MPC

Collaborative SNARKs - Co-Circom

In this talk we present collaborative SNARKs and why they are needed. Furthermore, we present our co-circom library, a rust library allowing to create a coSNARK from circuits written in Circom. Finally, we show how to apply co-circom to an on-chain …

Scaling Private Iris Code Uniqueness Checks to Millions of Users

In this work we tackle privacy concerns in biometric verification systems that typically require server-side processing of sensitive data (e.g., fingerprints and Iris Codes). Concretely, we design a solution that allows us to query whether a given …

Scaling Private Iris Code Uniqueness Checks to Millions of Users

In this work we tackle privacy concerns in biometric verification systems that typically require server-side processing of sensitive data (e.g., fingerprints and Iris Codes). Concretely, we design a solution that allows us to query whether a given …

Scaling Private Iris Code Uniqueness Checks to Millions of Users

Hiding Your Awful Online Choices Made More Efficient and Secure: A New Privacy-Aware Recommender System

Recommender systems are an integral part of online platforms that recommend new content to users with similar interests. However, they demand a considerable amount of user activity data where, if the data is not adequately protected, constitute a …

Large-Scale MPC: Scaling Private Iris Code Uniqueness Checks to Millions of Users

In this work we tackle privacy concerns in biometric verification systems that typically require server-side processing of sensitive data (e.g., fingerprints and Iris Codes). Concretely, we design a solution that allows us to query whether a given …

Large-Scale MPC: Decentralized Iris Code Membership

Proof of Personhood is one of the core ideas behind the Worldcoin project. An integral part of this proof is the biometric uniqueness service where an iris code is checked against many others stored in a centralized database. However, iris codes …

Privacy-Preserving Machine Learning Using Cryptography

Data scientists require an extensive training set to train an accurate and reliable machine learning model – the bigger and diverse the training set, the better. However, acquiring such a vast training set can be difficult, especially when sensitive …