MSc Cybersecurity and Artificial Intelligence

Overview

Start date: September 2018
Duration: 12 months full-time
Programme code: COMT141

Apply now

The Need for Cybersecurity

Many of our societal infrastructures have been digital for quite some time, e.g. telecoms, banking, e-commerce, and social media. The trend to increasing digitization continues apace, with areas such as health, power distribution, transport and manufacturing increasingly embracing the opportunities digitisation offers. In particular, the drive to increased automation and ‘smart’ operation inevitably means increased use of computation.

The Internet of Things, perhaps the highest profile development in computing of recent times, marks a step change in connectivity, with some estimating 50 billion devices coming on-line by 2020. There is little doubt that we are hugely dependent on interconnected devices and systems and there are many opportunities to inflict malicious damage on them. Unsurprisingly, cybersecurity problems are reported in the media everyday. Cybersecurity is one of the most pressing problems of our day and securing computational systems and infrastructures is critical for healthy operation of modern societies.

“Combining Artificial Intelligence, Machine Learning and an understanding of Cyber Security is going to be critical as Government services are digitised, and entitlement to services needs to be tightly monitored and controlled.”

John Wright, Head of Public Sector Services, IndigoBlue

Why Cybersecurity and Artificial Intelligence?

Artificial Intelligence (AI) has achieved an exceptional profile in recent years. If cybersecurity is one of the most pressing problems of our day then AI is perhaps the highest profile solution technology. Much ’smart’ infrastructure is underpinned by AI and the provision of insight via data analytics is becoming pervasive. Harnessing AI to provide more secure component and system designs and to provide insights into system operation, e.g. to detect intruders, is a natural goal.

AI underpins so much of the operation of modern day smart infrastructural and the AI algorithms and systems at the heart of such operation may themselves be maliciously attacked with great effect, e.g. the insertion of trapdoors into the neural networks that provide image recognition for automated car operation could cause catastrophic loss of life. Additionally, smart ‘attacks’ supported by AI means are now beginning to emerge; this introduces a new and worrying level of sophistication.

There is little doubt that AI will play a variety of offensive and defensive roles in the area of cybersecurity. Our MSc programme provides a grounding in cybersecurity fundamentals. It also provides a grounding in aspects of AI of significant relevance to cybersecurity, covering fundamental and widely applicable machine learning technologies, the computational support to use them, and specific data analytics technologies (text and speech processing).


Why Cybersecurtiy and Artificial Intelligence at Sheffield?

MSc Cybersecuity and AI

  • Be in demand - our course has been developed to meet acknowledged skills gaps.
  • Gain the specific skills increasingly valued by employers. Our programme has been developed with significant support from employers (who will also help to deliver the programme).
  • Access to a dedicated employability team to help increase your employment prospects.
  • Teaching informed by researchers working in relevant areas such as Cybersecurity, Machine Learning, Text and Natural Language Processing.
  • The Department of Computer Science is 5th in the UK for Research Excellence (REF 2014).

How to apply
Fees and Funding
International Students

Content

Course outline

The MSc is designed to provide you with a grounding in both Cybersecurity and Artificial Intelligence (AI) that will enable you to work at the interface of the two topics with confidence. It does so via taught modules and a research project.

There are four taught Cybersecurity modules and four in AI. These cover fundamental technologies, processes and mechanisms in each area together with specific applications.

You will learn via a range of activities that include: lectures, externally led seminars, computer lab practicals, online mini-lectures, small group work, online quizzes, and poster and podcast preparation.

Module are supported by external literature and reading around the subject is important. You are expected to study independently as well as engaging in the activities indicated above.

We teach technical fundamentals but also develop wider skills: the MSc is predominantly 'technical', but we expect you to become familiar with and understand the contextual issues (legal, ethical, sociological, political etc.) that apply to working in Cybersecurity and AI. It is a controversial area that requires you to become a responsible professional as well as a technically well-informed one.

We are supported in our delivery of the MSc by regional and national organisations with interests in Cybersecurity and AI. The MSc includes at least ten industrially or commercially led seminars, where our collaborators identify challenges and provide professional insights based on their real world experience. Some research projects may also involve our collaborators.

The eight modules are taught over two 15-week semesters, with two Cybersecurity and two AI modules in each semester. These are assessed by a variety of means, e.g., by examination, report, poster or podcast preparation, and online quizzes. Each module is worth 15 credits and make up two thirds of your final degree mark.

Successful completion of the taught modules allows you to proceed to the dissertation project. This is a challenging piece of research at the interface of Cybersecurity and AI and is worth a third of your final degree mark (and so corresponds to 60 Credits). It is assessed by a preliminary report and a final report.


Course content

Please note that the course details set out here may change before you start, particularly if you are applying significantly in advance of the course start date.

Core modules

Fundamental Security Properties and Mechanisms

This wide-ranging module covers some fundamental concepts, properties, and mechanisms in security, e.g. identity, authentication, confidentiality, privacy, anonymity, availability and integrity. Cryptographic algorithms are explored together with major attacks (using a break-understand-and-fix approach). High level security protocols are explored (passwords, graphical passwords, key distribution and authentication protocols) together with some rigorous mechanisms for reasoning about their correctness (e.g. belief logics). Other mechanisms such as biometric authentication are also covered.

Development of Secure Software

This module covers security analysis as well as the secure development of software-based systems both on an architectural as well as a system level. The main goal of this module is to teach the foundations of secure software design, secure programming, and security testing.

