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

Adel Sabry EESA; Zeynep ORMAN; Adnan Mohsin Abdulazeez BRIFCANI

Makale detayları

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

Yazarlar:

Adel Sabry EESA | Zeynep ORMAN | Adnan Mohsin Abdulazeez BRIFCANI

Yayıncı:

TUBITAK

Dergi:

Turkish Journal of Electrical Engineering and Computer Science 2015 Vol.23 Issue 2, pp.615-622

Belge Tipi:

Makale

Yayın Tarihi:

3/2015

Belge Dili:

Türkçe

Document ID (Org No.):

2000742707

Sıklık:

İki Aylık

eISSN:

1303-6203

pISSN:

1300-0632

Özet:

 

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.

 

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.

Makale detayları

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

Yazarlar: Adel Sabry EESA | Zeynep ORMAN | Adnan Mohsin Abdulazeez BRIFCANI

Yayıncı: TUBITAK

Dergi: Turkish Journal of Electrical Engineering and Computer Science 2015 Vol.23 Issue 2, pp.615-622

Belge Tipi: Makale

Yayın Tarihi: 3/2015

Belge Dili: Türkçe

Document ID (Org No.): 2000742707

Sıklık: İki Aylık

eISSN: 1303-6203

pISSN: 1300-0632

Sayı

Yazarlar:

Adel Sabry EESA | Zeynep ORMAN | Adnan Mohsin Abdulazeez BRIFCANI

Yayıncı:

TUBITAK

Dergi:

Turkish Journal of Electrical Engineering and Computer Science 2015 Vol.23 Issue 2, pp.615-622

Belge Tipi:

Makale

Yayın Tarihi:

3/2015

Belge Dili:

Türkçe

Document ID (Org No.):

2000742707

Sıklık:

İki Aylık

eISSN:

1303-6203

pISSN:

1300-0632