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.
| 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): |  Urheberrechtlich geschützt |