Cyber Threat Hunting and Digital Forensics

The module provides an in depth view of threat hunting in memory, file system and network data and an introductory analysis of malicious programs.  Practical sessions elaborate on key concepts of incident handling, cyber threat hunting and digital investigation along with detailed analysis of real-world case studies.

Security of Control and Embedded Systems

This module addresses the security of systems where sensing and control decisions must be taken in real-time. We cover systems such as autonomous vehicles, traffic control, industrial control systems (e.g. SCADA), RFID systems, and security of the Internet of Things. Since many such systems also have safety issues we consider also how safety and security issues can be considered together. Supporting technologies such as resource efficient crypto are also addressed.

Machine Learning and Adaptive Intelligence (in Python)

This module will give students a grounding in state of the art algorithms that allow computer systems to learn from data. The module will introduce statistical machine learning, probabilistic modelling and their application to describing real world phenomena.

Scalable Machine Learning

This module will focus on technologies and algorithms that can be applied to data at a very large scale (e.g. population level). From a theoretical perspective it will focus on parallelization of algorithms and algorithmic approaches such as stochastic gradient descent. There will also be a significant practical element to the module that will focus on approaches to deploying scalable ML in practice (e.g. Apache Spark).

Text Processing

This module focuses on modern quantitative techniques for text analysis and explores important models for representing and acquiring information from texts. It introduces fundamental concepts and ideas in natural language text processing, covers techniques for handling text corpora and examines representative systems that require the automated processing of large volumes of text.

Natural Language Processing

This module provides an introduction to the field of computer processing of written natural language, known as Natural Language Processing. It will cover standard theories, models and algorithms, discussing competing solutions to problems, describing example systems and applications, and highlighting areas of open research.

Dissertation project

Individual dissertation project

This is a research led project based on a topic chosen by the student. The project is completed during the summer, and each student will have a personal academic supervisor to guide them during this period, as well as an external supervisor in the case of industrially led projects. The individual project is examined by a dissertation based on the project work, together with a poster presentation, and there is scope for students to demonstrate their critical skills and topic-related knowledge to a high level. The project itself will address a topic that brings together cybersecurity and AI in some way.

Careers

Be in demand

The MSc in Cybersecurity and Artificial Intelligence will equip you with the key skills valued by employers, enabling you to progress rapidly within your chosen profession. Graduates are in demand with potential employment routes including:

  • Cybersecurity consultancy
  • Secure software and systems design, development, and consultancy
  • Industrial or commercial scientific research into cybersecurity
  • Further academic study, including PhD

What employers are saying

“We feel that NCC Group would be an ideal place for graduates of this course to begin their cybersecurity careers – the breadth of our work and client base means that there are boundless opportunities for graduates of this course.” Matt Lewis, Research Director NCC Group.

“Combining Artificial Intelligence, Machine Learning and an understanding of Cyber Security is going to be critical as Government services are digitised, and entitlement to services needs to be tightly monitored and controlled.” John Wright, Head of Public Sector Services, IndigoBlue

“The combination of cybersecurity skills with artificial intelligence is an exceptional one - combining skills in both areas should deliver graduates in very significant demand.” Derek Burton, Company Leader, Cougar Automation Ltd.

“The skills mix is very rare. Companies with access to such skills will be at a distinct commercial advantage. The application of AI as a flexible solution paradigm in cybersecurity seems a truly excellent proposition.” Steve Brown, Managing Director Highlander IT Systems

“The importance of the proposed programme and its alignment with our company's strategic goals allows me to enthusiastically support it and I look forward to a fruitful collaboration.” Paul Haimes, Vice-President, Technical Sales and Business Development PTC (UK) Limited

“Sky Betting & Gaming welcome the prospect of an MSc course presenting academically rigorous material with ready, practical applications in the enterprise.” Greg Knell, Head of Security, Sky Betting and Gaming.

"We believe this MSc programme is perfectly aligned to our requirements as an employer and also our passion for investment in the future as technologists. The mix of cybersecurity skills with artificial intelligence is highly desirable; the programme’s graduates should have excellent employment and career prospects.“ Dave Cates, Managing Director Redemption Media

We are also enthusiastically supported by Sheffield City Region and Sheffield Digital.

The above organisations have agreed to support the development of our programme in a variety of ways, including guest lectures to give an industrial or commercial viewpoint, development and delivery of taught materials, participation in project developments, sponsorship of prizes, co-definition and supervision of projects (and in some cases hosting project students on site).

Entry

Academic entry requirements

The MSc in Cybersecurity and Artificial Intelligence is designed for students with either a good (2.1) degree in computer science or other numerate discipline. Students without a degree in computer science should have significant experience in software systems development. We expect also that students will have studied mathematics to grade A at A level (or equivalent).

English Language requirements

IELTS 6.5 (with no less than 6.0 in each component)
Details of other qualifications recognised by the University of Sheffield can be found on the English language requirements webpage.
You can also compare grades for English language assessments on the English Language Teaching Centre website.

How to apply
Fees and Funding
International Students

Scholarships and funding

10% discount for Sheffield graduates

As a Sheffield graduate, you can take advantage of our Alumni Rewards which entitles you to 10% off your tuition fees.

Find out more about Postgraduate Masters Alumni Rewards.

Find out more about the University's full range of funding options.