On Adversarial Vulnerability of PHM algorithms: An Initial Study

@article{Yan2021OnAV,
  title={On Adversarial Vulnerability of PHM algorithms: An Initial Study},
  author={Weizhong Yan and Zhaoyuan Yang and Jianwei Qiu},
  journal={ArXiv},
  year={2021},
  volume={abs/2110.07462}
}
In almost all PHM applications, driving highest possible performance (prediction accuracy and robustness) of PHM models (fault detection, fault diagnosis and prognostics) has been the top development priority, since PHM models’ performance directly impacts how much business value the PHM models can bring. However, recent research work in other domains, e.g., computer vision (CV), has shown that machine learning (ML) models, especially deep learning models, are vulnerable to adversarial attacks… 
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