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Study information

Cyber Security Analytics (2024)

1. Programme Title:

Cyber Security Analytics

NQF Level:

7

2. Description of the Programme (as in the Business Approval Form)

The MSc Cyber Security Analytics is an innovative taught course that allows you to study two highly-sought-after skills: Cyber Security and Data Science. Combining these two disciplines will allow you to study challenges in our modern life from two complementary viewpoints. Completing this programme successfully will allow you to start a career in data analytics, cyber security, or in the intersection of both – e.g., using data analytics to solve cyber security challenges. The programme equips you with the necessary skills for both a career in industry (e.g., as a cyber security analyst) and in research, e.g., pursuing a PhD.

Cyber Security and Data Science are growth areas with an excellent career development potential. The University of Exeter is a world-class research active institution which regularly features in UK Top-10 and Global Top-100 rankings.

3. Educational Aims of the Programme

The MSc Cyber Security Analytics will provide outstanding training in cyber security and data science. The course content covers the fundamental mathematical and computational techniques underpinning both data science and cyber security. Furthermore, the course will apply these foundational concepts, e.g., using machine learning, mathematical modelling, offensive and defensive security techniques, to applications in data science and cyber security.  The research project will allow students to explore the intersection of data science and cyber security.

Content will be delivered through a combination of lectures, workshops, individual self-study, and group work on Exeter’s Streatham campus.

4. Programme Structure

The MSc Cyber Security Analytics programme is a one-year (full-time) or two year (part-time) programme of study at Regulated Qualifications Framework (RQF) Level 7 (as confirmed against the FHEQ). The programme is divided into units of study called ‘modules’ which are assigned a number of ‘credits’. The credit rating of a module is proportional to the total workload, with 1 credit being nominally equivalent to 10 hours of work. The programme comprises 180 credits in total.

Exit Awards

If you do not complete the programme, you may be able to exit with a lower qualification.

  • Postgraduate Diploma: At least 120 credits of which 90 or more must be at RQF Level 7.
  • Postgraduate Certificate: At least 60 credits of which 45 or more must be at RQF Level 7.

5. Programme Modules

The following tables describe the programme and constituent modules. Constituent modules may be updated, deleted or replaced as a consequence of the annual review of this programme. Details of the modules currently offered may be obtained from the College website:

http://intranet.exeter.ac.uk/emps/studentinfo/subjects/computerscience/modules/

Not all modules will be available every year, and new modules may be made available from time to time.

 

Stage 1

Code Title Credits Compulsory NonCondonable
CYBER MODULES (Select 30 credits)
ECMM462Fundamentals of Security15YesNo
ECMM463Building Secure and Trustworthy Systems15YesNo
DATA SCIENCE / ANALYTICS MODULES (Select 30 credits)
ECMM443Introduction to Data Science15YesNo
ECMM444Fundamentals of Data Science15YesNo
PROJECT
ECMM465Cyber Security Analytics Research Project60YesYes
CYBER MODULES (Select 30 credits)
ECMM464Security Assessment and Validation15NoNo
LAWM116The International Law of Cyber Operations30NoNo
LAWM129Human Rights and Modern Technologies30NoNo
BEE3109Bitcoin, Money and Trust15NoNo
SOCM033Data Governance and Ethics15NoNo
DATA SCIENCE / ANALYTICS MODULES (Select 30 credits)
COMM511Statistical Data Modelling15NoNo
ECMM422Machine Learning15NoNo
ECMM423Evolutionary Computation & Optimisation15NoNo
ECMM445Learning From Data15NoNo
ECMM450Stochastic Processes15NoNo
ECMM461High Performance Computing 15NoNo
MTHM508Bayesian Philosophy and Methods in Data Science15NoNo

Part time students will follow:

