ArticleslgStudy

engineering

Privacy by design

Privacy by design is a engineering topic covered in the lgStudy science library. This page brings together a partial reference excerpt, illustrations, worked examples, real-world applications and a short study plan, so you can understand Privacy by design rather than just read about it. In short: Privacy by design (PbD) is an approach to systems engineering initially developed by Ann Cavoukian and formalized in a joint report on privacy-enhancing technologies by a joint team of the Information and Privacy Commissioner of Ontario (Canada), the Dutch Data Protection Authority, and the Netherlands Organisation for Applied Scientific Research in 1995. The privacy by design framework was published in 2009 and ado…

Key takeaways

  • Privacy by design belongs to engineering; place it in that map before memorising details.
  • Learn the definition first, then one example that makes the definition concrete.
  • Connect Privacy by design to a quantity you can measure, compute or draw — that is where exam questions come from.
  • Reproduce the core statement of Privacy by design from memory before moving on to harder problems.

Reference excerpt

Privacy by design (PbD) is an approach to systems engineering initially developed by Ann Cavoukian and formalized in a joint report on privacy-enhancing technologies by a joint team of the Information and Privacy Commissioner of Ontario (Canada), the Dutch Data Protection Authority, and the Netherlands Organisation for Applied Scientific Research in 1995. The privacy by design framework was published in 2009 and adopted by the International Assembly of Privacy Commissioners and Data Protection Authorities in 2010. Privacy by design calls for privacy to be taken into account throughout the whole engineering process. The concept is an example of value sensitive design, i.e. taking human values into account in a well-defined manner throughout the design process. Cavoukian's approach to privacy has been criticized as being vague, challenging to enforce its adoption, difficult to apply to certain disciplines, challenging to scale up to networked infrastructures, as well as prioritizing corporate interests over consumers' interests, and placing insufficient emphasis on minimizing data collection. Recent developments in computer science and data engineering, such as support for encoding privacy in data and the availability and quality of Privacy-Enhancing Technologies (PET's) partly offset those critiques and help to make the principles feasible in real-world settings. The European GDPR regulation incorporates privacy by design.

History and background The privacy by design framework was developed by Ann Cavoukian, Information and Privacy Commissioner of Ontario, following her joint work with the Dutch Data Protection Authority and the Netherlands Organisation for Applied Scientific Research in 1995. In 2009, the Information and Privacy Commissioner of Ontario co-hosted an event, Privacy by Design: The Definitive Workshop, with the Israeli Law, Information and Technology Authority at the 31st International Conference of Data Protection and Privacy Commissioners (2009). In 2010 the framework achieved international acceptance when the International Assembly of Privacy Commissioners and Data Protection Authorities unanimously passed a resolution on privacy by design recognising it as an international standard at their annual conference. Among other commitments, the commissioners resolved to promote privacy by design as widely as possible and foster the incorporation of the principle into policy and legislation.

Foundational principles Privacy by design is based on seven "foundational principles":

Proactive not reactive; preventive not remedial Privacy as the default setting Privacy embedded into design Full functionality – positive-sum, not zero-sum End-to-end security – full lifecycle protection Visibility and transparency – keep it open Respect for user privacy – keep it user-centric The principles have been cited in over five hundred articles referring to the Privacy by Design in Law, Policy and Practice white paper by Ann Cavoukian.

Principles in detail

Proactive not reactive; preventive not remedial The privacy by design approach is characterized by proactive rather than reactive measures. It anticipates and prevents privacy invasive events before they happen. Privacy by design does not wait for privacy risks to materialize, nor does it offer remedies for resolving privacy infractions once they have occurred — it aims to prevent them from occurring. In short, privacy by design comes before-the-fact, not after.

Privacy as the default Privacy by design seeks to deliver the maximum degree of privacy by ensuring that personal data are automatically protected in any given IT system or business practice. If an individual does nothing, their privacy still remains intact. No action is required on the part of the individual to protect their privacy — it is built into the system, by default.

PbD practices Purpose Specification - The data subjects must be clearly communicated to at or before any data collection, retention, or usage occurs, and the purpose(s) must be limited and relevant to the stated needs. Collection Limitation - Collection of data must be fair, lawful, and limited to the stated purpose. Data minimization - Collection of data should be minimized as much as possible, and technologies should default to have users be non-identifiable and non-observable or minimized if absolutely necessary. Use, Retention, and Disclosure - Use, retention, and disclosure of data must be limited and only for what has been consented to, with exceptions by law. Information should only be retained for the stated amount time needed and then securely erased.

