Explaining Privacy Models Used in Anonymization (k-Anonymity, l-Diversity, t-Closeness)
Organizations utilize personal data collected from customers (e.g., analyzing them or sharing them for business purpose) while complying both with privacy policies agreed to by users and with data privacy regulations such as GDPR and CCPA. Achieving both using it for business and conforming to the regulations is tricky. Privacy models such as k-Anonymity, l-Diversity, t-Closeness are some of the metrics to help it by measuring the extent to which personal data is de-identified in a quantifiable manner.
