AIRO: A Streaming-Based Machine Learning Framework for Threat Detection and Security in Industrial Internet of Things
AIRO proposes a streaming ML framework for real-time IIoT threat detection across edge-to-cloud architectures — relevant for manufacturers converging IT and OT monitoring.
Summary written by editorial AI · Source link below
arXiv:2610.30713v1 Announce Type: new Abstract: Modern Industrial Internet of Things (IIoT) im- plementations now connect edge gateways, cloud dashboards and business applications. This improves visibility and remote monitoring. However it simultaneously exposes industrial traffic to various cyber threats including scanning, web attacks and Structured Query Language (SQL) injection (SQLi), phishing- driven credential theft, and command-and-control (C2) activity. Although rule-based tools remain
Editorial Analysis
As European manufacturers digitise production lines under NIS2 scope, real-time ML-based anomaly detection at the edge becomes a practical necessity rather than a research curiosity.
Forward-looking interpretation drafted by editorial AI under human review — not a reproduction of the source. See methodology.
External link — opens at arXiv Crypto & Security in a new tab.
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