TwinGuard: A Supervised Machine Learning Framework for DoS Attack Detection in IoT-Enabled Digital Twins Using Random Forest and Feature Selection Optimization

Digital Twin (DT) technology enables real-time monitoring of Internet of Things (IoT)-integrated systems but faces severe threats from Denial-of-Service (DoS) attacks, which compromise data accuracy and operational stability. Existing security solutions struggle to adapt to these threats, creating a...

Popoln opis

Bibliografske podrobnosti

Principais autores:	Norah Alhamam, M. M. Hafizur Rahman, Ahmed Aljughaiman
Format:	Artigo
Jezik:	Inglês
Izdano:	IEEE 2025-01-01
Serija:	IEEE Access
Teme:	Digital twin IoT security DoS attack detection feature selection Industry 4.0
Online dostop:	https://ieeexplore.ieee.org/document/11226999/
Oznake:	Označite Brez oznak, prvi označite!