AI-Enabled Digital Twin Framework for TSCA-like Anomaly Detection in FPGA-SoC-Based Industrial Cyber-Physical Systems.

Benelhaouare AZ, En-Nouar M, Kengne E, Lakhssassi A

Open source

DOI
10.3390/s26144382
Published
2026 Jul 10
Container
Sensors (Basel, Switzerland)
Publisher
Not recorded
Open access
yes

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BibTeX

@article{allodium:10.3390/s26144382,
  title = {AI-Enabled Digital Twin Framework for TSCA-like Anomaly Detection in FPGA-SoC-Based Industrial Cyber-Physical Systems.},
  author = {Benelhaouare AZ and En-Nouar M and Kengne E and Lakhssassi A},
  year = {2026},
  journal = {Sensors (Basel, Switzerland)},
  doi = {10.3390/s26144382},
  url = {https://doi.org/10.3390/s26144382}
}

RIS

TY  - JOUR
TI  - AI-Enabled Digital Twin Framework for TSCA-like Anomaly Detection in FPGA-SoC-Based Industrial Cyber-Physical Systems.
AU  - Benelhaouare AZ
AU  - En-Nouar M
AU  - Kengne E
AU  - Lakhssassi A
PY  - 2026
JO  - Sensors (Basel, Switzerland)
DO  - 10.3390/s26144382
UR  - https://doi.org/10.3390/s26144382
ER  -

APA

AZ, B., M, E., E, K., & A, L. (2026). AI-Enabled Digital Twin Framework for TSCA-like Anomaly Detection in FPGA-SoC-Based Industrial Cyber-Physical Systems.. Sensors (Basel, Switzerland). https://doi.org/10.3390/s26144382

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