Dimension Reduction in Intrusion Detection Using Manifold Learning.
Kai-mei ZhengXu QianPei-chong WangPublished in: CIS (2) (2009)
Keyphrases
- manifold learning
- intrusion detection
- dimension reduction
- intrusion detection system
- low dimensional
- anomaly detection
- feature extraction
- high dimensional
- dimensionality reduction
- high dimensional data
- principal component analysis
- feature selection
- nonlinear dimensionality reduction
- subspace learning
- data mining
- singular value decomposition
- random projections
- diffusion maps
- cluster analysis
- unsupervised learning
- high dimensionality
- manifold learning algorithm
- head pose estimation
- feature space
- data mining techniques
- preprocessing
- linear discriminant analysis
- geodesic distance
- manifold structure
- sparse representation
- low dimensional manifolds
- semi supervised
- locally linear embedding
- preprocessing step
- principle component analysis
- manifold embedding
- generative topographic mapping