COMMGMT 7023OL - Business Data & Cyber Security (M)
Online - Online Teaching 5 - 2023
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General Course Information
Course Details
Course Code COMMGMT 7023OL Course Business Data & Cyber Security (M) Coordinating Unit Management Term Online Teaching 5 Level Postgraduate Coursework Location/s Online Units 3 Available for Study Abroad and Exchange N Incompatible COMMGMT 2508 Assessment Projects, reflective journal and exam Course Staff
Course Coordinator: Siyakha Mthunzi
Course Timetable
The full timetable of all activities for this course can be accessed from .
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Learning Outcomes
Course Learning Outcomes
BDCS-OL Course Learning Outcomes
Code
Description
Mapped to PROGRAM LOs
CLO-1
Articulate the different roles of data, information, & knowledge in business & management.
PLO 1, PLO 3
CLO-2
Determine data and security needs to address specific business problems.
PLO 2
CLO-3
Identify and communicate appropriate quality sources and resources to address the determined needs.
PLO 2, PLO 4
CLO-4
Identify common cyber-attack vectors and the human factors that render them effective or ineffective.
PLO 1, PLO 2
CLO-5
Articulate the impacts of differing practices and legal and ethical issues around data, information and cyber security in personal, organisational, and international contexts.
PLO 3, PLO 4
Graduate Certificate in Cyber Security Program Learning OutcomesCode
Description
Mapped GAs
PLO-1
Demonstrate knowledge and understanding of the technical practice of Cyber Security, and its application within industry contexts.
GA -1,GA- 4, GA-7
PLO-2
Apply the principles of Cyber Security within real-world contexts, in an area of specialisation.
GA- 1, GA-2, GA-3,GA- 4, GA-7
PLO-3
Demonstrate professional attitudes, standards and values.
GA -4,GA- 5,GA- 6,GA- 8
PLO-4
Use interpersonal skills to enable effective communication with a range of audiences.
GA- 3, GA-4, GA-5, GA-6,GA- 8
University Graduate Attributes
This course will provide students with an opportunity to develop the Graduate Attribute(s) specified below:
University 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, 4 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-2, 3, 4 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-3, 4, 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-2, 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-3, 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-3, 5 -
Learning Resources
Required Resources
Module 1
There will be multiple occasions upon which you are directed to search for, access, assess, and use readings of your own choice. A core feature of this course is learning to find appropriate readings and use solid criteria to assess their quality, value, and relevance.
Module 1 has no pre-set readings.
Module 2
El-Atms, S & Barnes, R 2018, ‘GDPR—What it means for Australian Business’, blog post, August, 22 May.
Pienta, J, Bennet, T, Johnston, A 2020, ‘Protecting a whale in a sea of phish’, Journal of Information Technology, 3 June.
Module 3
Manisha Mathur. (2019). Where is the Security Blanket? Developing Social Media Marketing Capability as a Shield from Perceived Cybersecurity Risk, Journal of Promotion Management, 25:2, 200-224, DOI: 10.1080/10496491.2018.1443310
Oltramari, A., Henshel, D., & Cains, M. & Hoffman, B. (2015). Towards a Human Factors Ontology for Cyber Security. Proceedings of the Tenth Conference on Semantic Technology for Intelligence, Defense, and Security, Fairfax VA, USA, November 18-20, 2015.
Module 4
Berry C & Berry R 2018, ‘An initial assessment of small business risk management approaches for cyber security threats (Links to an external site.)’, International Journal of Business Continuity and Risk Management 8(1):1 DOI: 10.1504/IJBCRM.2018.10011667
Dynes S, Goetz E, Freeman M 2008, ‘Cyber Security: Are Economic Incentives Adequate?’, In: Goetz E, Shenoi S.(eds) Critical Infrastructure Protection. ICCIP 2007. IFIP International Federation for Information Processing, vol 253. Springer, Boston, MA.
