基于分布式融合的FDI攻击信号快速检测方法
作者:
作者单位:

浙江工业大学

作者简介:

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中图分类号:

TP273

基金项目:

国家自然科学基金项目(面上项目,重点项目,重大项目)


A fast detection method of FDI attack signal based on distributed fusion
Author:
Affiliation:

Zhejiang University of Technology

Fund Project:

The National Natural Science Foundation of China (General Program, Key Program, Major Research Plan)

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    摘要:

    本文研究了带宽受限下信息物理系统中虚假数据注入(False Data Injection, FDI)攻击的检测问题. 首先将执行器遭受的FDI攻击信号建模为系统的未知输入信号, 基于给定的H_infinity性能指标, 设计局部残差产生器以实时逼近攻击信号. 其次, 为提高检测系统预警速度, 在分布式融合框架下将所有经对数量化后的残差信号发送至检测中心, 在给定的H_infinity性能指标下, 设计优化目标并将分布式加权融合准则的求解问题转化为线性矩阵不等式形式下的凸优化问题. 与单个传感器情况下的检测方法相比, 基于分布式融合方法所确定的检测阈值更加精准, 从而大幅度提高对攻击信号的预警速度. 最后, 通过移动目标系统的仿真验证了所提方法的有效性.

    Abstract:

    This paper studies the alarm response of false data injection attack in cyber-physical system under limited bandwidth constraints. Firstly, the false data injected in the actuator is modeled as unknown input, and the local residual generators are designed by the given H_infinity performance index to generate the residual signals approaching the attack signal. Subsequently, in order to improve the alarm response, all the residual signals are quantized and then send to the detection center under the distributed fusion framework, the optimization objective is designed where the H_infinity performance index is pre-defined, and then the distributed fusion criterion are derived by solving a convex optimization problem in terms of LMI. Comparing with the detection method by single sensor, the detection threshold based on distributed fusion method is more accurate, thus the alarm response is more effective and the detection time is sharply reduced. Finally, an illustrative example is used to show the effectiveness of the proposed algorithm.

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历史
  • 收稿日期:2021-02-01
  • 最后修改日期:2021-08-02
  • 录用日期:2021-08-09
  • 在线发布日期: 2021-09-17
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