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...
Homomorphic encryption is a powerful cryptographic technique that allows computations to be performed on encrypted data without decrypting it first. This blog post will introduce the concept of homomorphic encryption and demonstrate implementations using Python. What is Homomorphic Encryption? Homomorphic encryption is a form of...