RobustPdM: Designing Robust Predictive Maintenance against Adversarial Attacks. (arXiv:2301.10822v2 [cs.CR] UPDATED)

The state-of-the-art predictive maintenance (PdM) techniques have shown great
success in reducing maintenance costs and downtime of complicated machines
while increasing overall productivity through extensive utilization of
Internet-of-Things (IoT) and Deep Learning (DL). Unfortunately, IoT sensors and
DL algorithms are both prone to cyber-attacks. For instance, DL algorithms are
known for their susceptibility to adversarial examples. Such adversarial
attacks are vastly under-explored in the PdM domain. This is because the
adversarial attacks in the computer vision domain for classification tasks …

adversarial attacks algorithms art arxiv attacks costs cyber deep learning downtime instance internet iot machines maintenance predictive predictive maintenance productivity sensors state success through