Security Analytics (COMP90073)
Graduate courseworkPoints: 12.5On Campus (Parkville)
About this subject
Contact information
Semester 2
Dr Sarah Monazam Erfani
Overview
| Availability | Semester 2 |
|---|---|
| Fees | Look up fees |
Aims
As we become more dependent on networks in every aspect of our lives the task of protecting those networks becomes harder. The sheer quantity of data and sophistication of the attacks is rapidly making manual analysis infeasible. Security Analytics will examine how we can automate the analysis of such data to better detect and predict security incidents and vulnerabilities within our networks and organisations.
Indicative Content
The subject will first introduce the types of data sources that are relevant to detecting different types of security threats in practice. Indicative examples are operating system logs, web server logs, packet traces, flow records and deep packet inspection traces. The second part of the subject will introduce methods from machine learning that are widely used for cyber security analysis. Specific unsupervised machine learning techniques will be covered in more detail, which include methods for anomaly detection, alarm correlation and intrusion detection. The third part of the subject will introduce some of the theoretical challenges and emerging issues for security analytics research, based on recent trends in the evolution of security threats.
Indicative examples of the emerging challenges and issues that will be studied are privacy‐preserving analytics, adversarial machine learning, concept drift and new applications in monitoring critical infrastructure
Intended learning outcomes
On completion of the subject, students should be able to:
- Evaluate the suitability of different types ofmonitoring data for detecting security incidents
- Describe and implement a range of pattern recognition and machine learning algorithms for use in security analytics
- Select algorithms appropriate to a given security analysis task
- Apply pattern recognition and machine learning techniques to non‐trivial security analysis tasks
- Evaluate computational techniques for security analytics to solve real‐world problems, based on their accuracy and efficiency
- Discuss theoretical challenges and emerging trends for security analytics research
Generic skills
- Ability to undertake problem identification, formulation and solution
- Ability to utilise a systems approach to complex problems
- Capacity for creativity and innovation
- Ability to communicate the results of complex analysis effectively to both technical audiences and the community at large
Last updated: 3 November 2022
Eligibility and requirements
Prerequisites
| Code | Name | Teaching period | Credit Points |
|---|---|---|---|
| COMP90049 | Knowledge Technologies |
Semester 2 (On Campus - Parkville)
Semester 1 (On Campus - Parkville)
|
12.5 |
| COMP30018 | Knowledge Technologies | No longer available | |
| COMP30027 | Machine Learning | Semester 1 (On Campus - Parkville) |
12.5 |
One of COMP30018 Knowledge Technologies, COMP90049 Knowledge Technologies, or COMP30027 Machine Learning
or entry into MC-IT 100 point program
Corequisites
None
Non-allowed subjects
None
Inherent requirements (core participation requirements)
The Master of Information Technology welcomes applications from students with disabilities. It is University and degree policy to take all reasonable steps to minimise the impact of disability upon academic study, and reasonable adjustments will be made to enhance a student’s participation in the degree.
The Master of Information Technology requires all students to enrol in subjects where they will require:
- The ability to comprehend complex theory and technology-related information
- The ability to clearly and independently communicate a knowledge and application of theory, and technology principles and practices during assessment tasks
- The ability to actively and safely contribute in IT development and management activities
Students must possess behavioural and social attributes that enable them to participate in a complex learning environment. Students are required to take responsibility for their own participation and learning. They also contribute to the learning of other students in collaborative learning environments, demonstrating interpersonal skills and an understanding of the needs of other students. Assessment may include the outcomes of tasks completed in collaboration with other students.
There may be additional inherent academic requirements for some subjects, and these requirements are listed within the description of the requirements for each of these subjects.
Students who feel their disability will impact on meeting this requirement are encouraged to discuss this matter with the relevant Subject Coordinator and the Disability Liaison Unit: http://www.services.unimelb.edu.au/disability/
Last updated: 3 November 2022
Assessment
| Description | Timing | Percentage |
|---|---|---|
Programing-based project
| Week 7 | 20% |
Programming-based project
| Week 11 | 20% |
End of semester written examination
| During the examination period | 60% |
Last updated: 3 November 2022
Dates & times
- Semester 2
Mode of delivery On Campus (Parkville) Contact hours 36 – two 1 hour lectures, and 1 workshop per week Total time commitment 200 hours Teaching period 29 July 2019 to 27 October 2019 Last self-enrol date 9 August 2019 Census date 31 August 2019 Last date to withdraw without fail 27 September 2019 Assessment period ends 22 November 2019 Semester 2 contact information
Dr Sarah Monazam Erfani
Time commitment details
200 hours
Last updated: 3 November 2022
Further information
- Texts
- Available through the Community Access Program
About the Community Access Program (CAP)
This subject is available through the Community Access Program (also called Single Subject Studies) which allows you to enrol in single subjects offered by the University of Melbourne, without the commitment required to complete a whole degree.
Please note Single Subject Studies via Community Access Program is not available to student visa holders or applicants
Entry requirements including prerequisites may apply. Please refer to the CAP applications page for further information.
- Available to Study Abroad and/or Study Exchange Students
Last updated: 3 November 2022