Students preparing for their graduation ceremony at Canterbury Cathedral

Cyber Security - MSc

2017

On this GCHQ provisionally certified programme you will learn the essential skills to support cyber security within commercial and government organisations. This includes the technical side of encryption, authentication, biometrics, network security, etc as well as information security management and cyber security risk. 

2017

Overview

This MSc is aimed at computing graduates with strong programming skills seeking careers as cyber security professionals or careers that need a systematic and deep understanding of the subject. It would also be an excellent starting point for those wishing to carry out further research in cyber security.

About the School of Computing

Our world-leading researchers, in key areas such as cyber securityprogramming languagescomputational intelligence and data science, earned us an outstanding result in the recent Research Excellence Framework (REF). Our submission was ranked 12th in the UK for research intensity, with an impressive 98% of our research judged to be of international quality.

Strong links with industry underpin all our work, notably with Cisco Systems Inc, Microsoft, Oracle, IBM, Nvidia, Erlang Solutions, GCHQ and Google.

The School of Computing is a leader in computer science teaching. Our staff have received the ACM SIGCSE Award for Outstanding Contribution to Computer Science Education and two have been honoured as Distinguished Scientists by the Association of Computer Machinery (ACM). 

While studying with us, you can gain work experience through an industrial placement. Our dedicated placement team can help you gain a suitable paid position and provide support throughout your placement. 

We have a large range of equipment providing both Linux and PC-based systems. Our resources include a multicore enterprise server and a virtual machine server that supports computer security experiments. 

The School also has a makerspace, The Shed, which offers exciting teaching and collaboration opportunities. Among other equipment it contains a milling machine, 3D printers, laser cutter and extensive space for building and making digital artefacts.

Think Kent video series

This talk describes why identity theft is so easy to enact today over the Internet, and how it can be prevented by utilising the latest research in verifiable credentials.

National ratings

In the Research Excellence Framework (REF) 2014, research by the School of Computing was ranked 12th in the UK for research intensity.

An impressive 98% of our research was judged to be of international quality, with 81% of this judged world-leading or internationally excellent. The School’s environment was judged to be conducive to supporting the development of research of international excellence.

Course structure

Each of our taught MSc courses is available in several formats to accommodate students from different backgrounds and to provide maximum flexibility. See more about Taught Master's course formats.

Modules

The following modules are indicative of those offered on this programme. This list is based on the current curriculum and may change year to year in response to new curriculum developments and innovation.  Most programmes will require you to study a combination of compulsory and optional modules. You may also have the option to take modules from other programmes so that you may customise your programme and explore other subject areas that interest you.

Modules may include Credits

This module investigates the whole process of security management. A holistic view of security management is taken, starting with risk management and the formulation of security policies. Technical subjects include a description of the various security models, and showing how authorisation policies can be automatically enforced. The legal and privacy issues associated with information management are also addressed, as are the usability issues of security technologies. Finally, the module concludes by investigating how security has already been inbuilt into some existing applications, and how security issues will effect the uptake of ubiquitous computing systems

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A synopsis of the curriculumIntroduction, including a review of network techniques, switching and multiple access.High speed local area networks.Network protocols, including data link, network, transport and application layers.Real time data transmission and quality of service.Naming and addressing, including material on the domain name system, dynamic IP address allocation and address translation systems.Routing in data networksNetwork services.Firewalls and layer 3 network security.Recent developments. Topic will change from year to year and will be addressed prinicipally by research seminars and student centred research.

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• A study of cryptographic algorithms including symmetric and asymmetric techniques and the distinction between encryption and signatures.

• Security mechanisms used with operating systems, including: access control lists and capabilities. Trusted operating systems and common criteria for evaluation.

• Problems of network security including wiretap, replay, masquerade and denial of service. Mechanisms to provide security such as firewalls and VPNs.

• Viruses and worms.

• Distributed Mechanisms, including client authentication (Needham-Schroeder, Kerberos and others); public key infrastructures and certification, with treatment of chains and authority, and the problem of revocation.

• Digital rights management systems: CSS, OMA DRM. Using digital watermarking techniques for digital rights management.

• Security of IEEE 802.11 networks (aka Wi-Fi), presentation and discussion of their security protocols: WEP, WPA, WPA2, IEEE 802.11i and RSN.

