Abstract
Understanding of the intersection of cyber vulnerabilities and bioprocess regulation is critical with the rise of artificial intelligence and machine learning in manufacturing. We detail a case study in which we model cyberattacks on network-mediated signals from a novel bioreactor, where it is important to control medium feed rates to maintain cell proliferation. We use a digital twin counterpart reactor to compare glucose and oxygen sensor signals from the bioreactor to predictions from a kinetic growth model, allowing discernment of faulty sensors from hacked signals. Our results demonstrate a successful biomanufacturing cyberattack detection system based on fundamental process control principles.
Recommended Citation
Fraser-Hevlin, Brenden; Schuler, Alec W.; Gozen, B. Arda; and Van Wie, Bernard J.
(2024)
"Using Digital Twins to Protect Biomanufacturing from Cyberattacks,"
Military Cyber Affairs: Vol. 7
:
Iss.
1
, Article 7.
Available at:
https://digitalcommons.usf.edu/mca/vol7/iss1/7
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