Outline

Overview

The Cybersecurity project will provide students an opportunity to apply the knowledge and practise the skills acquired in the prerequisite and qualifying units, in the context of designing and building a substantial cybersecurity system in diverse application domains including life sciences. Students will need to demonstrate sensible application of cybersecurity knowledge and skills in their project including deciding on most suitable authentication protocols, cryptographic primitives, security assessment strategies, security proofs (if applicable). Working in groups for an external client combined with academic supervision, students will need to carry out the full range of activities including requirements capture, analysis and design, coding, testing and documentation. Students will use the XP methodology and make use of professional tools for the management of their project.

Unit details and rules

Academic unit	Computer Science
Credit points	6
Prerequisites ?	(COMP2017 or COMP2907) and ISYS2120 and ELEC3506
Corequisites ?	None
Prohibitions ?	INFO3600
Assumed knowledge ?	None
Available to study abroad and exchange students	Yes

Teaching staff

Coordinator	Xiu Wang, xiu.wang@sydney.edu.au

Type	Description	Weight	Due	Length
Assignment	Progressive group reports & presentation Progressive group reports & presentation	5%	Multiple weeks	Multiple weeks (W3, W5, W9, W11)
Outcomes assessed:
Small continuous assessment	Individual contribution reports Individual contribution reports (W5, W9, W11)	5%	Progressive	multiple weeks
Outcomes assessed:
Assignment	Assignment 1 Individual Contribution Report (W6)	10%	Week 05 Due date: 05 Sep 2022 at 23:59	N/A
Outcomes assessed:
Presentation	First project demo and presentation 1st presentation and demo (group work)	5%	Week 06	in-tutorial
Outcomes assessed:
Assignment	First project report (group) First project report (group)	10%	Week 06	multiple weeks
Outcomes assessed:
Presentation	First client deployment deploy & demo first product at client site.	5%	Week 07	multiple weeks
Outcomes assessed:
Presentation	Final project demo and presentation Final project demo and presentation (group work)	10%	Week 12	in-tutorial
Outcomes assessed:
Presentation	Final product delivery to client Complete product delivery & demo at the client site.	10%	Week 12	multiple weeks
Outcomes assessed:
Assignment	Final project report (group) Final project report (group)	20%	Week 12	Multiple weeks
Outcomes assessed:
Assignment	Final Assignment Individual Contribution Report (W13)	20%	Week 13 Due date: 31 Oct 2022 at 23:59	N/A
Outcomes assessed:
= group assignment ?

Assessment summary

1 . First project demo and presentation: present the work done to understand the client’s requirements and complete the first set of requirements. This should be a major release, with some working and useful outcomes for the client and some parts presented in proposed form such as storyboards.
2 . First project report (group): reports the work done to understand the client’s requirements and complete the first set of requirements. It should also report on the group work and processes followed, systems and software tools used, and client interaction.
3. Individual contribution reports (5 individual reports)*: focuses on the individual contributions to the group project work completed by each student. All students will be required to give some feedback about the other team members of their group, in order to validate the individual reports as well.
4. First client deployment: first set of test and implemented requirements must be deployed at client site. Students need to demonstrate that that the group has had a professional approach to the project deployment and worked to ensure that the client will be satisfied. The client will be consulted to ratify the deployment.
5. Final delivery to client: final product and relevant documentation delivered to the client. This includes all the sources, necessary technical documentation and any product or documentation that the client required at the start of the project.
6. Final project demo and presentation: must provide a convincing demonstration that the group has performed a substantial amount of work that meets client needs and have had a professional approach to achieving that.
7. Final project report (group) : this report discusses important aspects including technical details of the final delivered product, how it met client’s needs, approach followed to interact with the client, group’s discipline knowledge and skills used to tackle problems, the quality of the processes followed and the effectiveness of group management processes.

* The marks obtained from this assessemnt will be used to scale the total marks obtained from the group assessments as follows:
final mark = total individual contribution marks + (total marks obtained from group assessments * percentage of individual contribution marks)

Detailed information for each assessment will be communicated on Canvas through the tutorials and Ed discussion forum.

Assessment criteria

The University awards common result grades, set out in the Coursework Policy 2014 (Schedule 1).
As a general guide, a high distinction indicates work of an exceptional standard, a distinction a very high standard, a credit a good standard, and a pass an acceptable standard.

.
It is a policy of the School of Computer Science that in order to pass this unit, a student must achieve at least 40% in the written examination. For subjects without a final exam, the 40% minimum requirement applies to the corresponding major assessment component specified by the lecturer. A student must also achieve an overall final mark of 50 or more. Any student not meeting these requirements may be given a maximum final mark of no more than 45 regardless of their average.

Result name	Mark range	Description
High distinction	85-100
Distinction	75-84
Credit	65-74
Pass	50-64
Fail	0-49	When you don’t meet the learning outcomes of the unit to a satisfactory standard.

