Safeguarding the Future of Mobility: Cybersecurity Issues and Solutions for Infrastructure Associated with Electric Vehicle Charging
Year: 2025
Type: article
Abstract: The development of an ecosystem that balances consumer convenience and security is imperative given the expanding market for electric vehicles (EVs). The vast amount of data that EV charging station management systems (EVCSMSs) give is powered by the Internet of Things (IoT) ecosystem. Intrusion Detection Systems (IDSs), which track network traffic to spot potentially dangerous data exchanges in IT and IoT contexts, are constantly improving in terms of efficacy and accuracy. Intrusion detection is becoming a major topic in academia because of the acceleration of IDS development caused by machine learning and deep learning techniques. The goal of the research presented in this paper is to use a machine-learning-based intrusion detection system with low false-positive rates and high accuracy to safeguard the ecosystem of EV charging stations (EVCS).
Authors: Md Rakibul Karim Akanda, Joao Raimundo Queiroz Pires Santana De Oliveira Lima, Amaya Alexandria Holmes, Christina Bonner
Institution: Savannah State University
Language: English
Subfield: Computer Networks and Communications
Field: Computer Science
Domain: Physical Sciences
Open Access status: diamond
OpenAlex ID: W4408821118