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恒温控制网络入侵中的攻击阶段会使温度信号的输出产生巨大的波动,使得对其稳定性的控制难度增大.传统的温控网络入侵波动抑制方法主要是锁定信号干扰源并加以排除,但是在干扰源不确定的情况下,传统方法缺少主动防御能力,被动性明显.提出基于最优入侵特征分类模型的恒温控制网络中入侵波动抑制方法.利用最优入侵特征分类方法对温控网络的入侵进行准确分类,获取入侵特征基向量的加权和矩阵形式,计算基向量的正交向量,以获取入侵向量估计值,根据入侵检测的结果计算输出信号的波动变化,对入侵后的信号波动系数进行有效变换,并对波动系数的大小进行动态调整以输出控制指令信号的补偿量,完成对温控网络入侵后的信号波动抑制.实验结果表明,该模型在恒温控制网络中,对入侵后温度信号波动抑制方面有着明显的优越性.
In the attack stage of constant temperature control network intrusion, the output of the temperature signal will be greatly fluctuated, making it more difficult to control the stability of the network.Traditional temperature control network intrusion suppression method is mainly to lock the signal interference source and to exclude, but In the case of uncertain sources of interference, the traditional method lacks the ability of active defense, and the passivity is obvious.An intrusion control method based on the optimal intrusion classification model is proposed to suppress intrusion.An optimal intrusion classification method is applied to the temperature control network Intrusion is classified accurately, and the matrix of weighted sum of invaded base vectors is obtained. The orthogonal vectors of base vectors are calculated to get the invaded vector estimates. The fluctuation of output signals is calculated according to the intrusion detection results. The signal fluctuation coefficients And the amplitude of the fluctuation coefficient is dynamically adjusted to output the compensation amount of the control command signal to complete the signal fluctuation suppression after the temperature control network intrusion.The experimental results show that in the temperature control network, Signal fluctuation has obvious advantages.