Hybrid self-organizing feature map (SOM) for anomaly detection in cloud infrastructures using granular clustering based upon value-difference metrics.
Ioannis M. StephanakisIoannis P. ChochliourosEvangelos SfakianakisSyed Noorulhassan ShiraziDavid HutchisonPublished in: Inf. Sci. (2019)
Keyphrases
- anomaly detection
- self organizing maps
- unsupervised learning
- intrusion detection
- detecting anomalies
- anomalous behavior
- unsupervised anomaly detection
- network traffic
- network intrusion detection
- cloud computing
- intrusion detection system
- behavior analysis
- data management
- detecting anomalous
- computer security
- neural network
- network security
- computing infrastructure
- network anomaly detection
- negative selection algorithm
- object recognition
- detect anomalies
- similarity measure
- one class support vector machines
- learning algorithm
- connectionist systems
- high dimensional
- feature vectors
- k means
- semi supervised
- dimensionality reduction