  • Year 1: You must complete at least 4 modules (60 credits) which must include ECMM443 Introduction to Data Science, ECMM462 Fundamentals of Security, and ECMM444 Fundamentals of Data Science.
  • Year 2: You must complete at least 4 modules (60 credits) which must include ECMM463 Building Secure and Trustworthy Systems (if not already taken in year 1) and ECMM465 Cyber Security Analytics Research Project

6. Programme Outcomes Linked to Teaching, Learning & Assessment Methods

On successfully completing the programme you will be able to: Intended Learning Outcomes (ILOs) will be accommodated & facilitated by the following learning & teaching and evidenced by the following assessment methods:

A Specialised Subject Skills & Knowledge

 
1. Demonstrate knowledge and be able to use methods for machine learning to find patterns and relationships in complex datasets.
 
2. Demonstrate the knowledge and be able to assess the threats and security risks of modern ICT systems.
 
3. Demonstrate the knowledge and be able to build secure and trustworthy ICT systems.
 
4. Demonstrate knowledge and be able to use methods for statistical inference and data modelling.
 
5. Show awareness of the social context of both cyber security and data science, including data governance, legal requirements, and ethical considerations.
 
6. Show awareness of the organisational context of both cyber security and data science, including the role and applications of both cyber security data science to business practices.
 
7. Apply computational methods for analysis of large and complex datasets, including data generated by security analyses.
 

Learning & Teaching Activities

Lectures, workshops, seminars, online materials and formal training. Each module also has core and supplementary texts, or material recommended by module deliverers, which provide in-depth coverage of the subject and go beyond the lectures.

Assessment Methods

The assessment strategy for each module is explicitly stated in the full module description given to students. Group and team skills are addressed within modules dealing with specialist and advanced skills.
 
Assessment methods will include essays, technical reports, closed book tests, practical exercises in programming, program and data analysis, project work, and individual and group presentations.
 

B Academic Discipline Core Skills & Knowledge

8. Critically analyse and interpret relevant academic and technical literature.
 
9. Demonstrate competence in underpinning mathematical and computational techniques, including linear algebra, probability, logics, calculus, programming and programming tools, and security scanning and testing tools.
 
10. Effectively handle large and complex datasets and prepare them for analysis.
 
11. Use appropriate methods for data visualisation and presentation of data.
 
12. Use the appropriate methods and visualisations for communicating & presenting security critical data and information.
 
13. Appreciate the basic legal and regulatory requirements for data privacy, security, ethical use of data, and data governance.
 

Learning & Teaching Activities

Lectures, workshops, seminars, online materials and formal training. Each module also has core and supplementary texts, or material recommended by module deliverers, which provide in-depth coverage of the subject and go beyond the lectures.

Assessment Methods

The assessment strategy for each module is explicitly stated in the full module description given to students. Group and team skills are addressed within modules dealing with specialist and advanced skills.
 
Assessment methods will include essays, technical reports, closed book tests, practical exercises in programming, program and data analysis, project work, and individual and group presentations.
 

C Personal / Transferable / Employment Skills & Knowledge

14. Effectively communicate methods and results based on a comprehensive analysis in both written reports and oral presentations.
 
15. Demonstrate awareness of tools and technologies relevant to data science.
 
16. Demonstrate awareness of the need for cyber security, data security, and privacy.
 
17. Be able to assess the threats and risks of systems or processes and to plan and implement mitigation strategies. 
 
18. Design and manage a small research from initiation to final report.
 
19. Work effectively independently or in a team.
 

Learning & Teaching Activities

Lectures, workshops, seminars, online materials and formal training. Each module also has core and supplementary texts, or material recommended by module deliverers, which provide in-depth coverage of the subject and go beyond the lectures.

Assessment Methods

The assessment strategy for each module is explicitly stated in the full module description given to students. Group and team skills are addressed within modules dealing with specialist and advanced skills.

Assessment methods will include essays, technical reports, closed book tests, practical exercises in programming, program and data analysis, project work, and individual and group presentations.

