A decision tree trained on six autoencoder-learned features reports 99.94% accuracy and F1 on the Edge-IIoTset benchmark, with 0.185 ms per-sample inference on a Jetson Nano.
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Enhanced Intrusion Detection in IIoT Networks: A Lightweight Approach with Autoencoder-Based Feature Learning
A decision tree trained on six autoencoder-learned features reports 99.94% accuracy and F1 on the Edge-IIoTset benchmark, with 0.185 ms per-sample inference on a Jetson Nano.