电子科技 ›› 2021, Vol. 34 ›› Issue (12): 75-80.doi: 10.16180/j.cnki.issn1007-7820.2021.12.013

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针对偏差攻击的安全状态估计与检测

孙杨燕,周秀莹,任祝   

  1. 浙江理工大学 信息学院,浙江 杭州 310018
  • 收稿日期:2020-08-15 出版日期:2021-12-15 发布日期:2021-12-06
  • 作者简介:孙杨燕(1996-),女,硕士研究生。研究方向:网络化控制。|周秀莹(1995-),女,硕士研究生。研究方向:网络化控制。|任祝(1983-),男,博士,讲师。研究方向:网络化控制。
  • 基金资助:
    国家自然科学基金(61403347);浙江省自然科学基金(LY17F030023)

Security State Estimation and Detection for Biasing Attack

SUN Yangyan,ZHOU Xiuying,REN Zhu   

  1. School of Information Science and Technology,Zhejiang Sci-Tech University,Hangzhou 310018,China
  • Received:2020-08-15 Online:2021-12-15 Published:2021-12-06
  • Supported by:
    National Natural Science Foundation of China(61403347);Natural Science Foundation of Zhejiang(LY17F030023)

摘要:

信息物理系统是集计算、通信和控制于一体的智能系统,可以实现网络和物理的深度协作。偏差攻击通过攻击信息物理系统中的运行数据,注入恒定虚假偏差数据,造成系统状态估计错误,影响系统正常运行。针对这一问题,文中利用基于最小迹原则的卡尔曼滤波状态估计器和t检测器相结合的攻击检测模型,对同一攻击场景下基于最优状态估计的系统量测残差进行偏差攻击的检测。对于虚假偏差数据的检测基于量测残差的观测值,根据目标观测函数的偏离来判断系统受到攻击,文中进一步提出目标观测函数的攻击检测阈值及基于假设检验的t检验方案。MATLAB仿真实例表明,该检验方案可以在短时间内发现偏差攻击的发生,检测率较传统检测方法提高2%以上,具有更强的鲁棒性。

关键词: 信息物理系统, 虚假数据注入, 偏差攻击, 卡尔曼滤波, 状态估计, t检验, 假设检验, 残差

Abstract:

Cyber-physical system is an intelligent system integrating computing, communication and control, which can realize the deep cooperation between network and physics. Biasing attack infuses constant false bias data by attacking operational data in information physical system, which leads to system state estimation error and affects the normal operation of the system. To solve this problem, the study adopts the attack detection model combining Kalman filter state estimator and t detector based on the least trace principle to detect the biasing attack of the measurement residual error of the system based on the optimal state estimation in the same attack scene. The detection of false biasing data is based on the measurement of the observed value of the residual, and the system is attacked according to the bias of the target observation function. Furthermore, the present study proposes the attack detection threshold of the target observation function and the t-test scheme based on hypothesis testing. MATLAB simulation shows that the scheme can detect the occurrence of biasing attack in a short time, and the detection rate is increased by more than 2% compared with traditional detection methods, and has stronger robustness.

Key words: cyber physical systems, false data injection, biasing attack, Kalman filtering, state estimation, t-test, hypothesis test, residual

中图分类号: 

  • TP393