| Unit name | Anomaly Detection |
|---|---|
| Unit code | MATHM0030 |
| Credit points | 10 |
| Level of study | M/7 |
| Teaching block(s) |
Teaching Block 1B (weeks 7 - 12) |
| Unit director | Professor. Rubin-Delanchy |
| Open unit status | Not open |
| Pre-requisites |
MATH10013 Probability and Statistics and MATH20800 Statistics 2 |
| Co-requisites |
None |
| School/department | School of Mathematics |
| Faculty | Faculty of Science |
Unit Aims
This unit aims to introduce models of normal network behaviour, anomaly detection, and the process of combining and screening anomalies over space and time.
Unit Description
It will provide the mathematical & statistical underpinnings of anomaly detection for cybersecurity data. It will cover the following topics: dynamic network models, fundamentals of hypothesis testing, combining and screening anomalies, Bayesian methods, Monte-Carlo approaches. In coursework assignments, students will use network, point process and cluster models to find anomalies in real cyber security data.
ILO1: to recognise and apply a range of models for dynamic network data, and their estimation
ILO2: to understand core anomaly detection concepts and tools, including mastering theory and interpretation of hypothesis tests, controlling false positive rates and performing meta-analysis
ILO3: to apply these anomaly detection tools to analyse real large-scale data and report the results
The unit will be taught through a combination of
90% Timed, open-book examination 10% Coursework
Raw scores on the examinations will be determined according to the marking scheme written on the examination paper. The marking scheme, indicating the maximum score per question, is a guide to the relative weighting of the questions. Raw scores are moderated as described in the Undergraduate Handbook.
If you fail this unit and are required to resit, reassessment is by a written examination in the August/September Resit and Supplementary exam period.
If this unit has a Resource List, you will normally find a link to it in the Blackboard area for the unit. Sometimes there will be a separate link for each weekly topic.
If you are unable to access a list through Blackboard, you can also find it via the Resource Lists homepage. Search for the list by the unit name or code (e.g. MATHM0030).
How much time the unit requires
Each credit equates to 10 hours of total student input. For example a 20 credit unit will take you 200 hours
of study to complete. Your total learning time is made up of contact time, directed learning tasks,
independent learning and assessment activity.
See the Faculty workload statement relating to this unit for more information.
Assessment
The Board of Examiners will consider all cases where students have failed or not completed the assessments required for credit.
The Board considers each student's outcomes across all the units which contribute to each year's programme of study. If you have self-certificated your absence from an
assessment, you will normally be required to complete it the next time it runs (this is usually in the next assessment period).
The Board of Examiners will take into account any extenuating circumstances and operates
within the Regulations and Code of Practice for Taught Programmes.
