A new feature selection model based on ID3 and bees algorithm for intrusion detection system

Authors

ADEL SABRY EESA
ZEYNEP ORMAN
ADNAN MOHSIN ABDULAZEEZ BRIFCANI

DOI

10.3906/elk-1302-53

Abstract

Intrusion detection systems (IDSs) have become a necessary component of computers and information security framework. IDSs commonly deal with a large amount of data traffic and these data may contain redundant and unimportant features. Choosing the best quality of features that represent all of the data and exclude the redundant features is a crucial topic in IDSs. In this paper, a new combination approach based on the ID3 algorithm and the bees algorithm (BA) is proposed to select the optimal subset of features for an IDS. The BA is used to generate a subset of features, and the ID3 algorithm is used as a classifier. The proposed model is applied on KDD Cup 99 dataset. The obtained results show that the feature subset generated by the proposed ID3-BA gives a higher accuracy and detection rate with a lower false alarm rate when compared to the results obtained by using all features.

Keywords

Intrusion detection system, ID3 algorithm, bees algorithm, feature selection

First Page

615

Last Page

622

Recommended Citation

EESA, ADEL SABRY; ORMAN, ZEYNEP; and BRIFCANI, ADNAN MOHSIN ABDULAZEEZ (2015) "A new feature selection model based on ID3 and bees algorithm for intrusion detection system," Turkish Journal of Electrical Engineering and Computer Sciences: Vol. 23: No. 2, Article 21. https://doi.org/10.3906/elk-1302-53
Available at: https://journals.tubitak.gov.tr/elektrik/vol23/iss2/21