Privacy embedded into design Privacy by design is embedded into the design and architecture of IT systems as well as business practices. It is not bolted on as an add-on, after the fact. The result is that privacy becomes an essential component of the core functionality being delivered. Privacy is integral to the system without diminishing functionality.

Full functionality – positive-sum, not zero-sum Privacy by design seeks to accommodate all legitimate interests and objectives in a positive-sum “win-win” manner, not through a dated, zero-sum approach, where unnecessary trade-offs are made. Privacy by design avoids the pretense of false dichotomies, such as privacy versus security, demonstrating that it is possible to have both.

End-to-end security – full lifecycle protection Privacy by design, having been embedded into the system prior to the first element of information being collected, extends securely throughout the entire lifecycle of the data involved — strong security measures are essential to privacy, from start to finish. This ensures that all data are securely retained, and then securely destroyed at the end of the process, in a timely fashion. Thus, privacy by design ensures cradle-to-grave, secure lifecycle management of information, end-to-end.

Visibility and transparency – keep it open Privacy by design seeks to assure all stakeholders that whatever business practice or technology involved is in fact operating according to the stated promises and objectives, subject to independent verification. The component parts and operations remain visible and transparent, to users and providers alike. Remember to trust but verify.

… excerpt ends here. Continue reading the full article.

Worked examples

Example 1 — a first encounter with Privacy by design

Start with the simplest possible case. Write down what Privacy by design claims or describes in one sentence, then invent the smallest concrete situation in which that sentence is true. In engineering, the smallest case is usually a single object, a single equation or a single measurement. Check that every symbol or term in your sentence has a meaning in that case.

Example 2 — changing one variable

Take the situation from Example 1 and change exactly one quantity: double it, halve it, or set it to zero. Predict what should happen to Privacy by design before you calculate. Comparing your prediction with the result is the fastest way to find out whether you understand the idea or only the words.

Example 3 — an exam-style question

Typical questions about Privacy by design ask you to (a) state it precisely, (b) apply it to given data, and (c) explain a limitation. Practise writing all three answers in under five minutes; the third part is what separates a full-mark answer from an average one.

Applications of Privacy by design

In research
Privacy by design appears in engineering research whenever the underlying quantities have to be modelled precisely. Papers usually cite it as a starting assumption and then explore where it breaks down.
In technology and industry
Engineering practice reuses Privacy by design in design rules, simulations and safety margins. Knowing the idea lets you read a specification sheet and understand why the numbers look the way they do.
In the classroom
Privacy by design is common in secondary-school and first-year university syllabi. It links to neighbouring topics Information privacy, Privacy, Product design, so understanding it makes those chapters shorter.
In everyday life
Look for Privacy by design outside the textbook — in sport, cooking, traffic, electronics or the sky above you. An example you found yourself is remembered far longer than one you were given.

Affiliate

Preply — study more efficiently by working with a personal tutor. 50% off.

How to study Privacy by design in 20 minutes

  1. Read the reference excerpt below once, without taking notes.
  2. Close the page and write down what Privacy by design means in your own words.
  3. Compare your version with the excerpt and mark what you missed.
  4. Work through the three examples above with pen and paper.
  5. Explain Privacy by design out loud to somebody else — or to Teacher Smith in the lgStudy chat.

Frequently asked questions

What is Privacy by design in simple terms?

Privacy by design (PbD) is an approach to systems engineering initially developed by Ann Cavoukian and formalized in a joint report on privacy-enhancing technologies by a joint team of the Information and Privacy Commissioner of Ontario (Canada), the Dutch Data Protection Authority, and the Netherl…

Why does Privacy by design matter?

Because it connects several engineering ideas at once: it gives you a definition you can apply, a quantity you can calculate, and a way to check whether a result is plausible.

How should I study Privacy by design?

Read the excerpt, restate it from memory, then work through the examples and applications listed on this page. The five-step study plan above takes about twenty minutes.

What does this page cover?

It gives you a compact reference excerpt plus original lgStudy explanations, examples, applications and study material on Privacy by design.

Tags

  • Information privacy
  • Privacy
  • Product design
  • Systems engineering

Keep exploring