Unsupervised Anomaly Detection Framework for Multimodal Data in Industrial Control Systems.

Kim Y, An G, Kim K, Ha J

DOI: 10.3390/s26123914
Published: 2026 Jun 20
Container: Sensors (Basel, Switzerland)
Publisher: Not recorded
Open access: yes

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Cite this work

BibTeX

@article{allodium:10.3390/s26123914,
  title = {Unsupervised Anomaly Detection Framework for Multimodal Data in Industrial Control Systems.},
  author = {Kim Y and An G and Kim K and Ha J},
  year = {2026},
  journal = {Sensors (Basel, Switzerland)},
  doi = {10.3390/s26123914},
  url = {https://doi.org/10.3390/s26123914}
}

RIS

TY  - JOUR
TI  - Unsupervised Anomaly Detection Framework for Multimodal Data in Industrial Control Systems.
AU  - Kim Y
AU  - An G
AU  - Kim K
AU  - Ha J
PY  - 2026
JO  - Sensors (Basel, Switzerland)
DO  - 10.3390/s26123914
UR  - https://doi.org/10.3390/s26123914
ER  -

APA

Y, K., G, A., K, K., & J, H. (2026). Unsupervised Anomaly Detection Framework for Multimodal Data in Industrial Control Systems.. Sensors (Basel, Switzerland). https://doi.org/10.3390/s26123914

Source records

pubmed · retrieved 2026-09-25T11:24:59.256Z