Kritzinger, E & Von Solms, SH 2010, ‘Cyber security for home users: A new way of protection through awareness enforcement’, Computers & Security 29(8):840-847 November 2010
Tao H, Huiyan MZA, Raman MA, Wang G, Wang T, Ahmed MM, Li J 2019, ‘Economic perspective analysis of protecting big data security and privacy’, Future Generation Computer Systems. Volume 98, September 2019, 660-671Module 5
Ferra, F 2020, ‘Challenges in assessing privacy impact: tales from the front lines’, IEEE security & Privacy, vol. 3, no. 2, p. e101. ISSN: 1540-7993 , 1558-4046; DOI: 10.1002/spy2.101
Lam, PTI & Ma, R 2019, ‘Potential pitfalls in the development of smart cities and mitigation measures: an exploratory study', Cities, vol. 91, August, Pages 146–156
Rowe, F 2020, ‘Contact tracing apps and value dilemmas: a privacy paradox in a neo-liberal world’, International Journal of Information Management, 30 June, pp. 102–178
Di Stephano, M, 2017, ‘Here’s what happened when a Liberal donor’s business got caught dumping people’s private information’, Buzz Feed News, 25 January
Optional readings
Agrawal, A, Gans, J & Goldfarb, A 2018, Prediction machines: the simple economics of artificial intelligence, Harvard Business Review Press, Boston, Massachusetts.
Barratt, T, Veen, A & Goods, C 2020, ‘Algorithms workers can’t see are increasingly pulling the management skills’, The Conversation, 24 August.
Module 6
Christiano, A & Neimand, A 2017, ‘Stop raising awareness already’, Stanford Social Innovation Review, Spring.
Ramirez, R & Choucri, N 2016, ‘Improving interdisciplinary communication with standardized cyber security terminology: a literature review’, IEEE Access, vol. 4, pp. 2216–2243. DOI 10.1109/ACCESS.2016.2544381
Wulgaert, T 2017, ‘6 reasons why awareness programs fail even when following best practices’, CSO Australia, 24 October.
Byers, J 2020, ‘Australian Police: XAMN helped solve armed robbery’, MSAB, 10 February. -
Learning & Teaching Activities
Learning & Teaching Modes
This course is 100% online. Within the parameters of weekly requirements, course activity is conducted as self-paced learning.Workload
The information below is provided as a guide to assist students in engaging appropriately with the course requirements.
The information below is provided as a guide to assist students in engaging appropriately with the course requirements.
As a general rule, you should be spending 20 to 25 hours per week on the work in this course.Learning Activities Summary
Module 1 Introduction
Data in Business
Data Evolution
Data and Government
Data Quality
Data Risk & Value
Team CollaborationModule 2 Data & Ethical Issues
Data and Privacy
Data, Policy & Politics
Legislation, Regulation & Standards
Privacy, Bullying & TrollingModule 3 Human Vulnerability & Social Engineering
Technical Topics & Lay Speak
Social Media & Human vulnerabiities
Deep Dive into Cyber Resilience
Strategic Perspectie
Human Aspects of Cyber SecurityModule 4 Types of Data
Data, Strategy & Decision Making
Data & Economics
CyberOps - BASICS of Cyber Security for Business
Small Business & Home Network SecurityModule 5 Data, Artificial Intelligence & Machine Learning
MetaData
Smart Cities
Secure Erasure & Disposal of DataModule 6 Communicating Cyber Security
Securing Stakeholder Compliance to Cyber Security Policy
Policing & Data, Crime & Cybercrime -
Assessment
The University'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 task 1: AusTechTrade Data and Security Case Study Analysis
Due: End of Week 2, Sunday 11:59pm
Percentage of grade: 20%
Assessment task 2: Cybersecurity Group Project
Part A: Project Plan
Due: End of Week 3, Sunday 11:59pm
Percentage of grade: 10%
Part B: Pre-mortem Reflection
Due: End of Week 4, Sunday 11:59pm
Percentage of grade: 10%
Part C: Cybersecurity Group Presentation
Due: End of Week 4, Sunday 11:59pm
Percentage of grade: 20%
Assessment task 3: Research Project
Due: End of Week 6, Sunday 11:59pm
Percentage of grade: 35%
Assessment Detail
Each assessment task will have an 'Assessment task discussion board' to post your questions about the assessment. Your tutor will host a Zoom session specifically addressing the assessment in the week preceding the assessment due date.
All assessments adhere to the 成人大片 Assessment for Coursework Programs PolicyLinks to an external site..
When you submit an assessment via the online submission page, you declare that your submission is entirely your own work.
