A Copula-Based Attack Prediction Model for Vehicle-to-Grid Networks

The Vehicle-to-Grid (V2G) networks are a part of the Smart Grid networks. Their primary goal is to recharge electric vehicles. These networks, as with any computer system, facing cyber attacks. For example, during charge or process, V2G can be vulnerable attacks such Man-in-the-Middle (MitM), Denial Service (DoS), identity theft, and rebound It therefore up us offer innovative solutions in order reduce threats much possible. In this paper, model based on copulas detect intrusion cases proposed. To achieve model, database generated first from three scenarios using tools including MiniV2G, Wireshark, CICflowMeter. Then, significant variables selected Principal Component Analysis (PCA). classification algorithm notion constructed under software R. From obtained results, it emerges that created has very high prediction rate aforementioned network.