Author/Authors :
Jabbari، Neda نويسنده Computer Engineering department, Science and Research Branch, Islamic Azad University, West Azerbaijan, Iran , , Bagherzadeh، Jamshid نويسنده Assistant professor, Computer Science and Eng. Deptt, Urmia University, Urmia, Iran Bagherzadeh, Jamshid
Abstract :
According to the growth of the Internet technology, there is a need to develop strategies in order to maintain security of system. One of the most effective techniques is Intrusion Detection System (IDS). Clustering which is commonly used to detect possible attacks is one of the branches of unsupervised learning. Fuzzy clustering algorithms play an important role to reduce spurious alarms and Intrusion detection, which have uncertain quality. This paper Compare and Review fuzzy c-means and Gath-Geva and Gustafson-Kessel algorithms in order to Intrusion detection in system.
