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Corrupted Nodes and their Impact on a Distributed Decision Tree

  • Machine learning applications, like machine condition monitoring, predictive maintenance, and others, become a state of the art in Industry 4.0. One of many machine learning algorithms are decision trees for the decision-making process. A new approach for creating distributed decision trees, called node based parallelization, is presented. It allows data to be classified through a network of industrial devices. Each industrial device is responsible for a single classification rule. Also, nodes that react incorrectly, for example, due to an attack, are taken into account using a variety of methods to remain the decision-making process correct and robust.

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Metadaten
Author:Kevin Wallis, Fabian Schillinger, Christoph ReichORCiDGND, Christian Schindelhauer
DOI:https://doi.org/10.20533/WorldCIS.2020.0001
ISBN:978-1-913572-24-2
Parent Title (English):World Congress on Internet Security (WorldCIS-2020), December, 8, 2020 - December, 10, 2020, online
Document Type:Conference Proceeding
Language:English
Year of Completion:2020
Release Date:2021/12/13
First Page:11
Last Page:18
Licence (German):License LogoUrheberrechtlich gesch├╝tzt