DT4I4-Secure: Digital Twin Framework for Industry 4.0 Systems Security

Author:

Lin Yu-Zheng1,Shao Sicong2,Rahman Md Habibor3,Shafae Mohammed3,Satam Pratik3

Affiliation:

1. University of Arizona,Department of Electrical and Computer Engineering,Tucson,AZ,USA,85721

2. University of North Dakota,School of Electrical Engineering and Computer Science,Grand Forks,ND,USA,58202

3. University of Arizona,Department of Systems and Industrial Engineering,Tucson,AZ,USA,85721

Funder

National Science Foundation

University of Arizona

Publisher

IEEE

Reference49 articles.

1. Machine Learning for Intrusion Detection: Stream Classification Guided by Clustering for Sustainable Security in IoT

2. An approach to cyber-physical vulnerability assessment for intelligent manufacturing systems

3. The digital twin paradigm for future nasa and us air force vehicles;glaessgen;53rd AIAA/ASME/ASCE/AHS/ASC Structures Structural Dynamics and Materials Conference 20th AIAA/ASME/AHS Adaptive Structures Conference 14th AIAA,2012

4. Graph-theoretic approach for manufacturing cybersecurity risk modeling and assessment;rahman;arXiv preprint arXiv 2301 07898,2023

5. Manufacturing cybersecurity threat attributes and countermeasures: Review, meta-taxonomy, and use cases of cyberattack taxonomies

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