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AADMIP: Adversarial Attacks and Defenses Modeling in Industrial Processes

P. 8776–8779.
Pozdnyakov V., Makarov I., Aleksandr Kovalenko, Drobyshevskiy M., Lukyanov K.

The development of the smart manufacturing trend includes the integration of Artificial Intelligence technologies into industrial processes. One example of such implementation is deep learning models that diagnose the current state of a technological process. Recent studies have demonstrated that small data perturbations, named adversarial attacks, can significantly affect the correct predictions of such models. This fact is critical in industrial systems, where AI-based decisions can be made to manage physical equipment. In this work, we present a system which can help to evaluate the robustness of technological process diagnosis models to adversarial attacks, as well as consider protection options. We briefly review the system's modules and also consider some useful applications. Our demo video is available at: http://tinyurl.com/3by9zcj5

Language: English
DOI
Text on another site
Keywords: real-time systemsAdversarial machine learning

In book

Proceedings of the Thirty-Third International Joint Conference on Artificial Intelligence (IJCAI-24)
International Joint Conferences on Artificial Intelligence, 2024.
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