Abstract: Network security is one of the major concerns of the modern era. With the rapid development and massive usage of internet over the past decade, the vulnerabilities of network security have become an important issue. Intrusion detection system is used to identify unauthorized access and unusual attacks over the secured networks. Over the past years, many studies have been conducted on the intrusion detection system. However, in order to understand the current status of implementation of machine learning techniques for solving the intrusion detection problems this survey paper enlisted the 49 related studies in the time frame between 2009 and 2014 focusing on the architecture of the single, hybrid and ensemble classifier design. This survey paper also includes a statistical comparison of classifier algorithms, datasets being used and some other experimental setups as well as consideration of feature selection step.

Nutan Farah Haq, Abdur Rahman Onik, Md. Avishek Khan Hridoy, Musharrat Rafni, Faisal Muhammad Shah and Dewan Md. Farid, “Application of Machine Learning Approaches in Intrusion Detection System: A Survey” International Journal of Advanced Research in Artificial Intelligence(IJARAI), 4(3), 2015. http://dx.doi.org/10.14569/IJARAI.2015.040302

@article{Haq2015,
title = {Application of Machine Learning Approaches in Intrusion Detection System: A Survey},
journal = {International Journal of Advanced Research in Artificial Intelligence},
doi = {10.14569/IJARAI.2015.040302},
url = {http://dx.doi.org/10.14569/IJARAI.2015.040302},
year = {2015},
publisher = {The Science and Information Organization},
volume = {4},
number = {3},
author = {Nutan Farah Haq and Abdur Rahman Onik and Md. Avishek Khan Hridoy and Musharrat Rafni and Faisal Muhammad Shah and Dewan Md. Farid}
}