Dimension Reduction Technique Based on Supervised Autoencoder for Intrusion Detection of Industrial Control Systems

<table class="table-group" id="tab3"><tr><td><table class="table"><tr><td class="thead-hr" colspan="2"><hr/></td></tr><tr class="thead"><td class="align_left">Hyperparameter</td><td class="align_center">Value</td></tr><tr><td class="thead-hr" colspan="2"><hr/></td></tr><tr><td class="align_left">Hidden layers</td><td class="align_center">96-64-96</td></tr><tr><td class="align_left">Learning rate</td><td class="align_center">0.001</td></tr><tr><td class="align_left">Batch size</td><td class="align_center">32</td></tr><tr><td class="align_left">Epochs</td><td class="align_center">400</td></tr><tr><td class="align_left">Weight of classification error</td><td class="align_center">1.0</td></tr><tr class="table-tr"><td colspan="2"><hr class="tbody-hr"/></td></tr></table></td></tr></table>

<div>Hyperparameters of SupervisedAE.</div>

Security and Communication Networks

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Table 3

Table 3: Dimension Reduction Technique Based on Supervised Autoencoder for Intrusion Detection of Industrial Control Systems 