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The proposed IDS is designed to achieve optimal accuracy based on minimal information.
It only selected the discriminatory features using GA from the feature pool.
The discriminatory features plotted in 2-dimensional space
Their distribution showed how the different (normal and attack) patterns overlapped and separated each other.
We obtained best accuracies in all stages in both training and testing sets. The classification accuracies of training and testing sets were 97.0% and 93.0% using SVM (in two classes)
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IEEE/ICACT20210214 Slide.19
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