Computer Science with Cyber Security (MEng)

This course gives you the digital skills and industry experience to protect companies and governments from the rapidly increasing threat of cyber crime.  Your skills will be in high demand when you graduate because of a global shortage of qualified cyber security professionals.

• You’ll be taught by academics who are directly contributing to important advances in areas like blockchain and the Internet of Things.
• The UK government’s National Cyber Security Centre recognises Southampton as a centre of excellence when it comes to research in this growth area.

As part of your master's, you will:

• Learn how to design, build and deliver software programs and systems
• Study in computer science labs recognised as an Academic Centre of Excellence in Cyber Security Research by the UK government
• Learn how to identify and address cyber security risks in software, internet-connected devices, web-based and networked systems
• Be taught by academic staff at the forefront of research
• Do an individual special project in year 3
• Take part in a group design project in year 4, working with an academic or an industry customer

Course structure

• This accredited course is designed to give you industry experience alongside our research-led teaching. We encourage you to take a summer work placement in an industry of your choice, or even add a full year in industry, to help you gain the experience you need for accreditation.
• All our computer science degree courses share the same compulsory modules in years 1 and 2, making it easy to switch between them. In the third and fourth years, you can tailor your degree by choosing optional modules.

Year 1 overview

• You’ll study the logical and mathematical theory underpinning computer science. You’ll also get an understanding of the fundamentals of computer hardware.
• As an introduction to software engineering, you’ll cover data structures and algorithms. You’ll also look at the principles of programming, including using object-oriented approaches and software engineering processes.
• You’ll apply your knowledge by working on practical projects. For example, you’ll build algorithms and data analysis tools, and develop software user interfaces.

Year 2 overview

• You’ll deepen your understanding of computer science by studying topics, such as artificial intelligence (AI), communication protocols and the TCP/IP layered model.
• A group project will give you first-hand experience of working in a team, and of the issues of communication and scale in software engineering.

Year 3 overview

• An individual project gives you the chance to conduct in-depth research in an area of computer science that interests you, under the supervision of an academic with expertise in your chosen field. This could involve designing, building and testing software or computer system.
• You’ll take compulsory modules in cyber security systems and engineering management. You’ll specialise in cyber security, choosing from options such as cyber crime, cryptography and data mining.
• You could also study a language, take modules from other disciplines such as psychology or chemistry, or choose from a range of innovative interdisciplinary modules.

Year 4 overview

• You’ll take part in a group design project, working in a team that may include students from other engineering disciplines for a real industry or academic customer.
• There is wide range of specialist modules to choose from. These cover topics such as biometrics, the dark web and e-business.

Modules

• The modules outlined provide examples of what you can expect to learn on this degree course based on recent academic teaching. As a research-led University, we undertake a continuous review of our course to ensure quality enhancement and to manage our resources. The precise modules available to you in future years may vary depending on staff availability and research interests, new topics of study, timetabling and student demand. Find out why, when and how we might make changes.

Year 1 modules
You must study the following modules in year 1:

Algorithmics

COMP Part I Laboratory Programme
This module is the lab programme for all first-year students enrolled on the Computer Science or Software Engineering degree programmes. Structurally, the Part I Laboratory Programme organises all practical, professional and laboratory-based work in Part ...

• Computer Systems I
• Data Management
• Mathematics I
• Mathematics II
• Networks and Security
• Programming I
• Programming II

Year 2
You must study the following modules in year 2:

• Artificial Intelligence
• Computer Systems II
• Formal Specification and Verification
• Programming III
• Programming Language Concepts
• Software Design and Development Project
• Theory of Computing

Year 3
You must study the following modules in year 3:

Part III Individual Project Phase 1

• The Part Three Individual Project gives students the opportunity to gain both detailed knowledge and practical experience in a more focussed area than generally possible elsewhere in their degree programme. Most projects are in the nature of a challenging...

Part III Individual Project Phase 2

• The Part III Individual Project gives students the opportunity to gain both detailed knowledge and practical experience in a more focussed area than generally possible elsewhere in their degree programme. Most projects are in the nature of a challenging e...

You must also choose from the following modules in year 3:

Advanced Computer Architecture

• This module covers the development of modern computer architectures for servers, workstations, hand-held devices, signal processing and embedded systems from the introduction of the four-stage RISC pipeline to the present day.

Advanced Computer Networks

• This module is designed to be a follow-up module to the computer Science or ITO second year introductory networking module. The wireless networking part reviews wireless technologies and their application in areas such as IoT and sensor networks. The mod...

Advanced Databases

• This module builds on the first year Data Management module to give students a deeper and broader view of the issues involved in database management systems, some of the most complex software in common use.

Causal Reasoning and Machine Learning
Cheminformatics

• This course is an introduction to the use of computers in chemistry, commonly referred to as cheminformatics. A number of aspects will be covered, with the aim of giving a firm basis to continue with research in cheminformatics in industry or academia. Th...

