E-Mail Worm Detection Using Data Mining

Keyphrases

• Worm 100%
• Worm Detection 100%
• Dimensionality Reduction 66%
• Phase Selection 66%
• Data Mining Techniques 33%
• Support Vector Machine 33%
• Principal Coordinate Analysis (PCoA) 33%
• Published Results 33%
• Redundancy 33%
• Classification Methods 33%
• Learning Classifiers 33%
• Classification Model 33%
• Novel Combinations 33%
• Selection Algorithm 33%
• Decision Tree 33%
• Support Vector Machine Classification 33%
• Presence-absence 33%
• Feature Selection 33%
• Noise Reduction 33%
• Number of Words 33%
• Number of Features 33%
• Feature Selection Methods 33%
• Efficient Classification 33%
• Body-subject 33%
• Feature Dimension 33%
• Greedy Selection 33%
• Tree Selection 33%
• Attachment Style 33%
• Reduced Data 33%
• Nave Bayes 33%

Computer Science

• Data Mining 100%
• Support Vector Machine 100%
• Feature Selection 100%
• Selection Phase 100%
• Data Mining Technique 50%
• Classification Technique 50%
• Classification Models 50%
• Algorithm Selection 50%
• Component Analysis 50%
• Principal Components 50%
• Decision Trees 50%
• Attachment Type 50%
• Feature Dimension 50%
• Nave Bayes 50%