Late Assessment Submission Penalty

Students enrolled in session-based units with written assessments will have the following university standard late penalty applied. Please see https://students.mq.edu.au/study/assessment-exams/assessments for more information.

Unless a Special Consideration request has been submitted and approved, a 5% penalty (of the total possible mark) will be applied each day a written assessment is not submitted, up until the 7th day (including weekends). After the 7th day, a grade of '0' will be awarded even if the assessment is submitted. Submission time for all written assessments is set at 11:55 pm. A 1-hour grace period is provided to students who experience a technical concern.

For any late submission of time-sensitive tasks, such as scheduled tests/exams, performance assessments/presentations, and/or scheduled practical assessments/labs, students need to apply for Special Consideration.

Assessments where Late Submissions will be accepted

In this unit, late submissions will be accepted as follows:

Assignments 1 and 2 – YES, standard late penalty applies

Exam - NO, unless Special Consideration is granted

Special Consideration

The Special Consideration Policy aims to support students who have been impacted by short-term circumstances or events that are serious, unavoidable and significantly disruptive, and which may affect their performance in assessment.

• Written Assessments and Exams: If you experience circumstances or events that affect your ability to complete the assignments and exam in this unit on time, please inform the convenor and submit a Special Consideration request through ask.mq.edu.au.

Requirements to Pass this Unit

To pass this unit, you must:

• Achieve a total mark equal to or greater than 50%

You will maximise your chances of passing this unit if:

• You attempt all assessments
• Participate in all lectures and practicals

ASSESSMENT TASKS

Examination

• Type: Examination

• Weighting: 40%

• Indicative Time on Task: 35 hours

• Due: Session 2 Exam Period

An assessment of all content taught in the unit. On successful completion, you will be able to:

• Explain the concepts of information security and provable privacy.
• Perform risk assessment (including privacy risk) on digital information and datasets.
• Apply adapted security technologies and tools, in particular encryption, to enhance the security properties of data.
• Analyse the trends for managing data security.

Assignment 1 – Privacy Risk Solutions

• Type: Problem Set

• Weighting: 20%

• Indicative Time on Task: 20 hours

• Release: By 11:55 pm, Friday of Week 1

• Due: By 11:55 pm, Friday of Week 6

On successful completion, you will be able to:

• Explain the concepts of information security and provable privacy.
• Apply adapted security technologies and tools, in particular encryption, to enhance the security properties of data.
• Analyse the trends for managing data security.

Assignment 2 – Provable Privacy and Privacy Risk Concepts

• Type: Group Project

• Weighting: 30%

• Indicative Time on Task: 20 hours

• Release: By 11:55 pm, Friday of Week 6

• Due: By 11:55 pm, Friday of Week 12

On successful completion, you will be able to:

• Explain the concepts of information security and provable privacy.
• Perform risk assessment (including privacy risk) on digital information and datasets.  

COMMUNICATION AND SUPPORT

All unit-related communication will take place via the iLearn discussion boards. These forums are actively monitored by the teaching team and are the preferred method for addressing unit-related queries.

You may also contact the unit staff via their Macquarie University email addresses, which are listed on the unit’s iLearn page.

COMPUTING FACILITIES

Important! Please note that this is a BYOD (Bring Your Own Device) unit. You will be expected to bring your own laptop computer (Windows, Mac or Linux), install and configure the required software.

CLASSES

Each week, you should complete any assigned readings and review the lecture slides to prepare for the lecture. There are two hours of lectures and a one-hour practical every week. Commencing from Week 1, the practicals have hands-on exercises to reinforce concepts introduced during the lectures; you should have chosen a practical on enrollment. You will find it helpful to read the practical instructions before participating.

For details of days, times, and rooms, consult the timetables webpage.

Note that Lectures and Practicals commence in week 1.

DISCUSSION BOARDS

This unit makes use of discussion boards hosted within iLearn. Please post questions there; they are monitored by the staff on the unit.

REQUIRED AND RECOMMENDED TEXTS AND/OR MATERIALS

This material for this unit is in part based on the following textbooks:

• Dwork, C. and Roth, A., 2014. The algorithmic foundations of differential privacy. Foundations and Trends in Theoretical Computer Science, 9(3-4), pp.211-407. Available online: https://www.cis.upenn.edu/~aaroth/Papers/privacybook.pdf

• Yi, X., Paulet, R. and Bertino, E., 2014. Homomorphic encryption and applications (Vol. 3). Heidelberg: Springer. Available online: https://link.springer.com/content/pdf/10.1007%2F978-3-319-12229-8.pdf (accessible through MQ Library).

TECHNOLOGY USED AND REQUIRED

iLearn

iLearn is a Learning Management System that gives you access to lecture slides, lecture recordings, forums, assessment tasks, instructions for practicals, discussion forums, and other resources.

Echo 360 (formerly known as iLecture)

Digital recordings of lectures are available. Read these instructions for details.

Technology Used

Anaconda, Jupyter Notebook with Python.

COVID INFORMATION

For the latest information on the University’s response to COVID-19, please refer to the Coronavirus infection page on the Macquarie website: https://www.mq.edu.au/about/coronavirus-faqs. Remember to check this page regularly in case the information and requirements change during semester. If there are any changes to this unit about COVID-19, these will be communicated via iLearn.

Week	Topic
1	Introduction: Mathematical Background, Data Sharing, and Privacy Risks
2	De-identification and Privacy Attacks
3	Towards Provable Privacy: K-Anonymity and Related Definitions
4	Differential Privacy and its Applications
5	Cryptography Primer and Homomorphic Encryption
6	Machine Learning and Data Privacy
7	Mobile Privacy and Attacks
8	Privacy Protection for Mobile Apps
9	Web Privacy
10	Web Behaviour Re-identification and Defence
11	Online Tracking and Fingerprinting
12	Blacklists-based Tracking Prevention
13	Revision

We value student feedback to be able to continually improve the way we offer our units. As such we encourage students to provide constructive feedback via student surveys, to the teaching staff directly, or via the FSE Student Experience & Feedback link in the iLearn page.

Student feedback from the previous offering of this unit was very positive overall, with students pleased with the clarity around assessment requirements and the level of support from teaching staff. As such, no change to the delivery of the unit is planned, however we will continue to strive to improve the level of support and the level of student engagement.