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Students choose their project near the end of term 1 in coordination with the Project Research module (CO885). Projects are normally selected from a list of suggestions proposed by the school, a number of which may involve external collaboration. Alternatively, students may propose a project of their own if a suitable member of academic staff is available to act as the supervisor. In all cases the particular project must be appropriate for, and relevant to, the student's programme of study.

The project consists of an extended period during which students work on a specific piece of project work and a report on this work in the form of a dissertation. The project can be carried out individually or in groups, but the dissertation will always be individual. The project examines the student's ability to research the literature and related technologies, to understand and expand on a specific technical problem commensurate with their programme of study and relate it to other work, to carry out investigations and practical work generally including programming to describe results and draw conclusions from them and to write a coherent and well organised dissertation.

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The crowning piece of most Masters degrees is the Project and Dissertation in which you apply a wide range of skills learned in the taught modules to an interesting research problem or practical application of your choice. The Project Research module provides useful transferable skills for doing the project, and supports you in some preparatory tasks such as literature study and project planning.

Training in research methods is provided through a series of workshops, covering the following topics:

• Introduction to research

• Project selection

• Topic analysis

• Information gathering

• Simulation, experimentation and data analysis

• Writing about research

• Presenting research

• Intellectual property

• The publication process

• The review process

The module culminates in a mini-conference where students present their research.

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Email security. Spam: why? ; spam 'click through' rates; targeted spam; spam filtering systems. Phishing attacks; blocking fake sites; browser based defences. Email based malware and defences against this.

Intrusion detection and prevention systems; honey pots.

Denial of service; distributed denial of service; bot-nets; methods to detect complex denial of service attacks and defences against them.

Problems of eavesdropping; security in wireless networks.

Use of router based firewalls as a method to protect intranets: de-militarized zones, bastion hosts; internal intranet firewalls; personal firewalls.

Proxy based firewall systems: control over which parts of the Internet are accessible; black-lists and white-lists; key-word based filtering; time based controls.

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Syllabus

Federated identity management: OpenID, SAML, Liberty Alliance, ...

Privacy protection

Viruses and worms

Hacking

Secure architectures

Formal verification methods

E-mail security: SMTP-MIME, S/MIME

Secure software development methods and tools, common criteria, code inspections, code coverage tools, code evaluation tools etc.

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Lecture Syllabus

Fundamentals of Biometric Systems:

Biometrics and biometrics systems; Biometric modalities; Components of a biometric system;Biometrics sample acquisition, transformation, & normalisation; Introduction to characteristics of some specific key modalities including face recognition, iris recognition, handwritten signature verification, fingerprint processing; Errors, error sources, and error handling in identification systems; Concept of multimodal systems: accuracy, flexibility, usability, inclusion and exception handling. Characterising human behaviour in biometrics-based systems. Relationships with image and signal processing and pattern recognition techniques. Social issues, privacy, and trust.

Biometric Technologies:

Implementation of biometric systems. Examples of systems using the major modalities. Analysis of modality specific features and feature extraction, selection and classification strategies. State of the art in sensor technologies; Spoofing and counter-measures.

Coursework

Workshops

Four six-hour assessed practical workshops.

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Teaching and Assessment

Assessment is through a combination of unseen written examinations, written and practical coursework, student presentations, individual and group projects.

The substantial research or development project undertaken for other programmes is assessed by dissertation.

Programme aims

This programme aims to:

  • enhance the career prospects of graduates seeking employment in the computing/IT sector
  • prepare you for research and/or professional practice at the forefront of the discipline
  • develop an integrated and critically aware understanding of one or more areas of computing/IT and their applications (according to your degree title)
  • develop a variety of advanced intellectual and transferable skills
  • equip you with the lifelong learning skills necessary to keep abreast of future developments in the field.

Learning outcomes

Knowledge and understanding

You gain knowledge and understanding of:

  • how to engineer software systems that satisfy the needs of customers, using a state-of-the art methodology and an industrially-relevant programming language
  • a broad variety of advanced topics relating to computing/IT (the specific topics will depend on the optional modules you chose and may vary from year to year in response to developments in the field, staff changes etc)
  • the specification, design and implementation of software systems for a variety of platforms and across a range of application domains
  • security vulnerabilities of computer systems and networks and the countermeasures used to address them
  • the motivation, design, operation and management of modern systems for encryption, authentication and authorisation, including quality of service issues.
  • professional, legal, social, cultural and ethical issues related to the chosen field of computing.

