Data-Driven-Based Attack Detection Framework Using Graph Convolution Neural Networks in Smart Grids

False data injection attacks (FDIAs) can compromise power system state estimation by falsifying measurement data, thereby distorting grid control decisions without being detected. Thus, this paper develops a data - driven detection framework using a graph convolutional network (GCN). The proposed GC... View More