Intrusion Detection with Machine Learning Techniques: Comparative Analysis

Cilt: 26 Sayı: 3 16 Mart 2015
  • Çetin Kaya
  • Oktay Yıldız
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Intrusion Detection with Machine Learning Techniques: Comparative Analysis

Öz

The Internet is an indispensable part of our daily lives. The increasing number of web applications and the user, in terms of data security, has some risks. Intrusion detection systems, secure access to internal networks to detect attacks and unexpected due to the demands of one of the important tools for network security. In order to develop more effective intrusion detection systems a lot of investigative work. However, so many different machine learning techniques in the literature with intrusion-detection system. In this study, the intrusion detection systems are frequently used in machine learning techniques are researched, evaluated, and the resulting achievements classifiers, used by datasets. To this end between the years 2007-2013 65 article examined, the results are presented in a way that the comparative. Thus, the determination of the future machine learning techniques to gain a perspective on the work of the attack.

Anahtar Kelimeler

Kaynakça

  1. «ICT Statistics Home Page» [Çevrimiçi],
  2. http://http://www.itu.int/en/ITU
  3. D/Statistics/Documents/facts/ICTFactsFigures2013-e.pdf.
  4. erişilmiştir]. [30 04 2014 tarihinde
  5. X. Zhang, L. Jia, H. Shi, Z. Tang ve X. Wang, «The Application of Machine Learning Methods to Intrusion Detection,» 2012.
  6. J. Co, Computer Security Threat Monitoring and Surveillance, Pennsylvania: James P. Anderson Company, Fort Washington, 1980.
  7. R. Bace ve P. Mell, «NIST Special Publication on Intrusion Detection Systems,» Publications of National Institute of Standards and Technology, pp. 1-53, 2011.
  8. Y. Vural ve Ş. Sağıroğlu, «Kurumsal Bilgi Güvenliğinde Güvenlik Testleri ve Öneriler,» Gazi Üniv. Müh. Mim. Fak. Der., cilt 26, no. 1, pp. 89-103, 2011.

Ayrıntılar

Birincil Dil

İngilizce

Konular

-

Bölüm

-

Yazarlar

Çetin Kaya Bu kişi benim

Oktay Yıldız Bu kişi benim

Yayımlanma Tarihi

16 Mart 2015

Gönderilme Tarihi

12 Aralık 2014

Kabul Tarihi

-

Yayımlandığı Sayı

Yıl 2014 Cilt: 26 Sayı: 3

Kaynak Göster

APA
Kaya, Ç., & Yıldız, O. (2015). Intrusion Detection with Machine Learning Techniques: Comparative Analysis. Marmara Fen Bilimleri Dergisi, 26(3), 89-104. https://doi.org/10.7240/mufbed.24684
AMA
1.Kaya Ç, Yıldız O. Intrusion Detection with Machine Learning Techniques: Comparative Analysis. MFBD. 2015;26(3):89-104. doi:10.7240/mufbed.24684
Chicago
Kaya, Çetin, ve Oktay Yıldız. 2015. “Intrusion Detection with Machine Learning Techniques: Comparative Analysis”. Marmara Fen Bilimleri Dergisi 26 (3): 89-104. https://doi.org/10.7240/mufbed.24684.
EndNote
Kaya Ç, Yıldız O (01 Mart 2015) Intrusion Detection with Machine Learning Techniques: Comparative Analysis. Marmara Fen Bilimleri Dergisi 26 3 89–104.
IEEE
[1]Ç. Kaya ve O. Yıldız, “Intrusion Detection with Machine Learning Techniques: Comparative Analysis”, MFBD, c. 26, sy 3, ss. 89–104, Mar. 2015, doi: 10.7240/mufbed.24684.
ISNAD
Kaya, Çetin - Yıldız, Oktay. “Intrusion Detection with Machine Learning Techniques: Comparative Analysis”. Marmara Fen Bilimleri Dergisi 26/3 (01 Mart 2015): 89-104. https://doi.org/10.7240/mufbed.24684.
JAMA
1.Kaya Ç, Yıldız O. Intrusion Detection with Machine Learning Techniques: Comparative Analysis. MFBD. 2015;26:89–104.
MLA
Kaya, Çetin, ve Oktay Yıldız. “Intrusion Detection with Machine Learning Techniques: Comparative Analysis”. Marmara Fen Bilimleri Dergisi, c. 26, sy 3, Mart 2015, ss. 89-104, doi:10.7240/mufbed.24684.
Vancouver
1.Çetin Kaya, Oktay Yıldız. Intrusion Detection with Machine Learning Techniques: Comparative Analysis. MFBD. 01 Mart 2015;26(3):89-104. doi:10.7240/mufbed.24684

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