Collaborative Learning and Blockchain-enabled Cybersecurity Model for V2X Communications

The functional safety of many intelligent systems, such as autonomous robots and self-driving cars, remains largely dependent on the robustness of the underlying machine learning model. These systems are expected to operate flawlessly, and hence need to be trained on examples of all possible situational conditions. State-of-the-art methods demonstrated that training models on representative summaries highly improves the robustness of the learned models against noisy labels, both in theory and practice. One concrete direction, this project aims to pursue along these lines is to build scalable, secure, privacy preserving, robust frameworks for safety-critical systems for V2X communications using Blockchain and collaborative learning. In particular, the project will focus in developing optimization methods that can provide guarantees for the quality of inference under noisy data, noisy labels, and adversarial attacks.

Candidates should have (or expect to achieve) a UK honours degree at 2.1 or above (or equivalent) in Computer Science, Cyber Security, Mathematics or related fields. A relevant Master’s degree and/or experience in one of the above will be an advantage. 

We are looking for a PhD student, who has a background in machine learning techniques and Blockchain technology. Knowledge of Security and Privacy would also be an advantage.

APPLICATION PROCEDURE:

Formal applications can be completed online: https://www.abdn.ac.uk/pgap/login.php

• Apply for Degree of Doctor of Philosophy in Computing Science

• State name of the lead supervisor as the Name of Proposed Supervisor

• State ‘Self-funded’ as Intended Source of Funding

• State the exact project title on the application form

When applying please ensure all required documents are attached:

• All degree certificates and transcripts (Undergraduate AND Postgraduate MSc-officially translated into English where necessary)

• Detailed CV, Personal Statement and Intended source of funding

Informal inquiries can be made to Dr P K Sharma ([Email Address Removed]), with a copy of your curriculum vitae and cover letter. All general enquiries should be directed to the Postgraduate Research School ([Email Address Removed])