EVs, charging Stations, and cyber security
Research by UofM faculty Ali will focus on charging station cyber-attack impacts and solutions
The University of Memphis received a $498,083 grant for two years to conduct research through the project “Cyber Resilient 5G-Enabled Electric Vehicle Charging Infrastructure,” under the NCAE-C (National Centers of Academic Excellence in Cybersecurity). Dr. Mohd Hasan Ali, associate professor of Electrical and Computer Engineering, will serve as the Principal Investigator (PI) and Dr. Dipankar Dasgupta, Hill Professor in Cybersecurity and director of the Center for Information Assurance, will serve as the Co-PI. This project is affiliated with the University of Memphis Center for Information Assurance (CfIA), located inside the FedEx Institute of Technology. Ali is an associate director of the Center.
Recent research on electric vehicle (EV) charging is getting increasingly popular because of cleaner, climate friendly and reduced operational costs. EVs significantly reduce greenhouse gas emissions and society’s reliance on fossil fuels. However, the lack of charging infrastructure and prolonged charging time can lead to driving range anxiety. One of the preferred options is to improve the charging infrastructure and reduce charging time. Although plug-in electric vehicles (PEVs) can improve national energy security, they also present a new cybersecurity vulnerability to the U.S. transportation sector and the electricity grid. A single hacking attack, initiated from PEVs or the charging stations, could have serious physical implications. The energy flow in charge/discharge process of PEVs might be modified by the attackers, and the real-time data such as energy usage of customer and charging price from utility might be stolen. Furthermore, the automation of electric vehicle charging station (EVCS) operation and management requires remote centralized control like supervisory control and data acquisition (SCADA) that can communicate with numerous field devices with the least possible delay.
Recently 5G technology has emerged as the paradigm shift for cellular communication due to its ultra-low latency and a very high speed. By providing real-time control and extremely fast communication, 5G can be an appropriate solution to successfully enable communication between the SCADA and various intelligent controllers and smart components of EVCS. Although researchers listed and characterized exploitable backdoors of the EV charging infrastructure, they lack the impact analysis of attacks and detection and mitigation strategies. To overcome the limitation and drawbacks of the existing approaches and to fill in the technical gaps, this project proposes to design and develop a cyber secure 5G-enabled EVCS.
The overall goal of the proposed research is to explore related technologies to develop a secure and trustworthy approach for 5G-enabled EVCS and its charging system. To achieve this goal, the project will have several objectives: i) analyzing the negative impacts of cyberattacks on EVCS and charging system; ii) detecting cyberattacks on the 5G connected EVCS; and iii) exploring mitigation solutions for 5G based EVCS. Their focus is to design and develop EVCS related cybersecurity research, education and outreach program in order to address the technical needs of students (future workforce) and industry professionals in energy/utility.
The proposed research aims to develop a holistic approach for the 5G-enabled EVCS and to investigate unique cyber security challenges and solutions related to EVCS. They propose the Deep learning-based network intrusion detection system (NIDS) that constantly monitors the network packets. The proposed deep learning-driven detection algorithms can successfully detect distributed denial of service (DDoS) and false data injection (FDI) attacks on EVCS. Furthermore, we focus on developing mitigation and defense strategies against the attacks on EVCS. We propose the data-driven model-free distributed intelligence based on multiagent Deep Reinforcement Learning (DRL) to mitigate the cyberattacks on the controllers of EVCS. The project will help transform existing plug-in charging mechanisms into advanced secure and trustworthy wireless charging for smart EVs and other mobile artifacts with 5G-enabled communication. Equally important, the outcomes of this research will aid and provide inputs in the development of IEEE and IEC standards for EVs especially for emerging cyber vulnerabilities and system resiliency for this application domain.
This research will have significant impacts on industry, academia, and society at large. In industry, research outcomes will help manufacturers design a secure and resilient 5G-enabled EVCS. In academia, this work will impact the design of electrical engineering as well as computer science undergraduate and graduate level courses related to smart EVs design and cybersecurity. At a societal level, this work will help ensure safe and reliable charging infrastructure for EVs at both home and work environments. In military bases, the proposed 5G-based EVCS can play a great role in charging the vehicles securely and successfully. The PIs will also engage in outreach and educational activities designed to expose diverse populations, including women, minorities, and undergraduate students, to 5G-enabled EVCS and cybersecurity science.
Ali serves as the director of the Electric Power and Energy Systems (EPES) Laboratory at the UofM. His research interests include cybersecurity issues and solutions to modern power grids, electric vehicle charging system and station, 5G based communication system, smart-grid and micro-grid systems, renewable energy systems, and energy storage systems. Ali has more than 210 publications, including three books, six book chapters, three patents, 70 top ranked journal papers, 99 peer-reviewed international conference papers and 20 national conference papers. According to Google Scholar, as of October 2022, the total citations number of his published research is 5,039 with an H-index of 36 and i-10 index 98. In recent years, he has actively engaged in research related to cybersecurity issues and solutions to electric vehicle charging and infrastructure systems. He has edited a book titled Emerging Power Converters for Renewable Energy and Electric Vehicles (published by CRC Press, Taylor & Francis Group, June 2021, ISBN 9780367528034) and also a book chapter titled “A Deep Learning Perspective on Connected Automated Vehicle (CAV) Cybersecurity and Threat Intelligence", published in the book titled Deep Learning and Its Applications for Vehicle Networks by CRC Press, Taylor and Francis group, 2022.
For more information on this project and or research, contact Ali at mhali@memphis.edu.