Comparison of Feature Reduction Techniques for the Binominal Classification of Network Traffic

• 作 者: Adel Ammar
• 机 构: CollegeofComputerandInformationSciences
• 出 处: 数据分析和信息处理(英文)
• 发表日期: 2015年2期
• 关键词: INTRUSION Detection Network Security FEATURE Selection KYOTO DATASET Neural Netw

This paper tests various scenarios of feature selection and feature reduction, with the objective of building a real-time anomaly-based intrusion detection system. These scenarios are evaluated on the realistic Kyoto 2006+ dataset. The influence of reduci