An ensemble approach for feature selection of Cyber Attack Dataset

Details An ensemble approach for feature selection of Cyber Attack Dataset An ensemble approach for feature selection of Cyber Attack Dataset

2009-12-05

arxiv.org/abs/0912.1014v1

International Journal of Computer Science and Information Security, IJCSIS, Vol. 6, No. 2, pp. 297-302, November 2009, USA

Computer Science

Cryptography and Security

6 pages IEEE format, International Journal of Computer Science and Information Security, IJCSIS November 2009, ISSN 1947 5500,

Scientific paper

Feature selection is an indispensable preprocessing step when mining huge datasets that can significantly improve the overall system performance. Therefore in this paper we focus on a hybrid approach of feature selection. This method falls into two phases. The filter phase select the features with highest information gain and guides the initialization of search process for wrapper phase whose output the final feature subset. The final feature subsets are passed through the Knearest neighbor classifier for classification of attacks. The effectiveness of this algorithm is demonstrated on DARPA KDDCUP99 cyber attack dataset.

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