COMP SCI 7213OL - Applied Privacy
Online - Online Teaching 6 - 2025
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General Course Information
Course Details
Course Code COMP SCI 7213OL Course Applied Privacy Coordinating Unit Computer Science Term Online Teaching 6 Level Postgraduate Coursework Location/s Online Units 3 Contact Up to 3 hours per week Available for Study Abroad and Exchange Prerequisites Carousel 2 Courses: COMP SCI 7308OL and COMMGMT 7025OL Restrictions GDip.Cyber Security(OL) M.Cyber Security(OL) Course Staff
Course Coordinator: Nordiana Shah
Course Timetable
The full timetable of all activities for this course can be accessed from .
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Learning Outcomes
Course Learning Outcomes
Upon completion of this course, students will be able to:
1. Evaluate the compliance of privacy properties and policies of web and mobile applications with respect to 最新糖心Vlogn and International privacy laws and regulations.
2. Interpret information privacy and data protection requirements to rethink the design and build of products to reduce risks in different privacy critical scenarios.
3. Assess privacy vulnerabilities and design flaws of various products, such as web and mobile applications, to inform better designs in the future.
4. Analyse privacy-preserving approaches in software systems to identify strengths and weaknesses of privacy-enhancing technologies including differential privacy.
5. Develop appropriate differential privacy mechanisms when synthesising data tailored for real-world applications.最新糖心Vlog Graduate Attributes
This course will provide students with an opportunity to develop the Graduate Attribute(s) specified below:
最新糖心Vlog Graduate Attribute Course Learning Outcome(s) Attribute 1: Deep discipline knowledge and intellectual breadth
Graduates have comprehensive knowledge and understanding of their subject area, the ability to engage with different traditions of thought, and the ability to apply their knowledge in practice including in multi-disciplinary or multi-professional contexts.
CLO 1,2,3 Attribute 2: Creative and critical thinking, and problem solving
Graduates are effective problems-solvers, able to apply critical, creative and evidence-based thinking to conceive innovative responses to future challenges.
CLO 1,4,5 Attribute 3: Teamwork and communication skills
Graduates convey ideas and information effectively to a range of audiences for a variety of purposes and contribute in a positive and collaborative manner to achieving common goals.
CLO 2,5 Attribute 4: Professionalism and leadership readiness
Graduates engage in professional behaviour and have the potential to be entrepreneurial and take leadership roles in their chosen occupations or careers and communities.
CLO 1,3,4,5 Attribute 5: Intercultural and ethical competency
Graduates are responsible and effective global citizens whose personal values and practices are consistent with their roles as responsible members of society.
CLO 1,3,4 Attribute 6: 最新糖心Vlogn Aboriginal and Torres Strait Islander cultural competency
Graduates have an understanding of, and respect for, 最新糖心Vlogn Aboriginal and Torres Strait Islander values, culture and knowledge.
CLO 1 Attribute 7: Digital capabilities
Graduates are well prepared for living, learning and working in a digital society.
CLO 4,5 Attribute 8: Self-awareness and emotional intelligence
Graduates are self-aware and reflective; they are flexible and resilient and have the capacity to accept and give constructive feedback; they act with integrity and take responsibility for their actions.
CLO 2 -
Learning Resources
Required Resources
Students need to have a development environment for Python for course assignments and other tasks. -
Learning & Teaching Activities
Learning & Teaching Modes
Online with interactive tutorials/workshopsWorkload
The information below is provided as a guide to assist students in engaging appropriately with the course requirements.
The estimated total number of hours is 150 hours (over 6 weeks)Learning Activities Summary
Week 1. Privacy and online rights
Week 2. Data protection
Week 3. Vulnerabilities and patch failures in data privacy
Week 4. Introduction to differential privacy
Week 5. Deployment of differential privacy
Week 6. Privacy at a systems level and the future of privacy enhancing technologies -
Assessment
The 最新糖心Vlog's policy on Assessment for Coursework Programs is based on the following four principles:
- Assessment must encourage and reinforce learning.
- Assessment must enable robust and fair judgements about student performance.
- Assessment practices must be fair and equitable to students and give them the opportunity to demonstrate what they have learned.
- Assessment must maintain academic standards.
