| Publisher | University of New Brunswick | ||
|---|---|---|---|
| Format | 348.6KB PDF | Date added | 01 Jul 2007 |
| Topics | Network Security, Security Tools, Intrusion Detection Systems | ||
| Downloads | 20 | ||
One of the most important phases of the IDS/IPS implementation identifies the set of features that the system is going to use. This paper presents a feature classification schema for network intrusion detection intended to provide a better understanding regarding the features that can be extracted from network packets. Furthermore, it presents the design of a feature extractor that extracts and statistically analyzes features with respect to attacks. The experimental results, conducted on DARPA dataset, are intended to statistically highlight the importance of each proposed feature category, as well as to identify some of the most sensitive features to attacks.
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