Context: To reduce greenhouses gases from the largest emitting sector, electric vehicles (EVs) present great opportunities for country like UK. Air pollution, which is considered as the second largest cause of death in UK, can be reduced using EVs. EVs can play a big role in achieving the decarbonization targets by UK. The UK government has announced £80 million ($99.7m) of investment to develop the next generation of EVs. With the introduction of sensing and actuation in EVs, there is an improvement in energy efficiency and battery energy consumption predictions. Different components in EV like sensors, human drivers, roadside infrastructure, and charging stations communicate with each other collecting information about the condition of EV and the environment in which the vehicle is moving. This exchange of information with the server could be vulnerable to security attacks (including message modification and spoofing), especially when an adversary takes control over an in-vehicle network (e.g. a CAN, Flexray, LIN or Ethernet bus) or the vehicle-to-infrastructure communication channel. Therefore, maintaining safety and security of the EV and interaction with its surrounding infrastructure is crucial, as an adversary can mount coordinating/cascading attacks that can disrupt the service of the grid or can damage the vehicle itself. Data privacy could also be at risk.
The School of Computer Science & Informatics has a strong emphasis on cyber security research due to recent grants, and also hosts the Airbus Centre of Excellence for Cyber Security and NCSC approved Academic Centres of Excellence in Cyber Security Research (ACE-CSR). Students attend research workshops and conferences, skills training through the Doctoral Academy, and have an opportunity to work with industry. A healthy research environment promotes research ideas and collaborations, and opportunities for networking through interdisciplinary work with the School of Engineering (Energy/EV research group).
Objectives: The objectives of this work are: (1) How can we help drivers better understand the driving conditions (especially in remote areas), such as road infrastructure, position of EV, weather, destination route and battery level, in a secure manner? And can we develop indicators around potential security conditions of a vehicle (providing a rating to the driver – e.g. low risk, high risk etc. – similar to driver alerts that are generated on the vehicle dashboard)? (2) How can we make drivers aware about the safety and security of the electric vehicle by improving its cyber-physical security? This includes exchange of information with the server over the insecure network, attacks on vehicles at changing station (propagating from electrical charging point to the EV infrastructure) and through vehicle’s battery as well. (3) How can we preserve data privacy of the moving EV and the drivers while processing the collected data?
- Surveys on risk, impact and state of the art: EVs’ safety and security;
- Developing techniques and capabilities that offers real-time predictions on driving conditions and safety under a secure environment;
- Situational awareness alerting platform to the drivers of electric vehicles about any safety and cyber-physical security-related issues, including risk prediction;
- Develop techniques for processing privacy-preserved data collected from EVs and drivers;
All these deliverables will be considered in the context of human factors – i.e. how do human drivers respond to events reported about potential cyberattacks and data privacy/leakage. The human factors work will also investigate how alert levels can be generated that require input from a driver;
Each of these deliverables will be publications arising from this work.
- Dr Neetesh Saxena
- Dr Qiyuan Zhang
- Prof Omer Rana
This project is to be self-funded.
A 2:1 or above Honours undergraduate degree or a master’s degree, in computing or a related subject. Applicants for whom English is not their first language must demonstrate their proficiency by obtaining an IELTS score of at least 6.5 overall, with a minimum of 6.0 in each skills component.
Please contact Dr. Neetesh Saxena to discuss this project.
For an overview of the programme, tuition fees and other information, visit the website here.
Read the How to Apply tab, and in the Apply box choose qualification Doctor of Philosophy in Computer Science & Informatics, mode of study Full-time. In the research proposal section of your application, specify the project title and supervisors of this project, and in the funding section, select the ‘self-funding’ option.