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.
Authors: Kevin Wallis, Fabian Schillinger, Christoph Reich and Christian Schindelhauer
Published in: World Congress on Internet Security (WorldCIS-2020)
- Date of Conference: 8-10 December 2020
- DOI: 10.20533/WorldCIS.2020.0001
- ISBN: 978-1-913572-24-2
- Conference Location: London, UK