Intrusion Detection with Machine Learning Techniques: Comparative Analysis

Year 2014, Volume: 26 Issue: 3, 89 - 104, 16.03.2015

Çetin Kaya Oktay Yıldız

https://doi.org/10.7240/mufbed.24684

Cited By: 9

Abstract

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.

Keywords

IDS;Machine learning;KDD Cup99

Makine Öğrenmesi Teknikleriyle Saldırı Tespiti: Karşılaştırmalı Analiz

Abstract

İnternet, günlük hayatımızın vazgeçilmez bir parçasıdır. Artan web uygulamaları ve kullanıcı sayısı, veri güvenliği açısından bazı riskleri de beraberinde getirmiştir. Ağ güvenliği için önemli araçlardan biri olan saldırı tespit sistemleri, güvenli iç ağlara yapılan saldırıları ve beklenmeyen erişim taleplerini tespit etmede başarılı bir şekilde kullanılmaktadır. Günümüzde, pek çok araştırmacı, daha etkin saldırı tespit sistemi gerçekleştirilmesi amacıyla çalışma yapmaktadır.  Bu amaçla literatürde farklı makine öğrenme teknikleri ile gerçekleştirilmiş pek çok saldırı tespit sistemi vardır. Yapılan bu çalışmada, saldırı tespit sistemlerinde sıklıkla kullanılan makine öğrenme teknikleri araştırılmış, kullandıkları sınıflandırıcılar, veri setleri ve elde edilen başarılar değerlendirilmiştir. Bu amaçla 2007-2013 yılları arasında SCI, SCI Expanded ve EBSCO indekslerince taranan ulusal ve uluslararası dergilerde yayınlanmış 65 makale incelenmiş, sonuçlar, karşılaştırılmalı bir şekilde sunulmuştur. Böylece, gelecekte yapılacak

Keywords

STS;Makine öğrenmesi;KDD Cup99

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