Open access
Oct 2026
The Aggregate–Worst-Class Trade-Off in Feature Selection for IoT Intrusion Detection: A Multi-Objective Study on TON_IoT
Machine-learning intrusion detection on multi-attack Internet-of-Things (IoT) datasets is often reported through aggregate metrics that can hide near-failure on rare attack classes, and through single hand-picked feature subsets whose stability is seldom examined. Using the real TON_IoT Network dataset (211,043 flows,...
Najem N. Sirhan, Sami Serhan, Tariq Khraishi
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