Provenance, Not Behaviour: A Serialisation Artifact in Edge-IIoTset and a Leakage-Free Benchmark for Precision-Agriculture Intrusion Detection
Edge-IIoTset is the reference benchmark for machine-learning intrusion detection in the industrial Internet of Things, and results reported on it cluster above 99%. We show that much of that performance is not intrusion detection. The preprocessing recipe distributed with the dataset instructs researchers to one-hot encode seven categorical columns. Four of them separate attack from normal traffic with an accuracy of 1.0000 on their own, through the spelling of the placeholder written for an absent protocol field: the string "0" in the normal-traffic branch of the dataset build against "0.0" in the attack branch. The label is recoverable from a serialisation artifact encoding file provena...
| Authors | Mostafa M. Galal |
|---|---|
| Primary category | cs.CR |
| Published | 16 August 2026 |
| Last updated at source | 16 August 2026 |
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