对 VIMT 的中毒攻击及其不利影响

Pub Date : 2023-11-13 DOI:10.1007/s10015-023-00914-7
Taichi Ikezaki, Osamu Kaneko, Kenji Sawada, Junya Fujita
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引用次数: 0

摘要

近年来,人们提出了各种方法来设计控制系统,直接利用数据而无需数学工厂模型。数据驱动控制涉及利用实际运行数据更新或重新设计控制器,从而对控制系统进行微调并实现所需的特性。然而,针对控制系统的网络攻击日益猖獗,给社会带来了巨大挑战。Russo 和 Proutiere 的一项研究(载于 2021 年美国控制会议(ACC)论文集)展示了一种针对虚拟参考反馈调整(一种数据驱动的控制方法)的中毒方法。研究表明,破坏数据驱动方法中使用的数据可能会导致闭环性能无法达到预期规格,在最坏的情况下还会破坏控制系统的稳定性。因此,研究网络攻击对数据驱动方法中使用的数据的不利影响至关重要。本研究探讨了中毒攻击对数据驱动控制方法所用数据的影响,特别强调了虚拟内部模型调整作为一种代表性的数据驱动控制方法。
本文章由计算机程序翻译,如有差异,请以英文原文为准。

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Poisoning attack on VIMT and its adverse effect

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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