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 Manley, Christopher Tubb, Andrew Bellamy, Madhu Khurana, Emma Derbi, Joshua Richards, Peter Eden, Richard Ward, Beth Jenkins, Arun Kumar, Mamoun Qasem, Nisha Rawindaran, Chelsea Cooper, Muhammad Awais | ||
| 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) | ✔ | ✔ | |