Macquarie University
Cyber Security: Data Privacy
Macquarie University

Cyber Security: Data Privacy

Matt Bushby

Instructor: Matt Bushby

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Gain insight into a topic and learn the fundamentals.
Beginner level
No prior experience required
2 weeks to complete
at 10 hours a week
Flexible schedule
Learn at your own pace
Gain insight into a topic and learn the fundamentals.
Beginner level
No prior experience required
2 weeks to complete
at 10 hours a week
Flexible schedule
Learn at your own pace

What you'll learn

  • Build and maintain accurate data inventories to track and govern personal information.

  • Apply Privacy by Design principles to embed safeguards across systems and services.

  • Conduct Privacy and Algorithmic Impact Assessments to identify and mitigate risks.

  • Use de-identification techniques while managing re-identification vulnerabilities.

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Recently updated!

September 2025

Assessments

12 assignments

Taught in English

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This course is part of the Cyber Security: Data, Privacy and AI Security Specialization
When you enroll in this course, you'll also be enrolled in this Specialization.
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There are 6 modules in this course

Before organisations can safeguard privacy or comply with regulations, they must first know exactly what data they hold and how it is being used. This opening topic introduces learners to the critical practice of building and maintaining data inventories, the foundation of every effective privacy program. You’ll explore how organisations collect, store, share, and process personal information, and why incomplete or inaccurate records create blind spots that expose businesses to unnecessary risk. From customer details and employee records to metadata and machine-generated logs, you’ll learn to classify data according to sensitivity, purpose, and legal obligations. Just as importantly, you’ll examine how data flows across departments, systems, and third-party providers, uncovering the hidden pathways where information is most vulnerable. By working through real-world scenarios, you’ll see how inventories support compliance with global regulations like GDPR and CCPA, enable transparency with stakeholders, and provide the essential starting point for privacy by design, risk assessments, and incident response. This topic lays the groundwork for developing a holistic view of data, transforming what might appear as fragmented information into a structured map that empowers organisations to act responsibly and strategically.

What's included

2 assignments5 plugins

Protecting privacy cannot be an afterthought, it must be embedded at the very core of products, services, and systems. This topic introduces learners to the framework of Privacy by Design and its seven foundational principles, which shift organisations from reactive responses to proactive safeguards. You’ll explore how default settings, system architecture, and lifecycle planning can minimise risks before they materialise, while still delivering functionality and value. Real-world case studies highlight both the costs of bolting privacy on too late and the advantages of designing with trust and transparency from the outset. By the end, you’ll recognise how privacy by design is not just a compliance tool, but a strategic advantage that strengthens resilience, customer loyalty, and organisational reputation.

What's included

2 assignments4 plugins

Even the best-designed systems can carry risks when implemented in practice. This topic introduces learners to Privacy Impact Assessments (PIAs), a structured process for anticipating and addressing privacy concerns before they become costly problems. You’ll discover how PIAs originated from environmental impact assessments and why regulators worldwide now view them as essential for high-risk projects. Through practical guidance, you’ll learn how to scope an assessment, engage stakeholders, evaluate risks, and propose mitigation strategies. Real-world examples illustrate how PIAs strengthen governance, reduce compliance failures, and build public trust. More than just a checklist exercise, PIAs enable organisations to weigh trade-offs, make informed choices, and demonstrate accountability to both regulators and society.

What's included

2 assignments4 plugins

As artificial intelligence systems increasingly influence decisions about people’s lives, the need for oversight has never been greater. This topic explores Algorithmic Impact Assessments (AIAs), a framework for identifying risks, biases, and unintended consequences in automated decision-making. You’ll examine how AI systems can replicate or amplify human bias, how transparency and fairness can be compromised, and why regulators and the public demand greater accountability. By analysing case studies, you’ll see how flawed algorithms can harm individuals and erode trust, and how AIAs provide organisations with a systematic way to detect, address, and minimise those harms. This topic equips you to evaluate both the technical and ethical dimensions of algorithmic systems, ensuring their deployment is not only effective but also responsible.

What's included

2 assignments5 plugins

Sharing and analysing data is vital for innovation, but it must not come at the cost of individual privacy. This topic introduces learners to the principles and techniques of data de-identification, from simple anonymisation methods to advanced strategies such as differential privacy. You’ll explore the balance between maintaining data utility and reducing the risk of re-identification, and why achieving that balance is far more complex than it first appears. Real-world examples of re-identification attacks illustrate how even “anonymised” datasets can expose individuals when combined with other sources. By the end, you’ll understand not only how to apply de-identification techniques, but also how to assess when data remains vulnerable and what additional safeguards are needed to responsibly share or publish information.

What's included

2 assignments3 plugins

In a world where breaches are no longer a question of if but when, effective incident response is a cornerstone of privacy protection. This topic guides learners through the essential steps organisations must take to prepare for, detect, and respond to privacy incidents. You’ll learn how to build and test response plans, establish clear lines of responsibility, and engage regulators, stakeholders, and affected individuals with clarity and transparency. Case studies reveal how poor responses have amplified reputational and financial damage, while strong responses have limited harm and preserved trust. You’ll also explore the role of simulations, lessons learned reviews, and continuous improvement in ensuring that each incident, whether large or small, becomes an opportunity to strengthen resilience.

What's included

1 reading2 assignments4 plugins

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Instructor

Matt Bushby
Macquarie University
15 Courses6,603 learners

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