Design of an Evolutionary Approach for Intrusion Detection

<table class="table-group" width="800px"><tr class="fig-image" id="a"><td><img alt="962185.fig.006a" src="https://static.hindawi.com/articles/tswj/volume-2013/962185/figures/962185.fig.006a.jpg"/></td></tr><tr class="fig-caption"><td align="center"><table><tr><td><b>(a) </b> Training performance of noninferior NB based ensembles for ITFS-KDD (41 features) data subset</td></tr></table></td></tr><tr class="fig-image" id="b"><td><img alt="962185.fig.006b" src="https://static.hindawi.com/articles/tswj/volume-2013/962185/figures/962185.fig.006b.jpg"/></td></tr><tr class="fig-caption"><td align="center"><table><tr><td><b>(b) </b>Test performance of noninferior NB based ensembles for ITFS-KDD (41 features) data subset</td></tr></table></td></tr></table>

<table>Training and test performance of noninferior NB based ensembles for ITFS-KDD (41 features) data subset.</table>

The Scientific World Journal

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Figure 6

Figure 6: Design of an Evolutionary Approach for Intrusion Detection 