A Hybrid Intrusion Detection System Based on Multilayer Artificial Neural Network and Intelligent Feature Selection

Mehdi MANSOURI; Mohadese TORABI GOLSEFID; Naser NEMATBAKHSH

Makale detayları

A Hybrid Intrusion Detection System Based on Multilayer Artificial Neural Network and Intelligent Feature Selection

Yazarlar:

Mehdi MANSOURI | Mohadese TORABI GOLSEFID | Naser NEMATBAKHSH

Yayıncı:

Sivas Cumhuriyet Üniversitesi

Dergi:

Cumhuriyet Üniversitesi Fen Edebiyat Fakültesi Fen Bilimleri Dergisi 2015 Vol.36 Issue 3, pp.2686-2692

Belge Tipi:

Makale

Yayın Tarihi:

5/2015

Belge Dili:

Türkçe

Document ID (Org No.):

2000921718

Sıklık:

Üç Aylık

eISSN:

2587-246X

pISSN:

2587-2680

Özet:

 


Abstract. Increased intrusions into computer networks and cyber-attacks have rendered the immunization of cyberspace one of the most important issues of managers and experts in the recent years. Since cyber-attacks have become more sophisticated and hackers have become more professional, mere use techniques such as firewall, cryptography, biometrics, and antiviruses is not sufficient anymore. Therefore, it is necessary to employ efficient intrusion detection systems. Considering 5 classes of cyber-attacks, a detection intrusion system, of abuse detection type, based on the combination of a multilayer artificial neural network and an intelligent feature selection method was introduced in this research. The research results indicated that the feature selection phase using the proposed method yielded more favorable outcomes than the compared method in terms of the evaluation criteria.

.

Makale detayları

A Hybrid Intrusion Detection System Based on Multilayer Artificial Neural Network and Intelligent Feature Selection

Yazarlar: Mehdi MANSOURI | Mohadese TORABI GOLSEFID | Naser NEMATBAKHSH

Yayıncı: Sivas Cumhuriyet Üniversitesi

Dergi: Cumhuriyet Üniversitesi Fen Edebiyat Fakültesi Fen Bilimleri Dergisi 2015 Vol.36 Issue 3, pp.2686-2692

Belge Tipi: Makale

Yayın Tarihi: 5/2015

Belge Dili: Türkçe

Document ID (Org No.): 2000921718

Sıklık: Üç Aylık

eISSN: 2587-246X

pISSN: 2587-2680

Sayı

Yazarlar:

Mehdi MANSOURI | Mohadese TORABI GOLSEFID | Naser NEMATBAKHSH

Yayıncı:

Sivas Cumhuriyet Üniversitesi

Dergi:

Cumhuriyet Üniversitesi Fen Edebiyat Fakültesi Fen Bilimleri Dergisi 2015 Vol.36 Issue 3, pp.2686-2692

Belge Tipi:

Makale

Yayın Tarihi:

5/2015

Belge Dili:

Türkçe

Document ID (Org No.):

2000921718

Sıklık:

Üç Aylık

eISSN:

2587-246X

pISSN:

2587-2680