Privacy in data systems has traditionally focused on protecting sensitive information as it enters a system - what we call input privacy. However, as systems become more complex and capable of inferring sensitive information from seemingly harmless data, the importance of output privacy has gained...
Secure multi-party computation (SMPC) enables organisations to collaborate on sensitive data analysis without directly sharing raw information. However, seemingly harmless aggregate outputs, particularly private set intersection (PSI), can leak individual-level information when analysed strategically over time. This post is based on research presented by Guo...
Multi-touch attribution is considered as holy grail in advertising industry. As advertisers are targeting users with multiple advertisements across different platforms and publishers, understanding how each of these touch points contributes to conversion is crucial—but this understanding has traditionally come at the cost of...
Safeguarding individual privacy inherently means data minimisation i.e. limiting the collection and disposal of data. This principle has been a cornerstone of privacy advocacy and is even enshrined in regulations like the EU's General Data Protection Regulation (GDPR). However, a research published...
Tech companies and large consumer businesses are grappling with how best to protect end-user data while maintaining pace of innovation and competitive edge. Two distinct approaches have emerged: top-down and bottom-up privacy. Understanding these approaches is essential for anyone involved in privacy engineering, product development,...