Your brain is unique – here’s how it could be used as the ultimate security password

Palaniappan Ramaswamy, University of Kent

Biometrics – technology that can recognise individuals based on physical and behavioural traits such as their faces, voices or fingerprints – are becoming increasingly important to combat financial fraud and security threats. This is because traditional approaches, such as those based on PIN numbers or passwords, are proving too easily compromised. For example, Barclays has introduced TouchID, whereby customers can log onto internet banking using fingerprint scanners on mobile phones. The Conversation

However, this is not foolproof either – it is possible to forge such biometrics. Fingers can after all be chopped off and placed by impostors to gain fraudulent access. It has also been shown that prints lifted from glass using cellophane tape can be used with gelatine to create fake prints. So there is a real need to come up with more advanced biometrics that are difficult or impossible to forge. And a promising alternative is the brain.

Emerging biometric technology based on the electrical activity of the brain have indeed shown potential to be fraud resistant. Over the years, a number of research studies have found that “brainprints” (readings of how the brain reacts to certain words or tasks) are unique to individuals as each person’s brain is wired to think differently. In fact, the brain can be used to identify someone from a pool of 102 users with more than 98% accuracy at the moment, which is very close to that of fingerprints (99.8% accuracy).

More recently, this has been confirmed by functional magnetic resonance imaging (fMRI), which measures brain activity by tracking changes in blood flow. A study using fMRI data from the Human Connectome Project was able to recognise individuals with up to 99% accuracy when performing certain mental tasks such as relaxing, listening to a story, computing maths, looking at emotional faces or imagining moving parts of their body.

Fingerprints are commonly used.

However, the cost and difficulty of using fMRI (you have to lie very still in the scanner for a fairly long time) means it is clearly not practical for everyday biometric authentication. For that reason, researchers have instead looked at electroencephalography (EEG), which uses electrodes to track and record brain-wave patterns. But this is also cumbersome – who would be willing to wear a cap of gel-based electrodes just to log in to their computer? Hence, the technology has remained in the realm of science fiction for some time.

Promising alternatives

Recently, technological advances in recording EEG from the ear using electrodes placed on the surface of standard earphones have provided a solution – no gel needed. It is not easy though – EEG is very “noisy” since the brain is always actively processing different information. But advanced signal-processing approaches have recently been able to reduce the noisy components, albeit this typically requires powerful computing. This is, however, becoming less of a problem now that mobile-phone processing power is growing rapidly – it should in theory be possible to perform all the required processing on a smart phone.

So why aren’t brainprints everywhere already? One downside is that it can’t be used by twins – they have near-identical EEG patterns. But the main problem is the lack of stability of brainprints over time.

It seems that it is not enough to just have an EEG done once – occasional re-enrolment (say, monthly) is necessary. This is because the brain connections exhibit plastic behaviour (they change with experience) and thought processes in the brain change over time. However, in ongoing work at the University of Kent, we have shown that specific tones (which can be played using earphones) can be used to minimise these changes. It is not yet clear exactly how these tones affect the brain but we speculate that they may allow the brain to calm down, allowing more focused activity.

Two-factor authentication is now a norm for many banking transactions, for example using a password and an additional code sent to the phone. Soon, banks in New York may have to comply with multi-factor authentication protocol proposed by the New York State Department of Financial Services, whereby at least three authentication mechanisms are used for enhanced security by personnel accessing internal systems with privileged access or to support functions including remote access.

While fingerprints and voice recognition are possibilities, thought-based biometric technology is more apt to be used as an add-on to meet this new cybersecurity regulation. The brain biometric template could even be updated for a different mental activity should there be a security breach on the stored template (unlike a fingerprint biometric which remains for life and cannot be replaced once compromised).

Brainprints can also be used to generate passwords that can replace conventional alphanumeric passwords or PINs in ATM machines to withdraw cash. For example, rather than keying in the PIN, one would connect earphones and be shown a series of PIN numbers on the ATM screen. Brain patterns would change when the correct PIN number showed up – activating the transaction. By doing so, one does not have to worry about others looking over the shoulder to steal the PIN. Moreover, under coerced situations, brainprints will not work due to the stress – making them even more fraud resistant.

Given that it is difficult to copy another person’s exact thought process, the technology is certainly advantageous. Considering the advancement in the technology, we will likely see uptake of biometric applications based on brainprints soon – especially as part of multi-factor system for enhanced authentication. So don’t be surprised to see EEG earphones appearing in your post from the bank shortly.

