MSc Security Technologies and Applications

Taught master’s programmes in the Department of Computing utilise our research-active staff in conjunction with state-of-the-art facilities. We provide a range of learning experiences, including lectures, tutorials, directed study, practical laboratories and project work, which prepare graduates for their professional life.

We are particularly keen to develop, in all our students, a broad range of generic skills to complement the core technical or scientific competencies of their chosen subject area. Our modular programme format, coupled with the increasing use of innovative teaching and learning strategies such as e-learning and industrially focused short courses, provides a flexible study environment whilst maintaining academic rigour and quality.

Our record of graduate employment is outstanding, with Surrey graduates consistently being in high demand across all sectors.

The MSc dissertation project makes up one third of the degree programme, starting towards the end of the first semester and completing at the end of the summer. During the project, you are supervised by a member of academic staff to advise and guide you to completion. At the end of the project, you must submit your bound dissertation, which forms a complete record of the project.

The project focuses in depth on a subject at the leading edge of computing. For example, projects can undertake the development of a software system to solve a particular problem, possibly in collaboration with an industrial partner.

Alternatively, projects can be research-based, in which case an aspect of computing is investigated, perhaps to evaluate particular techniques or propose a new algorithm. These projects are usually closely linked to the Department’s research strengths.

Whatever the topic, you are expected to develop a critical understanding of the methods and technologies needed, then implement and evaluate your chosen solution to a professional standard. Project planning and time management is an important part of the experience.

David Lundin – E-voting Project

Elections across the globe have become high-profile events, not least because of their controversy, such as the American presidential election of 2000. One way in which elections can be made more reliable is through the use of electronic voting systems, which can provide security and verifiability.

Some electronic voting systems, such as Prêt à Voter and Punchscan, use a pre-printed paper ballot form, part of which is destroyed to create an encrypted receipt of the vote. The voter can use this receipt to check online that his or her vote has been included in the tally, but as the receipt is encrypted, it cannot be used to prove which candidate the vote is for. The problem with these ballot forms is that anyone who can see them before they are used has sufficient knowledge to check the contents of an encrypted receipt without it having to be properly decrypted.

In David’s MSc project, he developed a method based on visual encryption of the candidate list that hides the content of the ballot form until the moment when it is used by the voter in the voting booth. When the top layer, printed on the ballot form, is properly aligned over the bottom layer, displayed on a computer screen, the candidate list appears in plain text. When the form is removed from the screen, the content of the form is once again hidden.

Ian Golledge – Identifying and Classifying Electronic Spam

This project presents a prototype model for implementing a self-organising map as a spam filter. A method is shown where emails are converted into feature vectors, where features represent keywords. Keywords are selected from an analysis of an email corpus, with the results ranked based on word frequency measurements. The project describes phases of design which attempt to improve on feature selection and conclude on a prototype model for spam filtering using the self-organising map.

This prototype model is evaluated over six datasets of fluctuating ratios of ham and spam, with testing designed to emulate the incremental re-training of a personalised spam filter. The results are compared to common techniques in spam filtering. Initial results show the model can outperform popular Naive Bayesian techniques. The feature vector representation is then further developed and the model shows results that compare strongly against other classifiers identified in research, demonstrating effective application of self-organising maps for spam filtering.

The work was published at an international IEEE-sponsored conference in Italy:
Vrusias, B. and Golledge, I. (2008). ‘Adaptable text filters and unsupervised neural classifiers for spam detection’, Advances in Soft Computing, 53, 195–202.

Aaron Randall – Authentication and Self-Restoration of Watermarked Images

In an age where digital media use is prolific, accessible and cost-effective, the requirement for digital images to be used in such situations as evidence in court, medical imaging, traffic enforcement and forensics is increasingly important

However, along with digital media use, many different techniques to alter media files digitally have been developed – some with very realistic results. The ramifications of using potentially tampered digital media as evidence in court, for example, could cause the difference between an innocent or guilty verdict. This is an issue that digital watermark authentication and restoration attempts to answer.

Aaron’s MSc project was to develop an image authentication and restoration system capable of localising manipulated regions of an image. Through iterative restoration techniques and the extraction of hidden data from the image itself, he would then attempt to restore damaged regions. The first step of authentication highlighted any regions of the image that the application believed to have been tampered with in some way (such as cropping, blurring or other image manipulation techniques). The restoration stage then looked at fixing the regions highlighted as tampered. This step extracted hidden data from the image and inserted it back into the relevant damaged regions.

The Department of Computing is an active department within the Faculty of Engineering and Physical Sciences. There are 19 full-time academic staff and around 400 students at all levels – from undergraduate through to PhD. The Department is proud of its friendly reputation and aims to provide a supportive environment for students.

The Computing degree programmes at the University of Surrey and the all-round student experience are highly rated in the National Student Survey and league table results. The undergraduate and MSc postgraduate degree programmes are stimulating and challenging, with a high level of practical content. The Department is constantly exploring the use of new technology in teaching – such as podcasts and voting handsets – to support greater interactivity, accessibility and enjoyment of lectures. It also organises extra-curricular activities for those who want to explore other aspects of computing in more depth, while supporting local schools and colleges to bring some of the exciting aspects of computing to school pupils.

The Department’s research interests are many and varied, ranging across the research groups of Digital Ecosystems; Formal Methods and Security; Multimedia Security and Forensics; and Nature-Inspired Computing and Engineering. With a strong research culture and a growing research profile, the Department of Computing has won several prizes, including the University Voting Systems Competition System Design award in 2007 and the prestigious Institution of Engineering and Technology Innovation in Engineering Security award in 2006.

The Department offers four MSc programmes. Each with its own distinct focus, all of them offer a taste of the Department’s specialisms.

Internet Computing, Security Technologies and Applications, and Computational Intelligence and Computational Biology are technical degrees requiring a solid background in computing or a cognate discipline.

The MSc in Information Systems is a more generalist degree, accepting students from a wider range of backgrounds. It takes a more high-level, overall view on information technologies, and prepares students for managerial rather than technical roles in their future careers. It covers business and management topics as well as technical computing subjects.

The MSc in Security Technologies and Applications is specialised towards the Department’s multiple activities in relation to the technologies and principles that underlie a variety of information security techniques and technologies.

The MSc in Internet Computing is concerned with distributed information and computing resources, and builds from the Department’s activities relating to the Web and the Cloud.

The programme also has a strong element of more general, technical computer science and software development skills.

The MSc in Computational Intelligence and Computational Biology is the latest addition to the portfolio of programmes, following the appointment of a Professor of Computational Intelligence and the subsequent growth of a nature-inspired computing theme in the Department.

All of the programmes benefit from the strong research community and industrial partnerships of the Department. In particular, the dissertation project allows students to work on a topic in one of the key research areas. Even though the programmes share many modules, each has its own focus and direction.

Regardless of which programme you choose, we are committed to making your year at Surrey a valuable and enjoyable experience.

The Department benefits greatly from strong links with industry, and our industry partners support the programme in various ways, some with guest lectures and some with prizes for the best student performance (typically £150–200 per prize).

The Department pays a scholarship of £1,000 to students with a first-class honours degree or equivalent, who do not receive any other scholarship or bursary from the University. Please see the Department web pages for the full conditions.