Cloud Application Development

• During the first two years of the degree students gain experience in a variety of 'traditional' programming languages in procedural, functional and object-oriented flavours. This module addresses the design and use of scripting languages for a contemporar...

Computational Biology

• Modern biology poses many challenging problems for the computer scientists. Rapid growth in instrumentation, and our ability to archive and distribute vast amounts of data, has significantly changed the way we attempt to understand cellular function, and ...

Computer Vision

• The challenge of computer vision is to develop a computer based system with the capabilities of the human eye-brain system. It is therefore primarily concerned with the problem of capturing and making sense of digital images. The field draws heavily on ma...

Foundations of Machine Learning

• Machine Learning is about extracting useful information from large and complex datasets. The subject is a rich mixture of concepts from function analysis, statistical modelling and computational techniques. The module will cover the fundamental principles...

Game Design and Development

• Games design and development is an increasingly important and sophisticated topic, that draws together many of the core aspects of Computer Science and Software Engineering. This course introduces students to the fundamentals of game design, gives them pr...

History of Computing

• Our modern world has been profoundly shaped by the availability of cheap and reliable computers, but the ubiquity of this technology has led many to overlook the rich history of its development. In this module, we will study the evolution of technologi...

Machine Learning Technologies

• Machine Learning is about extracting useful information from large and complex datasets. The module will cover the practical basis of how learning algorithms are can be applied. You will gain hands-on experience in laboratory-bases sessions. Exclusions...

Natural Language Processing

• This module gives students an introduction to natural language processing (NLP) algorithms and an understanding of how to implement NLP applications.

Operational Research

• The module introduces the operational research approach for modelling and solving engineering and management problems.

Optimisation

• The module provides an introduction to the theory and practice of optimization techniques. It covers linear programming as well as nonlinear programming. This module is suitable to those who want to apply computational optimization methods to their proble...

Real-Time Computing and Embedded Systems

• This module gives a broad introduction to development of real-time and embedded systems

Robotic Systems

• Robots are becoming more widely used in society, with applications ranging from agriculture through to manufacturing, with increasing interest in autonomous systems. This module will introduce students to the fundamentals of robotic systems including k...

Security of Cyber Physical Systems

• The course requires to understand C code, assembly language, x86 architectures and memory allocation (a refresher will be provided).

Social Computing Techniques

• Web Architecture and Hypertext Technologies
• Web and Cloud Based Security
• This module will teach the principles of security in web and cloud based systems and how these principles apply in a range of different applications.

Year 4
You must study the following modules in year 4:

Group Design Project

• This module provides an introduction to intensive group project work in collaboration with an industrial or academic customer. Students work in groups of at least four people on a project typically based on an idea from an industrial partner, or from an a...

Industrial Studies

• This Industrial Studies module is part of our MEng programmes with “Industrial Studies” in the title, and allows students to go on to a one-year placement in industry in Part III of their programme. Students are normally expected start their placement...

Software Security

• This module focuses on both theoretical and practical perspectives in the security of software and software systems, by exploring software analysis and reverse engineering. 
The aims of the module at a high level are to: 
- Explore common threats to ...

You must also choose from the following modules in year 4:

Advanced Games Design and Development

• This module extends the topics covered in the Game Design and Development module by looking at games design that uses more complex technology, or is situated in novel contexts. Students will get further practical experience of developing games within an i...

Advanced Machine Learning

• To introduce key concepts in pattern recognition and machine learning; including specific algorithms for classification, regression, clustering and probabilistic modeling. - To give a broad view of the general issues arising in the application of algor...

Advanced Programming Language Concepts

• This module covers concepts in programming languages that go beyond those typically seen or are new to mainstream languages. The goal is to encourage students to look beyond traditional programming practice by introducing new tools and techniques inspired...

Algorithmic Game Theory

• This module: - Introduces the students to the key issues of interaction of multiple self-interested parties (a.k.a. agents) and gives a broad survey of topics at the interface of theoretical computer science and game theory dealing with such interactions...

Automated Software Verification

• This module aims to train students in both the principles and the practice of software verification. A range of verification approaches, including both testing and formal verification, will be covered. The use of logic as a specification language for prog...

Bayesian, Active & Reinforcement Learning
Biologically Inspired Robotics

• This module lies at the intersection of robotics and biology. Through the abstraction of design principles from biological systems, it is possible to develop a range of core competences, including mechatronic systems, sensor and actuator technologies. By ...

Biometrics

• Biometrics is about how we can recognise people automatically, by personal characteristic. We all have fingerprints and faces - and they are unique. We have to sense the information, process it and then deliver an assessment of the identity associated wit...

Computational Finance

• Financial markets form the source of a vast number of challenging computational problems. These are not only intellectually challenging from the point of view of computational modelling, but the financial sector is also an employer of a significant fracti...

