Feature Selection Improves Tree-based Classification for Wireless Intrusion Detection.
Shilpa BhandariAvinash K. KukrejaAlina LazarAlex SimKesheng WuPublished in: SNTA@HPDC (2020)
Keyphrases
- intrusion detection
- feature selection
- anomaly detection
- intrusion detection system
- classification accuracy
- network traffic
- feature extraction
- network intrusion detection
- network security
- text classification
- machine learning
- credit card fraud detection
- feature space
- support vector
- computer security
- high detection rate
- artificial immune
- unsupervised learning
- information security
- model selection
- network intrusion
- support vector machine
- data mining
- nsl kdd
- detecting anomalous
- network intrusions
- fraud detection
- feature subset
- wireless networks
- pattern recognition
- cyber security
- supervised learning
- alert correlation
- training set
- decision trees
- dimensionality reduction
- network attacks
- databases