Secure Network: A Novel IDS Against Spoofing Attacks in EVs

This project report focuses on a novel intrusion detection system (IDS) designed to protect connected electric vehicles (EVs) from spoofing attacks. The research explores the vulnerabilities of V2V (vehicle-to-vehicle) communication within VANETs (vehicular ad hoc networks), particularly concerning the impact of spoofing attacks on charging systems and network security. The study compares different charging systems, including static charging stations and mobile energy disseminators, and evaluates the effectiveness of an IDS based on supervised machine learning algorithms. It highlights the importance of secure communication, key distribution methods, and anonymous authentication schemes to strengthen VANETs against various threats. The paper also discusses the experimental evaluation using the city of Erlangen as a case study, employing the GEMV (geometry-based efficient propagation model) for the description of the modeled area. The findings emphasize the need for a probabilistic IDS to detect and mitigate spoofing attacks, ultimately aiming to enhance the security and reliability of EV networks.