Intellectual skills

You develop intellectual skills in:

  • the ability to identify, analyse and formulate criteria and specifications appropriate to a given problem
  • the ability to model problems and their solutions with an awareness of any tradeoffs involved
  • the ability to evaluate systems, processes or methodologies in terms of general quality attributes and possible tradeoffs
  • the ability to deal with complex issues both systematically and creatively
  • the ability to work with self-direction and originality in tackling and solving problems
  • the ability to make sound judgements in the absence of complete data
  • the ability to review a research paper or technical report critically and to present your findings to a group of peers
  • the ability to plan and execute a substantial research or development-based project and to report the work in the form of a dissertation.

Subject-specific skills

You gain subject-specific skills in:

  • the ability to specify, design, implement and test computer-based systems
  • the ability to deploy effectively the tools used for the construction and documentation of software
  • the ability to undertake practical work that explores techniques covered in the programme and to analyse and comment on the findings.

Transferable skills

You gain the following transferable skills:

  • the ability to plan, work and study independently and to use relevant resources in a manner that reflects good practice
  • the ability to make effective use of general IT facilities, including information retrieval skills
  • time management and organisational skills, including the ability to manage your own learning and development
  • an appreciation of the importance of continued professional development as part of lifelong learning
  • the ability to work effectively as a member of a team
  • the ability to communicate technical issues clearly to specialist and nonspecialists
  • the ability to present ideas, arguments and results in the form of a well-structured written report
  • the ability to act autonomously in planning and implementing tasks at professional or equivalent level.

Careers

Our programmes of study are designed to equip our graduates with the skills and knowledge that make them highly attractive to potential employers, providing a good balance between theoretical studies and real-life applications. The recent REF indicated that the School's research was in the top quartile of 89 Computing departments across the UK. Our graduates therefore benefit from a first-rate academic experience as well as being prepared to face the demands of the economic environment. 

Our graduates go on to work for leading companies including Cisco, GlaxoSmithKline, IBM, Intel, Lilly, Microsoft, Morgan Stanley, Thomson Reuters and T-Mobile. Many have gone on to develop their careers as project leaders and managers.

 

Study support

We provide an extensive support framework for our research students and encourage involvement in the international research community. We have strong links with industry including Cisco, IBM, Microsoft and Oracle.

Postgraduate resources

The School of Computing has a large range of equipment providing both UNIX (TM) and PCbased systems and a cluster facility consisting of 30 Linux-based PCs for parallel computation. New resources include a multi-core enterprise server with 128 hardware threads and a virtual machine server that supports computer security experiments.

All students benefit from a well-stocked library, giving access to e-books and online journals as well as books, and a high bandwidth internet gateway. The School and its research groups hold a series of regular seminars presented by staff as well as by visiting speakers and our students are welcome to attend.

The School of Computing has a makerspace on the Canterbury campus, which offers exciting new teaching and collaboration opportunities. Among other equipment, it contains milling machines, a 3D printer, laser cutter and extensive space for building and making digital artefacts. The School also owns speciallist equipment for Internet of Things and media steganography.

Our taught postgraduate students enjoy a high level of access to academic staff and have their own dedicated laboratory and study room. 

Links with industry

Strong links with industry underpin all our work, notably with Cisco, Microsoft, Oracle, IBM, Agilent Technologies, Erlang Solutions, Hewlett Packard Laboratories, Ericsson, Nvidia and Nexor.

 

Global Skills Award

All students registered for a taught Master's programme are eligible to apply for a place on our Global Skills Award Programme. The programme is designed to broaden your understanding of global issues and current affairs as well as to develop personal skills which will enhance your employability.  

Entry requirements

A first, 2.1 or good 2.2 honours degree (or equivalent) in computing or a related subject with a strong background in programming.

All applicants are considered on an individual basis and additional qualifications, and professional qualifications and experience will also be taken into account when considering applications. 

International students

Please see our International Student website for entry requirements by country and other relevant information for your country. 