7. Programme Regulations

Full details of assessment regulations for all taught programmes can be found in the TQA Manual, specifically in the Credit and Qualifications Framework, and the Assessment, Progression and Awarding: Taught Programmes Handbook.

Additional information, including Generic Marking Criteria, can be found in the Learning and Teaching Support Handbook

8. College Support for Students and Students' Learning

In accordance with University policy, a system of Personal Tutors is in place for all students on this programme. A University-wide statement on such provision is included in the University's TQA Manual. As a student enrolled on this programme, you will receive the personal and academic support of the Programme Coordinator and will have regular scheduled meetings with your Personal Tutor; you may request additional meetings as and when required. The role of personal tutors is to provide you with advice and support for the duration of the programme and extends to providing you with details of how to obtain support and guidance on personal difficulties, such as accommodation, financial difficulties and sickness. You can also make an appointment to see individual teaching staff.

Information Technology (IT) Services provide a wide range of services throughout the Exeter campuses including open access computer rooms, some of which are available 24 hours, 7 days a week. Help may be obtained through the Helpdesk, and most study bedrooms in halls and flats are linked to the University's campus network.

Additionally, the Faculty has its own dedicated IT support staff, helpdesk and computer facilities which are linked to the wider network, but which also provide access to some specialised software packages. Email is an important channel of communication between staff and students in the Faculty and an extensive range of web-based information (see https://intranet.exeter.ac.uk/emps/) is maintained for the use of students, including a comprehensive and annually revised student handbook.

The Harrison Learning Resource Centre is generally open during building open hours. The Centre is available for quiet study, with four separate rooms that can be booked for meetings and group work. Amongst its facilities, the Learning Resource Centre has a number of desks, four meeting rooms with large LCD screens, and free use of a photocopier. Also available are core set texts from your module reading lists, and undergraduate and MSc projects from the past two years.

Online Module study resources provide materials for modules that you are registered for, in addition to some useful subject and IT resources. Generic study support resources, library and research skills, past exam papers, and the 'Academic Honesty and Plagiarism' module are also available through the student portal (http://vle.exeter.ac.uk).

Student/Staff Liaison Committee enables students & staff to jointly participate in the management and review of the teaching and learning provision.

 

10. Admission Criteria

Undergraduate applicants must satisfy the Undergraduate Admissions Policy of the University of Exeter.

Postgraduate applicants must satisfy the Postgraduate Admissions Policy of the University of Exeter.

Candidates will be required to have at least a 2:1 degree in a numerate subject, usually Computer Science or a closely related discipline, and must be able to show evidence of good programming and software development ability in recognised modern computer languages. 

Candidates may be interviewed (e.g., via teleconference) to assess their programming ability and suitability for the course.

11. Regulation of Assessment and Academic Standards

Each academic programme in the University is subject to an agreed Faculty assessment and marking strategy, underpinned by institution-wide assessment procedures.

The security of assessment and academic standards is further supported through the appointment of External Examiners for each programme. External Examiners have access to draft papers, course work and examination scripts. They are required to attend the Board of Examiners and to provide an annual report. Annual External Examiner reports are monitored at both Faculty and University level. Their responsibilities are described in the University's code of practice. See the University's TQA Manual for details.

12. Indicators of Quality and Standards

Certain programmes are subject to accreditation and/or review by professional and statutory regulatory bodies (PSRBs). This programme is not subject to any such requirements. 

14 Awarding Institution University of Exeter
15 Lead College / Teaching Institution College of Engineering, Mathematics and Physical Sciences
16 Partner College / Institution University of Exeter Business School; College of Social Science and International Study
17 Programme accredited/validated by N/A
18 Final Award(s) MSc
19 UCAS Code (UG programmes) msccyber
20 NQF Level of Final Awards(s): 7
21 Credit (CATS and ECTS) 180 credits (90 ECTS)
22 QAA Subject Benchmarking Group (UG and PGT programmes) Computing (Master’s)
23 Origin Date March 15th 2024 Last Date of Revision: April 29th 2024