IY4S734 - Applied Artificial Intelligence in Cyber Security  01 Jul 2022 - 31 Aug 2028 | Version 1

Associated Module Information

Module Code: IY4S734
Module Title: Applied Artificial Intelligence in Cyber Security 
Faculty: Faculty of Computing, Engineering and Science
Faculty Group: Cyber Security
Faculty Sub Group: Cyber Security
Module Leader: Muhammad Awais
Module Team: Sharan Johnstone, Rachael Medhurst, Christopher Tubb, Andrew Bellamy, Madhu Khurana, Joshua Richards, Peter Eden, Richard Ward, Beth Jenkins, Arun Kumar, Mamoun Qasem, Nisha Rawindaran
First Intended Intake: SEP 2022 Final Year of Intake:
Date Closed:
Credit Value: 20 Credit Level: 7
Language: English
Percentage of Module Taught in Welsh: 0
Equivalent Module:
HECOS codes: 100376 - computer and information security
HECOS Code Weighting: 100

Document Version Information

Version 1
Valid From 01 Jul 2022
Valid To 31 Aug 2028

Module Aims

The aim is to explore core concepts underpinning applied artificial intelligence in cyber security. The module will cover different AI sub-domains to solve real-world cyber security problems.

Content Summary

  • Programming fundamentals
  • AI algorithms in cyber security
  • Detecting email cyber security threats with AI
  • Malware threat detection
  • Securing users authentication
  • Automatic intrusion detection
  • Securing and attacking data with machine learning
  • Human aspects and adversarial behaviours in AI-driven cyber security

Learning and Teaching Methods

Activity Type Hours
Lecture 12
Tutorial 12
Practical classes and workshops 24
Independent Study 78
Directed Study 48
Formative Assessment - Scheduled 2
Interdisciplinary work 12
Problem / challenge based learning 12
Total Hours Selected 200

Learning Outcomes

# Learning Outcome
LO1 To demonstrate deep applied understanding of several advanced and research-informed Artificial Intelligence subject areas, covering diverse Artificial Intelligence approaches and applications to cyber security.
LO2 To demonstrate applied understanding of how AI and cyber security can be employed to enhance certain aspects of real-world applications

Module Requisites

N/A

Assessment Criteria

Assessment Category Assessment Type Description Duration Word Count Weight (%) Best of? Pass Mark
Asynchronous Assessment Practical Coursework 1 (Asynch) A practical coursework that draws on knowledge from the module and the course. 0 2500 100 No 40

Assessment Matrix

Assessment Type Learning Outcomes
LO1 LO2
Practical Coursework 1 (Asynch) ✔ ✔

Reading List

Das, A (2021) Practical AI for Cybersecurity, CRC Press.

Dasgupta, J. et al (2021). Adversary-Aware Learning Techniques and Trends in Cybersecurity, Springer.

Clarke, B. et all. (2020). Human Aspects of Information Security and Assurance, Springer.

Gupta, B. et al. (2019 Machine Learning for Computer and Cyber Security - Principle, Algorithms, and Practices, CRC Press, 2019.

Parisi, A. (2019) Hands-On Artificial Intelligence for Cybersecurity - Implement smart AI systems for preventing cyber-attacks and detecting threats and network anomalies, Packt Publishing Priyadarshini, I. et al. (2022) Artificial Intelligence and Cybersecurity - Advances and Innovations, CRC Press.