Improving anomalous rare attack detection rate for intrusion detection system using support vector machine and genetic programming

• Main Authors: Mohd Pozi, Muhammad Syafiq, Sulaiman, Md. Nasir, Mustapha, Norwati, Perumal, Thinagaran
• Format: Article
• Language: English
• Published: Springer Verlag 2016
• Online Access: http://psasir.upm.edu.my/id/eprint/54525/1/Improving%20anomalous%20rare%20attack%20detection%20rate%20for%20intrusion%20detection%20system%20using%20support%20vector%20machine%20and%20genetic%20programming.pdf; http://psasir.upm.edu.my/id/eprint/54525/; https://link.springer.com/article/10.1007/s11063-015-9457-y
• Institution: Universiti Putra Malaysia

Commonly addressed problem in intrusion detection system (IDS) research works that employed NSL-KDD dataset is to improve the rare attacks detection rate. However, some of the rare attacks are hard to be recognized by the IDS model due to their patterns are totally missing from the training set, hen...