Loughborough University
Leicestershire, UK
LE11 3TU
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Loughborough University

Programme Specifications

Programme Specification

MSc Cyber Security and Big Data

Academic Year: 2019/20

This specification provides a concise summary of the main features of the programme and the learning outcomes that a typical student might reasonably be expected to achieve and demonstrate if full advantage is taken of the learning opportunities that are provided.

This specification applies to delivery of the programme in the Academic Year indicated above. Prospective students reviewing this information for a later year of study should be aware that these details are subject to change as outlined in our Terms and Conditions of Study.

This specification should be read in conjunction with:

  • Summary
  • Aims
  • Learning outcomes
  • Structure
  • Progression & weighting

Programme summary

Awarding body/institution Loughborough University
Teaching institution (if different)
Owning school/department Loughborough University in London
Details of accreditation by a professional/statutory body
Final award MSc
Programme title Cyber Security and Big Data
Programme code LLPT06/LLPT16
Length of programme Full-time: one year; Part-time: typically 2yrs but up to 4 years. Consult the programme director for advice.
UCAS code N/a
Admissions criteria

MSc Full time: http://www.lboro.ac.uk/LLPT06

MSc Part time: http://www.lboro.ac.uk/LLPT16

Date at which the programme specification was published Thu, 18 Jul 2019 13:29:37 BST

1. Programme Aims

This course aims to:

  • Provide students with a comprehensive understanding of the challenges in cyber security and big data faced by industry and society, and will help them to develop the necessary skills to address those challenges in the most effective way

  • Utilise both cyber security and big data analytics techniques to analyse and evaluate problems and respond to challenges with practical applications in real time

  • Build students’ knowledge and develop expertise in network security and cryptography, including big data analytics to combat malicious activities and to detect anomalies in the network

  • Provide individuals and teams with employment skills essential to the cyber security and big data industries and related businesses, such as IT, e-commerce, and governmental organisations using action-based learning

2. Relevant subject benchmark statements and other external reference points used to inform programme outcomes:

  • UK Quality Code for Higher Education, The Quality Assurance Agency for Higher Education, April 2012, especially Part A: Setting and maintaining academic standards:
    • The Frameworks for Higher Education Qualifications in England, Wales and Northern Ireland (FHEQ), the QAA, August 2008
    • Master’s Degree Characteristics, the QAA, March 2010
    • The Higher Education Credit Framework for England, the QAA, August 2008

  • The Quality Code, Part B: Assuring and enhancing academic quality
    • Chapter B1: Programme Design, Development and Approval
    • Chapter B3: Learning and Teaching
    • Chapter B4: Enabling student development and achievement
    • Chapter B6: Assessment of students
  • Master’s Degree Subject Benchmark for Engineering, the QAA, 2015

  • Master’s Degree Subject Benchmark for Business and Management, the QAA, 2015

  • UK Standard for Professional Engineering Competence: The Accreditation of Higher Education Programmes, Engineering Council UK, 3rd Edition 2014.

  • UK Standard for Professional Engineering Competence: Engineering Technician, Incorporated Engineer and Chartered Engineer Standard, Engineering Council UK, 2013.

  • Proposals for National Arrangements for the Use of Academic Credit in Higher Education in England: Final Report of the Burgess Group, December 2006.
  • The Northern Ireland Credit Accumulation and Transfer System (NICATS): Principles and Guidelines, 2002.

3. Programme Learning Outcomes

3.1 Knowledge and Understanding

On successful completion of this programme, students should be able to demonstrate a thorough knowledge and systematic understanding of: 

  • K1 cyber security and big data principles, practices, tools and techniques, and their application
  • K2 network security and cryptography, including big data analytics
  • K3 Internet, communication networks, and clouds
  • K4 the integration of security and privacy into design of the Internet, communication networks, big data applications and cloud architectures
  • K5 the influence of Digital Technologies on other areas through studying a complementary subject

3.2 Skills and other attributes

a. Subject-specific cognitive skills:

On successful completion of this programme, students should be able to:

  • C1 understand how to devise secure communication and data solutions
  • C2 critically evaluate how security and privacy can be made an integral part of future network and data systems
  • C3 exploit knowledge to design new cyber security tools, which interact with big data
  • C4 devise novel solutions in the design of secure communications, Internet, cloud, and data interactions
b. Subject-specific practical skills:

On successful completion of this programme, students should be able to: 

  • P1 analyse and evaluate cyber security and big data problems related to existing technologies
  • P2 understand and develop improved solutions to secure communication and big data services
  • P3 create innovative cyber security and big data analytics techniques and develop the necessary building blocks to synthesise secure communication and big data systems
  • P4 exploit their technical knowledge to create innovative cyber security and big data solutions
c. Key transferable skills:

On successful completion of this programme, students should be able to:

  • T1 Demonstrate skills in analysing information with attention to details
  • T2 Competently plan, execute and oversee technology projects to completion with skills they have acquired from the programme
  • T3 Demonstrate a high degree of subject knowledge that would support a wide research field
  • T4 Generate new ideas and concepts

4. Programme structure

 

 

Code

Title

Modular Weight

Semester

C/O

LLP008

Collaborative Project

 

15

 

1

C

LLP121

Principles of data science

 

15

1

C

LLP126~

Information Management

 

15

1

O

LLP114~

Cybersecurity and Forensics

15

1

O

 

LLP109~

Digital Application Development

15

1

O

 

LLP115

Applied Cryptography

15

2

C

 

LLP122~

 

Advanced big data analytics

15

2

O

LLP111~

Cloud applications & services

 

15

2

O

LLP103~

Media processing 

 

15

2

O

LLP108~

Internet of Things and Applications

 

15

2

O

LLP127~

 

Information Systems Security

15

2

O

LLP503

Dissertation

60

 

2

C

 ~Students must choose and complete 5 of the 8 optional modules to complete the MSc.Cyber Security and Big Data. Two of these modules must be completed in Semester 1 and 3 in Semester 2. 

  

5. Criteria for Progression and Degree Award

In order to be eligible for the award, candidates must satisfy the requirements of Regulation XXI.

All modules available in the Special Assessment Period (SAP) unless specified in the Module Specification.

6. Relative Weighting of Parts of the Programme for the Purposes of Final Degree Classification

Not Applicable.

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