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本文研究虚假数据注入攻击对电力信息物理系统连锁故障的影响，辨识系统中的脆弱节点。首先，综合考虑电力网的潮流特性和信息网的监视与控制功能，建立了电力信息物理系统模型。然后，从理论上分析了信息网通信过程遭受虚假数据攻击对决策和控制过程的影响，给出了网络攻击环境下的连锁故障分析流程。从拓扑完整性、电力网运行特性两个方面定义了脆弱性评估指标,通过对比节点潮流介数与脆弱性评估指标，验证信息物理环境下潮流介数评估脆弱节点的有效性。最后，选用IEEE14节点电力网构建电力信息物理系统，仿真表明，上行通信通道和下行通信通道遭受虚假数据攻击均会影响信息网抑制连锁故障传播的能力，扩大连锁故障规模；并计算出了各节点的脆弱性评估指标，验证了潮流介数辨识脆弱节点的有效性。“,”This study considers the performance impacts of false data injection attacks on the cascading failures of a power cyber-physical system, and identifies vulnerable nodes. First, considering the monitoring and control functions of a cyber network and power flow characteristics of a power network, a power cyber-physical system model is established. Then, the influences of a false data attack on the decision-making and control processes of the cyber network communication processes are studied, and a cascading failure analysis process is proposed for the cyber-attack environment. In addition, a vulnerability evaluation index is defined from two perspectives, i.e., the topology integrity and power network operation characteristics. Moreover, the effectiveness of a power flow betweenness assessment for vulnerable nodes in the cyber-physical environment is verified based on comparing the node power flow betweenness and vulnerability assessment index. Finally, an IEEE14-bus power network is selected for constructing a power cyber-physical system. Simulations show that both the uplink communication channel and downlink communication channel suffer from false data attacks, which affect the ability of the cyber network to suppress the propagation of cascading failures, and expand the scale of the cascading failures. The vulnerability evaluation index is calculated for each node, so as to verify the effectiveness of identifying vulnerable nodes based on the power flow betweenness.