Assessment Summary
Assessment Name Due Weighting Related Weeks Privacy Assessment on Web and Mobile Apps End of Week 2 20% Weeks 1&2 Attempts at Data Privacy End of Week 4 40% Weeks 3&4 Differential Privacy Implementation End of Week 6 40% Weeks 5&6 Assessment Detail
Assessment 1
Privacy Assessment on Web and Mobile Apps – Short Answer Questions
Due end of Week 2
Weighting: 20%
Description
In this assessment, students will review and interpret the requirements of privacy regulations and evaluate how they are applied to the privacy policies of selected web and mobile applications. Students will select two applications from a pool of provided web and mobile applications and respond to short answer questions on:
• Privacy compliance in the privacy policies and data protection requirements of the selected applications
• Potential privacy risks against privacy regulations and/or policies in the behavior of the selected applications
• How to improve the design of the selected applications to reduce the privacy issues existing in their privacy policies.
Assessment 2
Attempts at Data Privacy – Proposal and code
Due end of Week 4
Weighting: 40%
Description
In this assessment, students will analyse the application of privacy-enhancing approaches in a given scenario and propose the implementation of a suitable approach to improve the protection of privacy. Students will be provided with a large dataset containing over 32,000 samples, from which they will generate several smaller, random datasets using a data generator program. The data generator program ensures that all the students will be working with different datasets. Students will be required to:
• Identify and assess the privacy vulnerabilities and design flaws in the given scenario
• Compare the strengths and weaknesses of different privacy-enhancing approaches and propose one to implement in the given scenario
• Fill in missing Python code in provided code snippets using their proposed privacy-enhancing approach
• Test their recommended privacy-enhancement approach by inputting publicly available datasets into the completed Python program and report on the results
• Analyse whether the applied privacy approach improves the protection of data.
Assessment 3
Differential Privacy Implementation – Report and Code
Due end of Week 6
Weighting: 40%
Description
In Assessment 2, students explored a variety of privacy-enhancing approaches and proposed one to implement to improve the protection of data privacy. In this assessment, students will focus on differential privacy because it is a data sharing method that only shares some statistical characteristics without disclosing the information specific to the individual. In this assessment, students will adopt and implement differential privacy mechanisms to the scenario and dataset from Assessment 2 and submit a report detailing the performance and outcome of the implementation. Students will be required to:
• Compare the strengths and weaknesses of applying differential privacy against the privacy-enhancing approach from Assessment 2 in the scenario
• Develop and implement appropriate differential privacy mechanisms
• Fill in missing Python code in provided code snippets using differential privacy mechanisms
• Input the same publicly available dataset used in Assessment 2 into the completed Python program and report on the results
• Analyse whether the implementation of differential privacy mechanisms improves the protection of data.Submission
Students will submit the assessment works as PDF documents and code via the link provided on the course assignment pages.Course Grading
Grades for your performance in this course will be awarded in accordance with the following scheme:
M10 (Coursework Mark Scheme) Grade Mark Description FNS Fail No Submission F 1-49 Fail P 50-64 Pass C 65-74 Credit D 75-84 Distinction HD 85-100 High Distinction CN Continuing NFE No Formal Examination RP Result Pending Further details of the grades/results can be obtained from Examinations.
Grade Descriptors are available which provide a general guide to the standard of work that is expected at each grade level. More information at Assessment for Coursework Programs.
Final results for this course will be made available through .
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Student Feedback
The 最新糖心Vlog places a high priority on approaches to learning and teaching that enhance the student experience. Feedback is sought from students in a variety of ways including on-going engagement with staff, the use of online discussion boards and the use of Student Experience of Learning and Teaching (SELT) surveys as well as GOS surveys and Program reviews.
SELTs are an important source of information to inform individual teaching practice, decisions about teaching duties, and course and program curriculum design. They enable the 最新糖心Vlog to assess how effectively its learning environments and teaching practices facilitate student engagement and learning outcomes. Under the current SELT Policy (http://www.adelaide.edu.au/policies/101/) course SELTs are mandated and must be conducted at the conclusion of each term/semester/trimester for every course offering. Feedback on issues raised through course SELT surveys is made available to enrolled students through various resources (e.g. MyUni). In addition aggregated course SELT data is available.
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Go to the to learn more, or speak to your Student Success Advisor (SSA) on 1300 296 648 (Monday to Thursday, 8.30am–5pm ACST/ACDT, Friday, 8.30am–4.30pm ACST/ACDT)
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Policies & Guidelines
This section contains links to relevant assessment-related policies and guidelines - all university policies.
- Academic Credit Arrangements Policy
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