Meet our staff in your country

For more advice about applying to Kent, you can meet our staff at a range of international events.

English language entry requirements

For detailed information see our English language requirements web pages. 

Please note that if you are required to meet an English language condition, we offer a number of pre-sessional courses in English for Academic Purposes through Kent International Pathways.

Research areas

Security Research Group

Security - of information, systems, and communications - has become a central issue in our society. Interaction between people's personal devices (far beyond just phones and computers) and the rest of the connected world is nearly continuous; and with the advent of the Internet Of Things its scope will only grow.

In that context, so much can go wrong - every communication can potentially be intercepted, modified, or spoofed, and surreptitiously obtained data can be commercially exploited or used for privacy invasions. In fact, data flows in society are such that many people already feel they have lost control over where (their) data goes.

The security research group operates within that context. All members bring a particular technological emphasis - the analysis of particular classes of security problems or their solutions - but are fully aware that it all fits within a wider context of people using systems and communicating data in secure and insecure ways, and how external pressures beyond the mere technology impact on that. The topic of computer security then naturally widens to include topics like privacy, cyber crime, and ethics and law relating to computing, as well as bringing in aspects of psychology, sociology and economics.

From that perspective, the Security research group played a key role in setting up, and continues to be a core contributor to, the University's Interdisciplinary Cyber Security Research Centre, see www.cybersecurity.kent.ac.uk. The centre achieved EPSRC/GCHQ accreditation as an Academic Centre of Excellence in 2015, one of only 13 in the country.

The group has a strong involvement with postgraduate teaching in this area. It teaches most of the core modules in MSc programmes in Computer Security, and Networks and Security. A new (from September 2017) MSc Course in Cyber Security has been provisionally certified by GCHQ. The group is also involved in undergraduate modules in this area, as well as postgraduate programmes in other schools such as the MSc Information Security and Biometrics, and in UK activities to define curricula in Cyber Security.

Areas of Research Activity

Members are engaged in the following areas of research (research areas in more detail) .

  • Data Ethics and Privacy
  • Authorisation Infrastructures
  • Cybercrime
  • Internet Of Things Security and Privacy
  • Authentication
  • Quantum Computation and Information, with Security Applications 
  • Formal Methods for Cryptography
  • Steganography and Steganalysis
  • Trust Management and Metrics and Reputation Systems
  • Tools for Vulnerability Analysis
  • Self-Adaptation applied to Security and Privacy
  • Cloud Security
  • Human Aspects of Security
  • Blockchain and Distributed Ledger Technology
  • Identity Management

Programming Languages and Systems Group

Our research involves all aspects of programming languages and systems, from fundamental theory to practical implementation. The Group has interests across a wide range of programming paradigms: object-oriented, concurrent, functional and logic. We research the links between logic and programming languages, the verification of the correctness of programs, and develop tools for refactoring, tracing and testing. We are interested in incorporating safe concurrent programming practices into language design.

The Group is also interested in practical implementation of programming languages, from massively concurrent parallel processing to batteryoperated mobile systems. Particular research topics include lightweight multi-threading kernels, highly concurrent operating systems, memory managers and garbage collectors.

Research areas include:

  • theoretical and architectural questions concerning designs for both hardware and software
  • abstractions and implementations of concurrency in programming languages
  • formal specification of systems and their architecture
  • design patterns and tools for enabling the safe and scalable exploitation of concurrency
  • compilers, memory managers and garbage collectors
  • lightweight multi-threading kernels and highly concurrent operating systems • refactoring of functional and concurrent languages
  • applications of formal methods to provably correct, secure systems
  • model checking and abstract interpretation, including applications to discovering security vulnerabilities
  • program verification and theorem proving

Computational Intelligence Group

This Group brings together interdisciplinary researchers investigating the interface between computer science and the domains of bioscience and cognition. In terms of applying computation to other domains, we have experts in investigating the modelling of gene expression and modeling of human attention, emotions and reasoning. From the perspective of applying biological metaphors to computation, we research new computational methods such as genetic algorithms and swarm intelligence.

The Group also develops novel techniques for data mining, visualisation and simulation. These use the results of interdisciplinary research for finding solutions to computationally expensive problems.