For more information see guide to grades.

Late submission

In accordance with University policy, these penalties apply when written work is submitted after 11:59pm on the due date:

Deduction of 5% of the maximum mark for each calendar day after the due date.
After ten calendar days late, a mark of zero will be awarded.

This unit has an exception to the standard University policy or supplementary information has been provided by the unit coordinator. This information is displayed below:

In accordance with university polcies

Academic integrity

The Current Student website provides information on academic integrity and the resources available to all students. The University expects students and staff to act ethically and honestly and will treat all allegations of academic integrity breaches seriously.

We use similarity detection software to detect potential instances of plagiarism or other forms of academic integrity breach. If such matches indicate evidence of plagiarism or other forms of academic integrity breaches, your teacher is required to report your work for further investigation.

Use of generative artificial intelligence (AI) and automated writing tools

You may only use generative AI and automated writing tools in assessment tasks if you are permitted to by your unit coordinator. If you do use these tools, you must acknowledge this in your work, either in a footnote or an acknowledgement section. The assessment instructions or unit outline will give guidance of the types of tools that are permitted and how the tools should be used.

Your final submitted work must be your own, original work. You must acknowledge any use of generative AI tools that have been used in the assessment, and any material that forms part of your submission must be appropriately referenced. For guidance on how to acknowledge the use of AI, please refer to the AI in Education Canvas site.

The unapproved use of these tools or unacknowledged use will be considered a breach of the Academic Integrity Policy and penalties may apply.

Studiosity is permitted unless otherwise indicated by the unit coordinator. The use of this service must be acknowledged in your submission as detailed on the Learning Hub’s Canvas page.

Outside assessment tasks, generative AI tools may be used to support your learning. The AI in Education Canvas site contains a number of productive ways that students are using AI to improve their learning.

Learning support

Simple extensions

If you encounter a problem submitting your work on time, you may be able to apply for an extension of five calendar days through a simple extension.  The application process will be different depending on the type of assessment and extensions cannot be granted for some assessment types like exams.

Special consideration

If exceptional circumstances mean you can’t complete an assessment, you need consideration for a longer period of time, or if you have essential commitments which impact your performance in an assessment, you may be eligible for special consideration or special arrangements.

Special consideration applications will not be affected by a simple extension application.

Using AI responsibly

Co-created with students, AI in Education includes lots of helpful examples of how students use generative AI tools to support their learning. It explains how generative AI works, the different tools available and how to use them responsibly and productively.

Weekly schedule

WK	Topic	Learning activity
Week 01	Unit overview, team formation, presentation /proposals of projects offered, collection of teams preferences	Lecture (3 hr)
Week 02	1. Tutor meet all managers & tutor meets each group; 2. Group work and big 5 theory for efficient team work; 3. Group contract, XP, group management tools & first meeting with client	Project (2 hr)
Week 03	1. group progress demo and presentation; 2. discuss progress in terms of classic XP elements; 3. Tutor meet all managers & tutor meets each group; 4. progress with new /existing requirements (user stories) implementation and testing.	Project (2 hr)
Week 04	1. Workload management and awareness of teamwork; 2. Working towards first demo and report; 3. Tutor meet all managers & tutor meets each group 4. prototype implementation and testing; 5. reflection (group demo and presentation)	Project (2 hr)
Week 05	1. Continue working towards first prototype, demo and report; 2. Tutor meet all managers & tutor meets each group 3. prototype implementation and testing 4. more/refine requirements; 5. 1st Progressive Report	Project (2 hr)
Week 06	1. First presentation & demo and reports by all groups. 2. preparation for first client deployment & demos.	Project (2 hr)
Week 07	1. continue working on new user stories /requirements 2. Preparation for first client demo at client site 3. implementation of other requirements 4.Tutor meet all managers & tutor meets each group; 5. Reflection (First Presentation; First Group Project Report; First Individual Report)	Project (2 hr)
Week 08	1. progress with requirements (user stories); implements & test requirements 2. Code refactoring, more tests (user acceptance tests); 3. implementation of requirements (user stories); 4. Tutor meet all managers & tutor meets each group to discuss feedback on first reports, development progress & first client deployment follow ups.	Project (2 hr)
Week 09	1. code refactoring and progress with requirements (user stories) 2. implementation & testing of requirements (user stories) 3. Advanced testing types; 4. Tutor meet all managers & tutor meets each group to discuss development progress, client's feedback and interactions; 5. 2nd progress report submission	Project (2 hr)
Week 10	1. code refactoring and progress with requirements (user stories); implementation & testing of requirements (user stories) 2. Advanced testing types 3. Tutor meet all managers & tutor meets each group to discuss development progress 4. initial planning for final client deployment; 5. reflection (2nd progress report)	Project (2 hr)
Week 11	1. code refactoring and progress with requirements (user stories); implementation & testing of requirements (user stories) 2.Tutor meet all managers & tutor meets each group to discuss development progress 3. planning for final product delivery & demo; 4. 3rd progress report.	Project (2 hr)
Week 12	1. Final project presentation & demo (intutorial); 2.Final product delivery & demo at client site	Project (2 hr)
Week 13	1. Final Report (Individual) (wiki & Canvas) Due Monday; 2. Concluding remarks and feedback; 3. follow ups on final assessments 4. follow ups on client's final product demo and delivery 5. completion of project work and documentation where needed 7. Tutor meet all managers & tutor meets each group to discuss development progress	Project (2 hr)

