Dimension Reduction in Intrusion Detection Features Using Discriminative Machine Learning Approach
نویسندگان
چکیده
With the growing need of internet in daily life and the dependence on the world wide system of computer networks, the network security is becoming a necessary requirement of our world to secure the confidential information available on the networks. Efficient intrusion detection is needed as a defence of the network system to detect the attacks over the network. Using feature selection, we reduce the dimensions of NSL-KDD data set. By feature reduction and machine learning approach, we are able to build Intrusion detection model to find attacks on system and improve the intrusion detection using the captured data.
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