The Group has strong links with other schools at the University of Kent, as well as with universities, hospitals and scientific research institutes throughout the country and internationally.

Areas of research activity within the group include:

  • bio-inspired computing including neural networks, evolutionary
  • computing and swarm intelligence
  • application of computational simulations in biology and medicine
  • systems biology including gene expression modelling
  • theory and application of diagrammatic visualisation methods
  • data mining and knowledge discovery
  • construction of computational models of the human cognitive and neural system.

 

Computing Education Group

We focus on disciplinary-specific pedagogy, especially the teaching and learning of computer science and programming.

Our research interests focus on understanding the aspects of learning that are specific to computing education, and which range from examining general theories of learning, through thematically focused investigations (such as gender), to tool construction. We examine education from multiple aspects, including supporting computing education research infrastructure, working with teachers, or focusing on student learning.

Areas of interest include:

  • building an evidence base of research on early programming education
  • tool support for learning and teaching of programming, including custom-made development tools, such as educational programming languages, or development environments, which can adapt to changes in programming paradigms and technology and pedagogical advances
  • analysis of data generated as a part of the learning process, which could be text-based, naturally occurring in the classroom (eg, assessments), generated as a reflective process on learning (eg, diaries), or generated from interaction with programming environments.

Data Science Research Group

Data Science is about developing new techniques to better understand data and draws on many areas within and outside of computer science. Our research group develops and applies methods to interpret rich information sources.Our research comes under three themes:

eHealth

  • Dr Caroline Li gathers and analyses EEG data for to study of seasonal affective disorder.
  • Dr Srivas Chennu works on neurodynamics of consciousness, developing new tools to study brain networks, including improved diagnostics and prognostics during emergence from coma. He also uses neural network modelling for predictive coding in cognition.
  • Professor Ian McLoughlin studies speech signal processing, human hearing, automatic speech recognition as well as deep neural network acoustic models.
  • Dr Palani Ramaswamy has worked on biological signal analysis, brain-computer interfaces and biometrics. He has applied machine learning techniques to these and other fields.

Systems

  • Dr Fernando Otero, Professor Alex Frietas and  Dr Matteo Migliavacca, have developed new search-based approaches to computation, such as ant colony optimisation methods for predicting protein function.
  • Professor Frank Wang has shown that memristors can provide a radically new way to construct neural networks. In addition he has developed models of cloud computing for big data.

Finance

  • Dr Michael Kampouridis and Dr Fernando Otero research in the areas of algorithmic trading and financial forecasting. They have worked with different types of data, such as foreign exchange ultra-high frequency data. Algorithms they've used include genetic programming and ant colony optimisation.
  • Dr Kampouridis works on the pricing of weather derivatives by using machine learning algorithms.


Staff research interests

Full details of staff research interests can be found on the School's website.

David Barnes: Senior Lecturer

Simulation and modelling for biosciences, the teaching of introductory programming, chess cheating and legacy software.

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Dr Eerke Boiten: Senior Lecturer

Cyber security, including the use of formal methods, cryptography, privacy and data ethics. Refinement.

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Professor Howard Bowman: Professor of Cognition and Logic

Human attention, emotions, reasoning; connectionist modelling; symbolic modelling; EEG recording and analysis methods; formal methods and concurrency theory.

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Professor David Chadwick: Professor of Information Systems Security

Public key infrastructures; privilege management infrastructures; trust management; identity management; privacy management; policy based authorisation; cloud security; autonomic access controls and internet security research.

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Dr Olaf Chitil: Lecturer

Semantics and theoretical foundations of programming languages; type theory; program transformation; compiler construction; message-passing- based concurrency; programming tools; how to write programs.

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Dr Dominique Chu: Lecturer

Molecular computing (including biochemical computers), stochastic neural networks, complexity and computation, mathematical modelling of stochastic systems.

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Dr Rogerio de Lemos: Senior Lecturer

Software engineering for self-adaptive systems: dynamic generation of management processes, abstractions for supporting self-adaptability and self-organisation, resilience evaluation; self-adaptive dependable and secure systems; architecting dependable systems: abstractions for fault tolerance, and verification and validation of dependable software architectures; software development for safety-critical systems; dependability and bio-inspired computing.