Study commitment

Typically, there is a minimum expectation of 1.5-2 hours of student effort per week per credit point for units of study offered over a full semester. For a 6 credit point unit, this equates to roughly 120-150 hours of student effort in total.

Learning outcomes

Learning outcomes are what students know, understand and are able to do on completion of a unit of study. They are aligned with the University's graduate qualities and are assessed as part of the curriculum.

Outcomes
Graduate qualities

At the completion of this unit, you should be able to:

LO1. produce written reports of student's work in a style that conforms to their discipline and is appropriate for clients to check
LO2. Give an oral presentation of student’s work and its rationale to the student’s discipline
LO3. Work in a small group of students, to deliver substantial results for clients
LO4. Follow a systematic process of work, with appropriate mechanisms for dealing with risks, such as unforeseen factors and delays
LO5. Use previously unfamiliar tools and to integrate with previously unfamiliar software/systems, learning their use from examples and documentation
LO6. Work with clients to discover their needs and to demonstrate that the delivered results meet those needs
LO7. Apply discipline expertise in software engineering to solve problems and meet the needs of clients.

Graduate qualities

The graduate qualities are the qualities and skills that all University of Sydney graduates must demonstrate on successful completion of an award course. As a future Sydney graduate, the set of qualities have been designed to equip you for the contemporary world.

GQ1	Depth of disciplinary expertise Deep disciplinary expertise is the ability to integrate and rigorously apply knowledge, understanding and skills of a recognised discipline defined by scholarly activity, as well as familiarity with evolving practice of the discipline.
GQ2	Critical thinking and problem solving Critical thinking and problem solving are the questioning of ideas, evidence and assumptions in order to propose and evaluate hypotheses or alternative arguments before formulating a conclusion or a solution to an identified problem.
GQ3	Oral and written communication Effective communication, in both oral and written form, is the clear exchange of meaning in a manner that is appropriate to audience and context.
GQ4	Information and digital literacy Information and digital literacy is the ability to locate, interpret, evaluate, manage, adapt, integrate, create and convey information using appropriate resources, tools and strategies.
GQ5	Inventiveness Generating novel ideas and solutions.
GQ6	Cultural competence Cultural Competence is the ability to actively, ethically, respectfully, and successfully engage across and between cultures. In the Australian context, this includes and celebrates Aboriginal and Torres Strait Islander cultures, knowledge systems, and a mature understanding of contemporary issues.
GQ7	Interdisciplinary effectiveness Interdisciplinary effectiveness is the integration and synthesis of multiple viewpoints and practices, working effectively across disciplinary boundaries.
GQ8	Integrated professional, ethical, and personal identity An integrated professional, ethical and personal identity is understanding the interaction between one’s personal and professional selves in an ethical context.
GQ9	Influence Engaging others in a process, idea or vision.

Outcome map

Learning outcomes	Graduate qualities
Learning outcomes

Responding to student feedback

This section outlines changes made to this unit following staff and student reviews.

No changes have been made since this unit was last offered.

Disclaimer

The University reserves the right to amend units of study or no longer offer certain units, including where there are low enrolment numbers.

To help you understand common terms that we use at the University, we offer an online glossary.

Current students

Overview

Overview

Unit details and rules

Teaching staff

Assessment

Assessment

Assessment summary

Assessment criteria

Late submission

Academic integrity

Learning support

Learning support

Simple extensions

Special consideration

Using AI responsibly

Weekly schedule

Weekly schedule

Study commitment

Learning outcomes

Learning outcomes

Graduate qualities

Outcome map

Responding to student feedback

Responding to student feedback

Disclaimer

On this page

Useful links

Media

Student links

About us

Connect

Current students

CSEC3888: Cybersecurity Project

Semester 2, 2022 [Normal day] - Remote

Overview

Overview

Unit details and rules

Teaching staff

Assessment

Assessment

Assessment summary

Assessment criteria

Late submission

Academic integrity

Learning support

Learning support

Simple extensions

Special consideration

Using AI responsibly

Weekly schedule

Weekly schedule

Study commitment

Learning outcomes

Learning outcomes

Graduate qualities

Outcome map

Responding to student feedback

Responding to student feedback

Disclaimer

On this page

Useful links

Media

Student links

About us

Connect