| Abstrakt: |
V2G (Vehicle-to-Grid) is a system that allows an electric vehicle to connect and exchange energy with the electricity grid. This system is part of the smart-grid, which is an intelligent electricity network offering bidirectional communication and contributes to the environmental protection. Different actors are involved in communication in a V2G network, such as electric vehicles, charging stations, energy suppliers, and network operators, etc. Therefore, the V2G network faces several security challenges, such as data integrity, power system security, physical security of charging systems, data confidentiality and system interoperability. In this paper, an intrusion detection system (IDS) is proposed with the aim of predicting attacks in the V2G network. The study started with the generation of a dataset and the implementation of the Cockroach Behavior-Based Machine Learning Classifier with the objective of enhancing security of V2G networks by addressing Men-in-the-Middle (MitM) and Denial of Service (DoS) attacks. The simulation results, through the MiniV2G simulator, show that the proposed system achieved a detection accuracy of 98.93 %. This improves the reliability of the V2G network for users and better protects Electric Vehicle Charging Stations (EVCS) against DoS and MitM. [ABSTRACT FROM AUTHOR] |