Palaniappan Ramaswamy, Reader in Signal Analysis, University of Kent

This article was originally published on The Conversation. Read the original article.

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Professor of Cyber Security vacancy

The School of Computing is looking to appoint a Professor of Cyber Security to lead its highly successful Security research group.

The School has an outstanding reputation for research and education in cyber security where, for example, its MSc Cyber Security has been provisionally accredited by GCHQ.

We seek applications from senior academics with a distinguished and sustained track record of research leadership and attainment.  The closing date is 10 April and interviews will be held on 17 May.


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Maria Christakis wins the Best PhD Dissertation Award

The European Association for Programming Languages and Systems (EAPLS) Best PhD Dissertation Award 2015 has been won by Dr Maria Christakis, from the School of Computing for her dissertation ‘Narrowing the gap between verification and systematic testing‘.

This award is given to the PhD student who has made the most original and influential contribution to the area of Programming Languages and Systems, and has graduated in 2015 at a European academic institute. The purpose of the award is to draw attention to excellent work, to help the career of the student in question, and to promote the research field as a whole.

Maria said: ‘I’m so happy, moved, and excited to have won such a prestigious award. It reinforces my passion for research, with both theoretical and practical impact. I am grateful to the EAPLS committee, my PhD advisor Peter Müller at ETH Zürich, and all my collaborators.’

Maria’s thesis was judged on originality, impact, relevance, and quality of writing by a committee of international experts. They concluded unanimously that Dr Christakis’ dissertation is an outstanding piece of work; it received the best marks amidst some very strong contenders.

A summary of the jury’s findings:

  • The thesis contains an effort in combining verification and testing, fields that seemed to be disjoint to date.
  • This thesis presents both novel theoretical and practical results on a high level. There are contributions that advance the state of the art both in testing and verification as well as a case study on a real piece of software.
  • Her contributions are significant and novel, the breadth is also “unusual” or “impressive”, and she implemented and evaluated with industrial tools.
  • The results have been published in a series of internationally well-known conferences: FM, TACAS, ICSE, VMCAI, SEFM, RV, and SPIN.
  • The dissertation is very well written.

A spokesperson from EAPLS said: ‘We offer Dr Christakis our heartfelt congratulations with her achievement. We are confident that it will be a sign of a long and distinguished scientific career.’

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PhD pass for Alexia Zoumpoulaki

Congratulations to Alexia Zoumpoulaki, who has recently passed her PhD viva, with minor corrections. Alexia’s PhD thesis was titled ‘Detecting Perceptual Breakthrough in RSVP with Applications in Deception Detection: Methodological, Behavioural and Electrophysiological Explorations’ and was supervised by Howard Bowman.

Alexia explained; ‘My research explores perceptual breakthrough in rapid serial visual presentation (RSVP), for deception detection applications. In RSVP, visual stimuli are presented in rapid succession, pushing the perceptual processing system to the limit, allowing only a limited number of stimuli to be processed and encoded. My work investigates what type of stimuli capture attention in RSVP, taking advantage of both physiological and behavioural measurements.’

Alexia presented methods developed for the analysis ​of Event Related Potential (ERP) data with applications beyond deception detection. The focus is on reducing false positives while at the same time successfully measuring the underlying effects. She presented and evaluated methods for measuring latencies, selecting Regions of Interest (ROIs) and testing for significance. Alexia also presented evaluations of the protocol developed by her research group and explorations on how to improve it.


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Student consultants present to national computing group

Students from KITC (Kent IT Consultancy) presented examples of their work at an event entitled ‘Becoming a Consultant – the Next Generation’ at the headquarters of BCS, the Chartered Institute for IT.

Student consultants at the KITC are ‘the graduates of tomorrow helping the businesses of today’, and work on projects for paying clients, who are usually local small and medium enterprises. Their work forms as assessed part of their undergraduate or Master’s programme.

Professor Simon Thompson, Director of Innovation at the School of Computing, presented the concept of the KITC to delegates, before students gave examples of current projects and how their work benefits the client and the students. Simon said: ‘Our students were very impressive, not just in the presentations that they gave, but also in making the most of networking at the event. They are a credit to the School and it was good to see our student consultants from both Canterbury and Medway programmes working as such a strong team together.’


