Intrusion Detection with Machine Learning Techniques: Comparative Analysis

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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.

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IDS , Machine learning , KDD Cup99

International journal of advances in engineering and pure sciences

104

International journal of advances in engineering and pure sciences