Assessment task 1: AusTechTrade Data and Security Case Study Analysis
You are required to submit a case study analysis of a real-world scenario involving " AusTechTrade," a global e-commerce company facing data challenges in a cyber security context. This will be a vehicle to demonstrate your understanding of concepts and principles taught in Business Data and Cyber Security. You will achieve this through an analysis and addressing of business data challenges focusing on different areas of the changing nature and value of data, differing approaches to data usage and data quality challenges in specific contexts.
Background
AusTechTrade is a fictional global e-commerce company with business across multiple countries. As an incumbent in the industry, AusTechTrade deals with a vast amount of data collected from various sources, including customer interactions, financial transactions, and product details. This scenario highlights the challenges AusTechTrade faces regarding data collection, cyber security threats, legal and ethical issues related to data privacy, the value of data, approaches to data usage, and data quality.
AusTechTrade collects and processes Customer Information, Financial Data, Product Details, and Internal Business Data, classified based on sensitivity. Protecting data is crucial to maintain customer trust and comply with privacy laws. Operating in Australia, EU countries and the US, AusTechTrade must adhere to various data privacy regulations. Cyber security threats like Phishing Attacks, DDoS Attacks, Insider Threats, Ransomware and Data Breaches pose risks to AusTechTrade’s business data. Nonetheless, advancements in technology enable different players, including governments, businesses, and individuals, with distinct approaches to data usage. For companies like AusTechTrade, data can enhance their services, optimise operations, and increase profitability. However, they must prioritise data privacy to maintain customer trust and comply with laws. Beyond this, data quality is vital to AusTechTrade for effective decision-making and business operations..
Due: End of Week 2, Sunday 11:59pm
Percentage of grade: 20%
Assessment task 2: Cybersecurity Group Project
This assessment will prepare you to effectively communicate important data and information in a business world that requires constant cybersecurity awareness and vigilance. Most importantly, this assessment is critical as you are being entrusted with your cohort's learning experience on your chosen topic.
You will be allocated to a team of 3–4 students for the Cybersecurity Group Project. Each team will be asked to select a topic from this list below:
1. AI and its impact on business data and cybersecurity
2. How can AI help in cybersecurity?
3. Remote working cybersecurity risks
4. How to improve cybersecurity in your business
a) Legislation and Regulation in/for cybersecurity in the age of AI – Australia and the World
b) The rise of ransomware – what, who, how, when, where, and why?
c) Social engineering attacks getting smarter.
d) How marketing & promotions use Data
e) The IoT and the cyber security challenges it brings.
f) A fun & engaging way for non-IT personnel to learn about AI, Business Data and Cybersecurity
Part A: Project Plan, aims to help you identify and articulate criteria for ensuring a successful cybersecurity project delivery. Consider this as a vehicle to gain competencies in organisational processes such as project management and communication
Due: End of Week 3, Sunday 11:59pm
Percentage of grade: 10%
Part B: Pre-mortem Reflection, encourages critical thinking and planning and aims to help you approach the assessment with greater foresight and preparedness. Before starting the group work, you are each to submit an individual “premortem” group reflection focusing on the following:
• anticipate potential challenges you might encounter during the assessment process, such as group dynamics, time management, research limitations, and technical issues.
• suggest pre-emptive measures and strategies to address these challenges effectively
Due: End of Week 4, Sunday 11:59pm
Percentage of grade: 10%
Part C: Cybersecurity Group Presentation, assesses your presentation skills and ability to work effectively in teams focusing on the following:
• effective collaboration in a team environment
• communicate ideas and communicate core knowledge about business data and cyber security in a multidisciplinary or multi-professional context.
• evaluate, research, synthesise and summarise evidence-based knowledge so that this knowledge can be disseminated to key stakeholders
Due: End of Week 4, Sunday 11:59pm
Percentage of grade: 20%
Assessment task 3: Research Project
In this assessment you will be required to select a research topic from a provided list, submit a research proposal for approval and then
create a research report using your preferred presentation style, again selected from a list.
Due: End of Week 6, Sunday 11:59pm
Percentage of grade: 40%Submission
No information currently available.
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 University 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 University 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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Policies & Guidelines
This section contains links to relevant assessment-related policies and guidelines - all university policies.
- Academic Credit Arrangements Policy
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- Assessment for Coursework Programs Policy
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