How do new entrants to the digital economy gain experience in Consultancy? The University of Kent’s School of Computing have an innovative solution through their Kent IT Consultancy (KITC) business unit, a student staffed IT consultancy which delivers services to local small and medium enterprises. Each year KITC has a number of Student Consultant roles which are awarded based on a candidate’s suitability for the role. This supports their mission: “To solve business problems with technology and to make our student consultants more employable”.



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Kent expert shares biomedical signal knowledge in India

Dr Palaniappan Ramaswamy has delivered two courses on biomedical signals to colleagues in two Indian universities as part of an initiative to elevate India’s scientific and technological capacity to global excellence.

Palani, who is a Reader based at the School of Computing in Medway, was invited to deliver two one week courses for university staff, medical professors and postgraduate students. He taught on the analysis of biomedical signals such as electrocardiogram and electroencephalogram and how important it has become in providing cost effective point-of care diagnosis and personalised treatment.

The course on Practical Biological Signal Analysis was delivered in the National Institute of Technology, Karnataka, and one on Biomedical Engineering: Insights and Signal Processing in Aligarh Muslim University, one of the oldest educational institutions in India.

Palani said: ‘The courses exposed students, engineers and scientists attendees to recent developments in biomedical signal processing that have taken place in some of the most prominent international research centres and universities of the world. Simple approaches were followed in the delivery of the course. Mathematics was used only where necessary and when used, numerical examples that were suitable for paper and pencil were given. There were plenty of illustrations (‘picture speaks thousand words’) to aid the attendee in understanding the signal analysis methods and the results of applying the methods.’

The courses were funded by the Government of India under the Global Initiative Academic Network programme which aims to tap the talent pool of scientists and entrepreneurs internationally to encourage their engagement with the institutes of Higher Education in India.


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PhD success for Konstantin Kapinchev

Congratulations to Konstantin Kapinchev, who has recently passed his PhD viva, with minor corrections. His PhD thesis was titled ‘Scalable Parallel Optimization of Digital Signal Processing in the Fourier Domain’.

Konstantin’s thesis was supervised by Fred Barnes and examined by Dr Mark Batty with Professor Brian Vinter from the University of Copenhagen as the external examiner.

Konstantin said: ‘As well as my supervisor and examiners, I would also like to extend thanks to Professor Adrian Podoleanu in the School of Physical Sciences for his expertise and willingness to help during my work.’


The aim of the research presented in this thesis is to study different approaches to the parallel optimization of digital signal processing algorithms and optical coherence tomography methods. The parallel approaches are based on multithreading for multi-core and many-core architectures. The thesis follows the process of designing and implementing the parallel algorithms and programs and their integration into optical coherence tomography systems.

Evaluations of the performance and scalability of the proposed parallel solutions are presented.
The digital signal processing considered in this thesis is divided into two groups. The first one includes generally employed algorithms operating with digital signals in the Fourier domain. Those include forward and inverse Fourier transform, cross-correlation, convolution and others.
The second group involves optical coherence tomography methods, which incorporate the aforementioned algorithms. These methods are used to generate cross-sectional, en-face and confocal OCT images. Identifying the optimal parallel approaches to these methods allows improvements in the OCT imagery in terms of performance and content. The proposed parallel accelerations lead to real-time generated comprehensive imagery. This improves the utilization of the optical coherence tomography systems, especially in areas such as ophthalmology, where detailed visual information provided in real-time is crucial for accurate diagnosis.

A number of reports on performance, in terms of latency and speed-up, provide information for a balanced choice between performance and OCT method and between performance and size of digital signal, which in many cases is linked to image quality. The proposed parallel approaches, along with providing solutions to a range of signal processing problems, illustrate the computational characteristics, both sequential and parallel, of the utilized microarchitectures, language specifications, and libraries. To reach an improved performance, computer programs need to reflect these characteristics.

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PhD pass for Davin McCall

Congratulations to Davin McCall, research student in the School of Computing, who has recently passed his PhD viva, with minor corrections. His PhD thesis was entitled ‘Novice Programmer Errors – Analysis and Diagnostics‘.

The thesis detailed a systematic and thorough approach both to analysing which errors that are most problematic for students, and to automated diagnosis of errors.


