Intelligent Intrusion Detection System Combining Misuse Detection and Anomaly Detection Using Random Forest Algorithm
Abstract
Intelligent Intrusion Detection is a system that has the ability to provide security to data. It compares the existing attacks with the new attacks. This helps to secure data from the intruders and also monitors the intruder’s system. The IDS generates alarm when a malicious attack is detected [4]. In this research, an Intelligent Intrusion Detection System is proposed which detects attacks with high accuracy and in fast response time. The proposed system has two phases, 1) Clustering Technique which process large amounts of data efficiently to identify outliers 2) A Classification Algorithm that classifies attacks and also avoids high false positives.
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