Direct Identifiers, Quasi-Identifiers & Sensitive Attributes
This lesson is part of the course
In this lesson
You sort the columns of the (fictional) Larkfield Community Health Survey into direct identifiers, quasi-identifiers and sensitive attributes, the first step of every anonymisation project.
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Lessons in this course
- Direct Identifiers, Quasi-Identifiers & Sensitive Attributes Locked
- Pseudonymisation: Lookup Keys, Salted IDs & Masking Locked
- Generalisation: Age Bands & ZIP Prefixes Locked
- k-Anonymity: Equivalence Classes with COUNTIFS Locked
- Suppression of Small Classes & Information Loss Locked
- l-Diversity: When Everyone in a Class Shares the Secret Locked
- Re-identification Risk: 1/k, Average & Maximum Risk Locked
- Data Minimisation & Retention: Which Rows Must Go? Locked