SIT325 - Advanced Network Security
Unit details
| Year: | 2024 unit information |
|---|---|
| Enrolment modes: | Trimester 2: Burwood (Melbourne), Waurn Ponds (Geelong), Online |
| Credit point(s): | 1 |
| EFTSL value: | 0.125 |
| Unit Chair: | Trimester 2: Fariha Jaigirdar |
| Prerequisite: | SIT202 and one of SIT112, SIT215, SIT307 or SIT384 |
| Corequisite: | Nil |
| Incompatible with: | Nil |
| Typical study commitment: | Students will on average spend 150 hours over the trimester undertaking the teaching, learning and assessment activities for this unit. This will include educator guided online learning activities within the unit site. |
| Educator-facilitated (scheduled) learning activities - on-campus unit enrolment: | 1 x 3 hour seminar per week. |
| Educator-facilitated (scheduled) learning activities - online unit enrolment: | Online independent and collaborative learning including 1 x 2 hour online seminar per week, weekly meetings. |
Content
A strong understanding of networking is critical for cyber security. This unit will provide students in the network security minor the advanced understanding of networks needed for success in the field. The unit will cover a range of advanced and emerging technologies, such as Software Defined Networks, Internet of Things, and Artificial Intelligence (AI) based networking. The security of next generation of network such as 5G, 6G. etc. is not possible without AI methods. The unit will also foster the research culture to critically analyse the real-word security and privacy issues from socio-economic perspective.
| ULO | These are the Learning Outcomes (ULO) for this unit. At the completion of this unit, successful students can: | Deakin Graduate Learning Outcomes |
|---|---|---|
| ULO1 | Design a medium to large scale software-defined network (SDN) using customized topologies and assess network behaviour under different traffic conditions. | GLO1: Discipline-specific knowledge and capabilities |
| ULO2 | Design and analyse the key characteristics of SDN network using real-world network topologies. Evaluating an SDN network from DDoS attack and SDN switch table overloading attack. Analyse the bandwidth consumption, packets-drop ratio, and measure other performance metrics during attack and non-attack cases. | GLO1: Discipline-specific knowledge and capabilities |
| ULO3 | Investigate novel algorithms for packet routing, and load balancing for extremely high bandwidth networks under attack scenarios explain trade-offs for adjusting these algorithms. | GLO1: Discipline-specific knowledge and capabilities |
| ULO4 | Design an Artificial Intelligence (AI) based Intrusion Detection System for anomaly detection and foster the research culture among students to critically analyse real-world security and privacy aspects, from socio-economic perspectives. | GLO1: Discipline-specific knowledge and capabilities |
These Unit Learning Outcomes are applicable for all teaching periods throughout the year.
Assessment
| Assessment Description | Student output | Grading and weighting (% total mark for unit) | Indicative due week |
|---|---|---|---|
| Learning portfolio | Tasks include the production of a range of artefacts (code, reports, presentations etc.), along with written critique and reflection. | 100% | Week 11 |
The assessment due weeks provided may change. The Unit Chair will clarify the exact assessment requirements, including the due date, at the start of the teaching period.
Hurdle requirement
To be eligible to obtain a pass in this unit, students must meet certain milestones as part of the portfolio.
Learning Resource
The texts and reading list for the unit can be found on the University Library via the link below: SIT325 Note: Select the relevant trimester reading list. Please note that a future teaching period's reading list may not be available until a month prior to the start of that teaching period so you may wish to use the relevant trimester's prior year reading list as a guide only.
Unit Fee Information
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