شناسایی خوشه های گره آسیب پذیر در برابر حملات تزریقی داده های نادرست در شبکه هوشمند مبتنی بر AMI

In this paper, we study the physical characteristics of the power system, and draw a relationship between the system stability indices and the FDI attacks. We identify the level of vulnerabilities of each AMI node in terms of different degrees of FDI attacks. In order to obtain the interdependent relationship of different nodes, we implement an improved Constriction Factor Particle Swarm Optimization (CF-PSO) based hybrid clustering technique to group the nodes into the most, the moderate and the least vulnerable clusters. With extensive experiments and analysis using two benchmark test systems, we show that the nodes in the most vulnerable cluster exhibit higher likelihood of de-stabilizing system operation compared to other nodes. Complementing research is the construction of FDI attacks and their countermeasures, this paper focuses on the understanding of characteristics and practical effect of FDI attacks on the operation of the Smart Grid by analysing the interdependent nature of its physical properties.