A zero-trust digital twin framework for privacy-preserving multi-dataset intrusion detection in industrial IoT with lightweight blockchain auditing

Abstract Industrial IoT (IIoT) environments face growing cyber threats due to device heterogeneity and cyber-physical integration. This study proposes a Zero Trust-enhanced intrusion detection framework integrating deep learning anomaly detection, differential privacy, lightweight blockchain-inspire...

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Bibliografiske detaljer

Principais autores:	Shailendra Mishra, Tariq Saleh M. Aldafas, Naif S. Alshammari
Format:	Artigo
Sprog:	Inglês
Udgivet:	Nature Portfolio 2026-03-01
Serier:	Scientific Reports
Fag:	Industrial internet of things Intrusion detection system Zero trust architecture Differential privacy Lightweight blockchain Digital twin
Online adgang:	https://doi.org/10.1038/s41598-026-42041-w
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