Adversarial Machine Learning Threats To Medical Device AI Controllers

Abstract

The integration of artificial intelligence into life-critical medical device controllers—including closed-loop insulin delivery systems and cardiac monitoring devices—introduces adversarial machine learning (AML) attack surfaces that conventional cybersecurity frameworks do not adequately address. Adversarial attacks targeting these systems carry direct patient safety implications, yet no comprehensive, medical-device-specific AML threat taxonomy exists in the current literature. This paper addr

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@article{llmsec202601352,
  title = {{Adversarial Machine Learning Threats To Medical Device AI Controllers}},
  author = {Venkata Sai Abhinav Piratla -},
  year = {2026},
  month = mar,
  journal = {International Journal of Innovative Research and Creative Technology},
  doi = {10.62970/ijirct.v12.i2.2604012},
  url = {https://doi.org/10.62970/ijirct.v12.i2.2604012}
}