针对网络物理系统的最佳严格隐身攻击设计:数据驱动的方法
IEEE transactions on cybernetics
|July 10, 2024
概括
本研究介绍了一种数据驱动的方法,用于在没有先前系统知识的情况下设计对随机系统的隐形攻击. 这种方法最大限度地降低了性能,同时避免了检测,提供了对网络物理系统漏洞的洞察.
科学领域:
- 控制系统工程 控制系统工程
- 网络安全 网络安全
- 系统理论 系统理论
背景情况:
- 网络物理系统容易受到复杂的攻击.
- 隐形攻击旨在降低系统性能,同时逃避检测.
- 现有的方法通常需要攻击者拥有完整的系统知识.
研究的目的:
- 为随机线性不变系统开发数据驱动的最佳严格隐形攻击设计.
- 在能源限制下最大限度地降低系统性能.
- 在不假定系统知识的情况下绕过基于平价空间的攻击探测器.
主要方法:
- 提出了一种新的严格隐形攻击序列 (SSAS),协调传感器和执行器信号.
- 该SSAS是从平价和马尔科夫参数推导的矩阵的零空间参数化.
- 修改的子空间识别方法用于从闭环数据中进行公正的参数估计.
主要成果:
- 提出了SSAS存在的充分和必要条件.
- 攻击设计是作为一个受约束的优化问题与一个明确的解决方案.
- 漏洞分析为检测器参数选择提供了洞察力.
结论:
- 拟议的数据驱动方法可以在没有系统知识的情况下实现最佳的隐形攻击设计.
- 该方法有效地最大限度地降低了性能退化,同时逃避检测.
- 该研究突出了网络物理系统的漏洞,并为探测器设计提供了信息.
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