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Professor Sally Fincher: Professor of Computing Education

The construction and boundaries of CS education; the teacher perspective, especially teacher decision-making; patterns and pattern languages, their use in knowledge-transfer, and their application to CS pedagogy.

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Professor Alex Freitas: Professor of Computational Intelligence

Data mining; the biology of ageing; evolutionary algorithms; bioinformatics.

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Dr Colin Johnson: Reader

Bioinformatics; computer simulation in biology; bio-inspired computing including genetic algorithms, genetic programming and swarm intelligence methods.

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Professor Richard Jones: Professor of Computer Systems

Implementation of programming languages; memory management; garbage collection, distributed garbage collection; object demographics; program analysis for improved memory management; program visualisation. 

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Dr Stefan Kahrs: Lecturer

Expressiveness of programming languages, type systems, term rewriting, infinitary rewriting.

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Michael Kampouridis: Lecturer

Computational finance; application of computational intelligence (CI) techniques to business-related problems, such as economics and finance; use of evolutionary techniques (eg, genetic algorithms, genetic programming); financial forecasting; intelligent decision support systems for business.

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Dr Andy King: Reader in Program Analysis

Abstract interpretation, logic programming and security.

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Dr Caroline Li: Lecturer

Tools for controlling computer/robot using brain signal; body sensor data fusion for healthcare and sports; methods for diagnosing, classifying and monitoring states of brain health/ illness; signal processing and machine learning methods.

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Fernando Otero: Lecturer

Development of ant colony optimisation algorithms for data mining; economic applications of data mining; bioinformatics; evolutionary algorithms, mainly genetic programming.

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Scott Owens: Lecturer

Semantics of shared memory concurrency; design of programming languages; formal verification for software and interactive theorem proving.

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Dr Peter Rodgers: Reader

Information visualisation; graph drawing; Euler diagrams.

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Professor Simon Thompson: Professor of Logic and Computation

Functional programming in Haskell, OCaml and Erlang; refactoring functional programs: tool building, theory and practice; dependently-typed functional programming; testing of complex and concurrent systems using properties; property extraction from test suites. 

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Gerald Tripp: Lecturer

Techniques for the analysis and control of high-speed packet networks, including system monitoring and network intrusion detection; use of special-purpose hardware and firmware designs to perform high-speed string and regular expression matching.

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Ian Utting: Senior Lecturer

Tool support for teaching and learning in CS, especially programming, and especially small and mobile devices; large scale data-driven studies of initial programming education, especially using Black Box.

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Professor Frank Wang: Professor of Future Computing; Head of School

Future computing; unconventional computing; non-Turing architecture; cloud computing; big data; deep learning; memristor; neural networks; nature-inspired computing; green computing.

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Dr Laura Bocchi: Lecturer

Theory and application of session types, concurrency and service-oriented computing.

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Professor Ian McLoughlin: Head of School (Medway)

Speech is the primary communications mechanism for humans, and is increasingly the way we interact with computers and mobile devices. In my research I deal with all aspects of speech, language and hearing, and ally this with powerful machine learning techniques that mimic how human brains acquire language and recognise sounds (machine hearing). My research team also works with speech-impaired patients to develop techniques that enable them to regain the power of speech in their daily lives.

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Dr Matteo Migliavacca: Lecturer

Stream processing, database systems, parallel data processing, networked systems, cloud computing, distributed systems, big data.

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Dr Palaniappan Ramaswamy: Reader, Admissions Officer (Medway)

Analysis of biomedical signals (such as EEG, PCG and ECG) for various applications: brain-computer interface, biometrics, electrophysiological analysis, cardiovascular disease diagnosis and stress management. Also, analysis of speech and image data for various engineering and computer science applications. Tools utilised: advanced signal processing and machine learning (such as neural networks and genetic algorithms).

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Fees

The 2017/18 annual tuition fees for this programme are:

Cyber Security - MSc at Canterbury:
UK/EU Overseas
Full-time £6500 £16720
Part-time £3250 £8360

For students continuing on this programme fees will increase year on year by no more than RPI + 3% in each academic year of study except where regulated.*

The University will assess your fee status as part of the application process. If you are uncertain about your fee status you may wish to seek advice from UKCISA before applying.

Funding

Scholarships and funding information