Intrusion detection system: overview

• Main Authors: Alanazi, H., Noor, R.M., Zaidan, B.B., Zaidan, A.A.
• Format: Article
• Language: English
• Published: 2010
• Subjects: T Technology (General)
• Online Access: http://eprints.um.edu.my/4772/1/intrusion_detection_system_overview.pdf; http://eprints.um.edu.my/4772/; http://arxiv.org/abs/1002.4047

Network Intrusion Detection (NID) is the process of identifying network activity that can lead to the compromise of a security policy. In this paper, we will look at four intrusion detection approaches, which include ANN or Artificial Neural Network, SOM, Fuzzy Logic and SVM. ANN is one of the oldest systems that have been used for Intrusion Detection System (IDS), which presents supervised learning methods. However, in this research, we also came across SOM or Self Organizing Map, which is an ANN-based system, but applies unsupervised methods. Another approach is Fuzzy Logic (IDS-based), which also applies unsupervised learning methods. Lastly, we will look at the SVM system or Support Vector Machine for IDS. The goal of this paper is to draw an image for hybrid approaches using these supervised and unsupervised methods