Enhanced Intrusion Detection Using Feature Extraction and Adaptive Boost with SVM-RBF Kernel

Provided by: International Journal on Computer Science and Technology (IJCST)
Topic: Security
Format: PDF
The important and valuable information always attract attackers and has chances to maximum attacks over the network. With the quick increment of web innovation, the malevolent exercises on the system are likewise expanding. So the utilization of a productive technique is must to distinguish the intrusion. Security for all systems is turning into a major issue. In this paper, the authors compared the existing machine learning algorithms and proposed a new hybrid approach of classifier which is adaptive boost with SVM-RBF.

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