Brain activity as a biometric: Towards more secure and robust authentication mechanisms

This exciting inter-disciplinary studentship will apply cutting-edge data processing tools in the context of cybersecurity. The successful applicant will be trained in an interdisciplinary area of research at the interface signal processing and informatics.

The electroencephalogram (EEG) acquires brain activity with high temporal resolution over the scalp surface. It is non-invasive and portable. Moreover, affordable, consumer-grade devices have recently become available and the potential range of applications of EEG devices is expanding rapidly over and beyond the traditional clinical use-cases (e.g., epilepsy diagnosis) into brain-computer interfaces (BCI) and neurofeedback.

The use of EEG for biometric recognition purposes has recently been investigated due to some of its appealing properties. Preliminary investigations have highlighted the feasibility of this approach when trying to recognize the participants’ EEG acquired with their eyes closed and open. However, this approach is based on a static view of brain activity during predetermined mental states. Therefore, the system could be compromised if an attacker gains access to the participants’ patterns stored in the system.

Instead, we propose to consider self-initiated thoughts to increase the system’s robustness. This would lead to an increase in the signal dynamics which we plan to model with advanced multidimensional signal processing techniques. The current state of the art is such that we are now in the position where we can grasp the long-standing vision of recognizing people from their brain activity.

Therefore, the main objective of this interdisciplinary project is the development of data processing tools for the use of EEG activity as a biometric. The EEG biometric system will be fully dynamic, where the user will self-initiate the authentication process and we will focus on the use of affordable and portable consumer-grade EEG devices to facilitate the uptake of the results outside academic settings.

Further Information: 

Closing Date: 

Friday, February 24, 2017
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School of Engineering

Principal Supervisor: 

Assistant Supervisor: 

Dr David Aspinall


Enthusiastic and self-motivated candidates are sought with a background in electronic engineering, informatics, mathematics or related discipline. Previous experience in areas related to signal processing and cybersecurity would be beneficial but it is not required. 

Minimum entry qualification - an Honours degree at 2:1 or above (or International equivalent) in a relevant science or engineering discipline, possibly supported by an MSc Degree. Further information on English language requirements for EU/Overseas applicants.


We welcome applications from UK and EU students eligible for Research Council funding, and from students from other nationalities interested in applying to scholarships from the University of Edinburgh or elsewhere.

Further information and other funding options.

Informal Enquiries: