly detection
- semi supervised
- supervised learning
- connectionist systems
- novelty detection
- self organizing maps
- unsupervised methods
- intrusion detection
- detecting anomalies
- anomalous behavior
- network intrusion detection
- experimental evaluation
- pattern recognition
- feature selection
- network traffic
- genetic algorithm
- network anomaly detection
- intrusion detection system
- detecting anomalous
- network security
- detect anomalies
- computer security
- fuzzy systems
- one class support vector machines
- learning algorithm
- expectation maximization
- artificial neural networks
- negative selection algorithm
- real world
- machine learning
- malware detection
- behavior analysis
- reinforcement learning
- object recognition
- active learning