k-Anonymity
A privacy model ensuring that each record in a dataset is indistinguishable from at least k-1 other records with respect to quasi-identifier attributes.
In plain language
A technique that makes it impossible to identify a specific person in a dataset by ensuring everyone blends in with at least k-1 others. If k=5, you can't single out any individual based on characteristics like age, postcode and employer.
Why this matters
K-anonymity is a formal privacy protection mechanism that can support compliance with the Privacy Act's Australian Privacy Principles, particularly for research or analytics involving sensitive data. Your data governance framework should evaluate whether k-anonymity is appropriate for your use cases, especially when sharing data with external parties.
Relevance
GovernanceK-anonymity provides a measurable privacy standard that helps organisations meet legal obligations around data protection while enabling legitimate analytics.
Related terms
Putting k-anonymity into practice in your organisation?
Ready to transform your AI strategy?
Partner with Australia's AI strategy and governance specialists. From adoption roadmaps to ISO 42001 audit readiness.