Differential Privacy: 6 Key Equations Explained
Differential Privacy is a powerful framework for ensuring privacy in data analysis by adding …
Input vs Output Privacy
Privacy in data systems has traditionally focused on protecting sensitive information as it enters a …
Birds of a Feather Leak Together: The Set Bias Privacy Problem
Secure multi-party computation (SMPC) enables organisations to collaborate on sensitive data …
Privacy-Preserving Multi-Touch Attribution at TikTok
Multi-touch attribution is considered as holy grail in advertising industry. As advertisers are …
The Where's Waldo Effect in Privacy
Safeguarding individual privacy inherently means data minimisation i.e. limiting the collection and …
Top-down vs. Bottom up Privacy
Tech companies and large consumer businesses are grappling with how best to protect end-user data …
Distributed Aggregation Protocol (DAP) Primer
In last post we covered, Privacy Preserving Measurement (PPM) and discussed how Distributed …
Privacy Preserving Measurement
In 1982, Andrew Yao proposed the Millionaire Problem which discusses how two millionaires can learn …
Managing Differential Privacy in Large Scale Systems
The promise of differential privacy is compelling. It offers a rigorous, provable guarantee of …