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Published in: Artificial Life and Robotics 1/2024

13-11-2023 | Original Article

Poisoning attack on VIMT and its adverse effect

Authors: Taichi Ikezaki, Osamu Kaneko, Kenji Sawada, Junya Fujita

Published in: Artificial Life and Robotics | Issue 1/2024

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Abstract

In recent years, various approaches have been proposed to design control systems that directly utilize data without mathematical plant models. Data-driven control involves updating or redesigning a controller using actual operating data, enabling fine-tuning control systems and achieving desired characteristics. However, the increasing prevalence of cyber-attacks targeting control systems presents significant societal challenges. A study by Russo and Proutiere (in Proceeding of American Control Conference (ACC), 2021) showed a poisoning approach targeting virtual reference feedback tuning, a data-driven control method. The study suggests that compromising the data used in the data-driven method may result in the closed-loop performance failing to achieve desired specifications and, in the worst case, destabilizing the control system. Hence, investigating the adverse effects of cyber-attacks on data employed in data-driven methods becomes crucial. This study explores the impact of a poisoning attack on the data used in the data-driven control method, specifically emphasizing virtual internal model tuning as a representative data-driven control approach.

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Footnotes
1
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Metadata
Title
Poisoning attack on VIMT and its adverse effect
Authors
Taichi Ikezaki
Osamu Kaneko
Kenji Sawada
Junya Fujita
Publication date
13-11-2023
Publisher
Springer Japan
Published in
Artificial Life and Robotics / Issue 1/2024
Print ISSN: 1433-5298
Electronic ISSN: 1614-7456
DOI
https://doi.org/10.1007/s10015-023-00914-7

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