Abstract
In order to analyze results of anomaly detection methods for Network Intrusion Detection Systems, the DARPA KDD data set have been widely analyzed but their data are outdated for most kinds of attacks. A software called Spleen designed to get data from a tested network with the same structure of DARPA data set is introduced. The application is used to complete the data set with additional features according to an attack analysis. Finally, to show advantages of an extended data set, two genetic methods in the detection of non-content based attacks are tested. © 2014 Springer Science+Business Media Dordrecht.
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CITATION STYLE
Guillén, E. P., Rodríguez Parra, J., & Paéz Mendez, R. V. (2014). Improving network intrusion detection with extended KDD features. In Lecture Notes in Electrical Engineering (Vol. 247 LNEE, pp. 431–445). Springer Verlag. https://doi.org/10.1007/978-94-007-6818-5_30
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