Outline

Overview

This unit provides an integrated treatment of two critical topics for a computing professional: human computer interaction (HCI) and security. The techniques and core ideas of HCI will be studied with a particular focus on examples and case studies related to security. This unit builds the students' awareness of the deep challenges in creating computing systems that can meet people's needs for both HCI and security. It will develop basic skills to evaluate systems for their effectiveness in meeting people's needs within the contexts of their use, building knowledge of common mistakes in systems, and approaches to avoid those mistakes.

Unit details and rules

Academic unit	Computer Science
Credit points	6
Prerequisites ?	(INFO1103 OR INFO1105 OR INFO1905 OR INFO1113) AND (INFO1111 OR INFO1711 OR ENGG1111 OR ENGD1000 OF ENGG1805)
Corequisites ?	None
Prohibitions ?	None
Assumed knowledge ?	None
Available to study abroad and exchange students	Yes

Teaching staff

Coordinator	Sue Chng, sue.chng@sydney.edu.au
Lecturer(s)	Sue Chng, sue.chng@sydney.edu.au
Lecturer(s)	Alan Robertson, alan.robertson@sydney.edu.au

Type	Description	Weight	Due	Length
Final exam	Take-home Exam plus Viva Voce Written and non-written elements.	50%	-	2.5+ hours
Outcomes assessed:
Assignment	Mini-assignments Reflective essays and mini-quizzes.	10%	Multiple weeks	Depends
Outcomes assessed:
Assignment	Assignment 1 Written and non-written elements	20%	Week 07	5000 words/ 10 minutes
Outcomes assessed:
Assignment	Assignment 2 Written	10%	Week 10	2500 words
Outcomes assessed:
Assignment	Assignment 3 Written and non-written elements.	10%	Week 13	12 minutes
Outcomes assessed:
= group assignment ?

Assessment summary

Detailed information for each assessment can be found on Canvas.

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.

Result name	Mark range	Description
High distinction	85 - 100	Awarded when you demonstrate the learning outcomes for the unit at an exceptional standard, as defined by grade descriptors or exemplars outlined by your faculty or school.
Distinction	75 - 84	Awarded when you demonstrate the learning outcomes for the unit at a very high standard, as defined by grade descriptors or exemplars outlined by your faculty or school.
Credit	65 - 74	Awarded when you demonstrate the learning outcomes for the unit at a good standard, as defined by grade descriptors or exemplars outlined by your faculty or school.
Pass	50 - 64	Awarded when you demonstrate the learning outcomes for the unit at an acceptable standard, as defined by grade descriptors or exemplars outlined by your faculty or school.
Fail	0 - 49	When you don’t meet the learning outcomes of the unit to a satisfactory standard.

Minimum Pass Requirement:

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.

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.

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	Introduction and the usability context: introduction to the unit and to the challenges in enabling the use of system features by humans.	Lecture and tutorial (4 hr)
Week 02	Users I: Investigating users and their importance in understanding usability	Lecture and tutorial (4 hr)
Week 03	Usability in Design and Implementation: How to perform the processes of usability engineering in the context of software and system engineering	Lecture and tutorial (4 hr)
Week 04	IA and Navigation Design.	Lecture and tutorial (4 hr)
Week 05	User II. Human factors - individual physiology, cognition and broader psychology, social and organisational structures.	Online class (4 hr)
Week 06	The usability compromise?: the challenges the competing interests of usability and security place on system design, and techniques to achieve both in the same system	Online class (4 hr)
Week 07	Security terminology, identification and authentication	Online class (4 hr)
Week 08	Web and database security	Online class (4 hr)
Week 09	Cryptography and network security	Online class (4 hr)
Week 10	Software and system security	Online class (4 hr)
Week 11	Physical and operational security	Online class (4 hr)
Week 12	Privacy, legal and ethical issues	Online class (4 hr)
Week 13	Review and revision	Online class (4 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. work effectively in a team
LO2. understand the balance between risk, achieved security, and cost; experience with threat modelling and risk analysis as tools to choose this balance for a given system
LO3. produce written reports that evaluate a web site for usability and security
LO4. experience building a prototype interface, and learning aspects of it independently from provided resources
LO5. knowledge of design guidelines and how to apply them to design user interfaces
LO6. use iterative prototyping, with design and evaluation cycles, to explore a design space
LO7. demonstrate knowledge of a core set of cognitive, physiological, organisational, and other key human factors and their implications for interface design
LO8. demonstrate awareness of the major challenges for designing effective user interfaces, including factors associated with individual users, cultural and organisational contexts
LO9. evaluate interfaces, following a user-based technique
LO10. understand common security terminology in security literature
LO11. understand different ways in which security of computer systems can be compromised, e.g. physically, remotely, operationally (esp. social engineering); and relate specific attack scenarios to the major security goals such as authentication, integrity, secrecy, non-repudiation
LO12. understand the major challenges for security of programs, information, computers and networks, and ability to avoid most egregious (typical) flaws in designing and operating IT systems
LO13. demonstrate a high-level knowledge of common approaches to achieve security goals in computer systems (environment control, communications security and OS security, secure operational practices).

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 major structural 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

INFO2222: Computing 2 Usability and Security

Semester 1, 2020 [Normal day] - Camperdown/Darlington, Sydney

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