Cryptography

• This module covers the mathematics, techniques, and applications of modern cryptography. We will look at the history of code making and code breaking, and draw lessons for the future from the mistakes and successes of the past. We will also give a gentle ...

Data Mining

• The challenge of data mining is to transform raw data into useful information and actionable knowledge. Data mining is the computational process of discovering patterns in data sets involving methods at the intersection of artificial intelligence, machine...

Data Visualisation

• Welcome to the Data Visualisation module! In this course, you would learn about the terminology, concepts and techniques behind visualising data, and will get to use a range of tools to get experience of creating visual representations of data. You will g...

Deep Learning Technologies

• Deep learning has revolutionised numerous fields in recent years. We've witnessed improvements in everything from computer vision through speech analysis to natural language processing as a result of the advent of massively parallel compute coupled with l...

Differentiable Programming and Deep Learning

• Deep learning and differentiable programming has revolutionised numerous fields in recent years. We've witnessed improvements in everything from computer vision through speech analysis to natural language processing as a result of the advent of cheap GPGP...

Digital Forensics

• We will study the tools and techniques used in digital forensics and its relevance to incident responses and criminal investigations. This will include: Network Traffic, Disk and Memory Forensics, Hardware Architectures, Forensics frameworks, Attributions...

Evolution of Complexity

• Evolution by natural selection has created amazingly complex and sophisticated solutions to some very difficult problems - how exactly does it achieve this, and how can we harness this capability for engineering artificial systems and computational proble...

Image Processing

• This module is useful to introduce: - Image processing and its relation to signal processing. - Image transformations for filtering, coding and etc. - Histogram processing algorithms to enhance image qualities and visibility. - Theories analysing and ...

Individual Research Project

• The Individual Research Project is a 7.5 ECTS credit masters level module undertaken by independent study that allows students to demonstrate mastery of an advanced aspect of their discipline, including critical evaluation of current research and research...

Intelligent Agents

• This module gives a broad introduction to the new and rapidly expanding field of agent-based computing. It introduces the key concepts and models of the field, dealing both with the individual agents and with their interactions. Particular emphasis is pla...

Knowledge Graphs for AI Systems

• The last decade and a half have seen the Web move away from a purely document-centric information system to one in which hypertext techniques are applied to the sort of data found in databases; the term “Semantic Web” is used to refer to this Web of linke...

Optimisation for Machine Learning

• This module is about the fundamentals of algorithms solving continuous optimisation problems, which involve minimising functions of multiple real-valued variables, possibly subject to restrictions, constraints, and nondifferentiable regularisations on the...

Probability in Computing

• Computer Science has evolved significantly over the past decades, and various subfields require a strong foundation in probability. Such fondation is important in studying randomized algorithms, algorithm analysis, approximation algorithms and artificial ...

Simulation Modelling for Computer Science

• Simulation modelling plays an increasingly significant role across modern science and engineering, with the development of computational models becoming established practice in industry, consulting, and policy formulation. Computer scientists are often em...

Social Media and Network Science

• The second generation of web sites that came along in the mid 2000's included many of the social media sites that are now household names (YouTube, Flickr, Wikipedia, Facebook, Blogger, Twitter, etc.) These sites (known at the time as Web 2.0) focused on ...

Software Project Management and Secure Development

• This module prepares students to develop an understanding of the critical issues and application of software project management. It introduces the students to the tools, techniques and body of knowledge involved in each stage of the project management lif...

Software Security

• This module focuses on both theoretical and practical perspectives in the security of software and software systems, by exploring software analysis and reverse engineering. 
The aims of the module at a high level are to: 
- Explore common threats to ...

Wireless Networks

• This course is intended to give students an outline of how wireless communication and computer networks work "above the physical layer". This includes the interoperability of wireless networks such as WiMax/GPRS and WiFi to provide WiFi on trains etc. How.

The learning activities for this course include the following:

• Lectures
• Classes and tutorials
• coursework
• Individual and group projects
• Independent learning (studying on your own)

Careers

• Most of our graduates go straight into computer science jobs in high-tech companies. Roles include: software engineer, app developer, web developer, and systems analyst. This master's course is also a great foundation for further study at PhD level.
• Industry and government have an acute need for cyber security in a great variety of applications. You could become part of a team writing next-generation secure operating and communication systems, working to block the spread of malware, developing new defensive programming techniques, or work in government to protect national infrastructures or cyber defences.
• Through our Cyber Security Academy you’ll also have regular contact with companies at the forefront of cyber security. Summer internships will help you build a strong professional profile, and set you up well for a cyber security career path.

Thanks to an extensive combination of networks, mentors, societies and our own on-campus startup incubator, we also support aspiring entrepreneurs looking to build their enterprise skills.

Our Computer Science graduates have secured roles at organisations including:

• Apple
• Microsoft
• Cisco
• Audi
• Google
• IBM

Roles include:

• Cyber security analyst
• Information security manager
• Network security analyst
• Penetration tester
• Cyber security consultant