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Found 4 papers, 3 papers with code
RobustPdM: Designing Robust Predictive Maintenance against Adversarial Attacks
We observe that approximate adversarial training can significantly improve the robustness of PdM models (up to 54X) and outperforms the state-of-the-art PdM defense methods by offering 3X more robustness.
Adversarial Examples in Deep Learning for Multivariate Time Series Regression
Due to the tremendous success of deep learning (DL) algorithms in various domains including image recognition and computer vision, researchers started adopting these techniques for solving MTS data mining problems, many of which are targeted for safety-critical and cost-critical applications.
Crafting Adversarial Examples for Deep Learning Based Prognostics (Extended Version)
The obtained results show that all the evaluated PHM models are vulnerable to adversarial attacks and can cause a serious defect in the remaining useful life estimation.
False Data Injection Attacks in Internet of Things and Deep Learning enabled Predictive Analytics
In this paper, we demonstrate the effect of IoT sensor attacks on a PdM system.
