Information theoretic feature space slicing for statistical anomaly detection.
Ayesha Binte AshfaqSajjad RizviMobin JavedSyed Ali KhayamMuhammad Qasim AliEhab Al-ShaerPublished in: J. Netw. Comput. Appl. (2014)
Keyphrases
- information theoretic
- anomaly detection
- feature space
- information theory
- mutual information
- intrusion detection
- network intrusion detection
- information theoretic measures
- anomalous behavior
- network traffic
- theoretic framework
- detecting anomalies
- information bottleneck
- entropy measure
- network anomaly detection
- intrusion detection system
- jensen shannon divergence
- feature selection
- high dimensional
- low dimensional
- dimensionality reduction
- detect anomalies
- data points
- one class support vector machines
- cumulative sum
- negative selection algorithm
- kernel function
- unsupervised learning
- training set
- kl divergence
- kernel methods
- mean shift
- input data
- feature vectors
- training data
- data mining
- neural network