A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2018; you can also visit the original URL.
The file type is application/pdf
.
Feature Optimization and Performance Improvement of a Multiclass Intrusion Detection System using PCA and ANN
2012
International Journal of Computer Applications
There are several bottle necks in the process of high speed intrusion detection, of which large dimensionality is one of the major problem. We have employed the Principal Component Analysis (PCA) algorithm to handle this problem, through which we have improved the performance of the Artificial Neural Network (ANN) classifier for intrusion detection. With the help of PCA we were able to identify the top 15 out of 41 features among the feature set of KDD cup 1999 data set, and noticed an
doi:10.5120/6321-8668
fatcat:huuqehn7x5h37b66mv7bhaibhm