基于LSSVM的核电厂稳压器压力控制系统隐蔽攻击方法研究

隐蔽攻击对大型核电厂稳压器压力控制系统的安全、稳定、高效运行构成了严重威胁，实现隐蔽攻击的关键是建立高精度的对象估计模型。本文提出了一种基于最小二乘支持向量机（LSSVM）的隐蔽攻击方法，通过LSSVM算法进行系统辨识，获得稳压器受攻击区域高精度的估计模型，随后利用该估计模型结合隐蔽控制器实施攻击，实现稳压器压力控制系统在无噪声、有噪声及包含非线性环节情况下的隐蔽攻击。仿真结果表明，该攻击方式对稳压器压力控制系统造成一定破坏的同时具有高度的隐蔽性。 

LSSVM Based Covert Attack Method Research on Pressure Control System of Pressurizer in Nuclear Power Plant

Covert attacks pose a serious threat to the safe, stable and efficient operation of the control system of pressurizer in a large nuclear power plant. The key to realize covert attack is to establish a high-precision object estimation model. This paper proposes a covert attack method based on least square support vector machine (LSSVM). The system identification is carried out by LSSVM algorithm, and the high-precision estimation model of the attacked area of the pressurizer is obtained. Then the estimation model is combined with the hidden controller to realize the covert attack of the pressurizer pressure control system in the case of no noise, noise and with nonlinear links. The simulation results show that the attack mode not only causes some damage to the pressure control system of the pressurizer, but also has a high degree of covertness.