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An Approach Based on Decision Tree and Self-Organizing Map For Intrusion Detection | ||
| Iraqi Journal of Science | ||
| Article 1, Volume 58, Issue 3, 2018, Pages 1503-1515 | ||
| Authors | ||
| Sarah M. Shareef; Soukaena Hassan Hashim | ||
| Abstract | ||
| In modern years, internet and computers were used by many nations all overhead the world in different domains. So the number of Intruders is growing day-by-day posing a critical problem in recognizing among normal and abnormal manner of users in the network. Researchers have discussed the security concerns from different perspectives. Network Intrusion detection system which essentially analyzes, predicts the network traffic and the actions of users, then these behaviors will be examined either anomaly or normal manner. This paper suggested Deep analyzing system of NIDS to construct network intrusion detection system and detecting the type of intrusions in traditional network. The performance of the proposed system was evaluated by using Kdd cup 99 dataset. The experimental results displayed that the proposed module are best suited due to their high detection rate with false alarm rate. | ||
| Keywords | ||
| Network Intrusion Detection System; data mining; False Alarm; Decision Tree algorithm; Self; organizing map algorithm | ||
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