All programmers make errors when writing program code, and for novices the difficulty of repairing errors can be frustrating and demoralising. It is widely recognised that compiler error diagnostics can be inaccurate, imprecise, or otherwise difficult for novices to comprehend, and many approaches to mitigating the difficulty of dealing with errors are centered around the production of diagnostic messages with improved accuracy and precision, and revised wording considered more suitable for novices. These efforts have shown limited success, partially due to uncertainty surrounding the types of error that students actually have the most difficulty with – which has most commonly been assessed by categorising them according to the diagnostic message already produced – and a traditional approach to the error diagnosis process which has known limitations.

In this thesis we detail a systematic and thorough approach both to analysing which errors that are most problematic for students, and to automated diagnosis of errors. We detail a methodology for developing a category schema for errors and for classifying individual errors in student programs according to such a schema. We show that this classification results in a different picture of the distribution of error types when compared to a classification according to diagnostic messages. We formally define the severity of an error type as a product of its frequency and difficulty, and by using repair time as an indicator of difficulty we show that error types rank differently via severity than they do by frequency alone.

Having developed a ranking of errors according to severity, we then investigate the contextual information within source code that experienced programmers can use to more accurately and precisely classify errors than compiler tools typically do. We show that, for a number of more severe errors, these techniques can be applied in an automated tool to provide better diagnostics than are provided by traditional compilers.

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Year in Computing launches for 2017

Many students are keen to learn the tech skills that will make them stand out to a graduate employer, or simply want to learn more about computing for their own interests.

The School of Computing offers a ‘Year in Computing‘ for all Kent undergraduate students*. This extra year can be taken after stage 2 or the final year of a students’ current degree programme.

Students interested in finding out more can come to a kickstart lunch on Wednesday 25 January at 12.30 in SW101, Cornwallis South, to find out more.

The Year in Computing will especially be of interest to students if;

  • they are interested in studying computing AND their current degree,
  • they would like to get prepared for a career in tech,
  • they are interested in exploring the frontiers of their subject and computing,
  • they want to learn how to be creative with computing.

The Year in Computing’s current cohort of students come from a wide range of academic disciplines and have been very positive about learning computing in addition to their original degree. In anonymous feedback students listed the aspects of the programme they liked, including:

  • when my code actually works
  • the range of different subjects/information behind Computing
  • learning different programming languages
  • the photo examples in lectures
  • engaging with my lecturers both in and out of classes
  • I really understand the content and don’t feel stupid for asking questions


*with the exception of students from the School of Computing and School of Psychology

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New Head of School – Professor Richard Jones

Professor Richard Jones has been appointed as Head of School, a three year post starting on 1 January 2017. Richard is Professor of Computer Systems and has worked at the School of Computing in University of Kent since 1985.

He is well known for his research and books on dynamic memory management (‘garbage collection’).

The role of Head of School is a high-profile one within the University and provides academic and professional leadership. Richard said:
‘The longer I work in the School of Computing, the more proud I am of its staff and students. Every year I am impressed by the inventiveness and quality of their final year projects or MSc dissertations. It’s no wonder that their hard work, combined with opportunities such as the Year in Industry, leads to an excellent employment record. Our research is world class and in some areas, world leading. GCHQ has provisionally accredited our Cyber Security MSc and recognises the School as an Academic Centre of Excellence in Cyber Security Research, one of only 13 in the country.’ 

‘We have the potential and opportunity to do even better. Over the past few years, many energetic and enthusiastic computer scientists have joined the School, and we will continue to grow. I want to see Kent become one of the top UK schools for computer science, both for teaching and research. The quality of our students’ education is a priority. We – and I mean staff and students – need to think about the ways we teach and learn. One of my first objectives is to review this. On the research side, our Programming Languages and Systems research group is already world leading. I want our work to make a difference in a world of opportunities and vulnerabilities.  So further strengthening our Cyber Security group is important, and we’ve already created a new Data Science research group at our Medway campus.’

Richard was made a Distinguished Scientist of the ACM in 2006 and an Honorary Fellow of the University of Glasgow in July 2005. He is a Fellow of the British Computer Society. He received IBM Faculty Awards in 2003, 2004 and 2005 and was elected to AITO, Association Internationale pour les Technologies Objets, in 2014. He is also an Editor of the journal Software: Practice and Experience.

Professor Richard Jones sailing in the Thames estuary

Outside work, Richard is a keen sailor and cyclist.

Professor Frank Wang, who was Head of School for the previous six years, will continue to teach and research as part of the Data Science Research Group.

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