  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.
