Cyber Security Analytics (2023)
1. Programme Title:Cyber Security Analytics |
NQF Level: |
7 |
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2. Description of the Programme (as in the Business Approval Form) |
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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 |
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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 |
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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.
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5. Programme Modules |
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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.
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Stage 1
Code | Title | Credits | Compulsory | NonCondonable |
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CYBER MODULES (Select 30 credits) | ||||
ECMM462 | Fundamentals of Security | 15 | Yes | Yes |
ECMM463 | Building Secure and Trustworthy Systems | 15 | Yes | No |
DATA SCIENCE / ANALYTICS MODULES (Select 30 credits) | ||||
ECMM443 | Introduction to Data Science | 15 | Yes | Yes |
ECMM444 | Fundamentals of Data Science | 15 | Yes | No |
PROJECT | ||||
ECMM465 | Cyber Security Analytics Research Project | 60 | Yes | Yes |
CYBER MODULES (Select 30 credits) | ||||
ECMM464 | Security Assessment and Validation | 15 | No | No |
LAWM116 | The International Law of Cyber Operations | 30 | No | No |
LAWM129 | Human Rights and Modern Technologies | 30 | No | No |
BEE3109 | Bitcoin, Money and Trust | 15 | No | No |
SOCM033 | Data Governance and Ethics | 15 | No | No |
DATA SCIENCE / ANALYTICS MODULES (Select 30 credits) | ||||
COMM511 | Statistical Data Modelling | 15 | No | No |
ECMM422 | Machine Learning | 15 | No | No |
ECMM423 | Evolutionary Computation & Optimisation | 15 | No | No |
ECMM445 | Learning From Data | 15 | No | No |
ECMM450 | Stochastic Processes | 15 | No | No |
ECMM461 | High Performance Computing | 15 | No | No |
MTHM508 | Bayesian Philosophy and Methods in Data Science | 15 | No | No |
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 |
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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 ActivitiesLectures, 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.
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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 ActivitiesLectures, 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.
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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 ActivitiesLectures, 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 MethodsThe 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 |
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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 |
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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.
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10. Admission Criteria |
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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 |
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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 |
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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 | |
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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 | February 8th 2023 | Last Date of Revision: | April 27th 2023 |
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