PETS

Mutual Contact Discovery

Contact discovery allows new users of a messaging service to find existing contacts that already use that service. Existing users are similarly informed of new users that join. Current contact discovery protocols allow the server to reconstruct the social graph (i.e. the graph describing who is a contact of who), which is a serious privacy issue, unless they use trusted hardware to prevent this. But even in the latter case, privacy is still at stake: anyone already on the service that has your number on their contact list gets notified that you joined. Even if you don't know that person, or if it is an ex or former colleague that you long parted with and whose contact details you deleted long ago. To solve this, we propose a *mutual* contact discovery protocol, that only allow users to discover each other when *both* are (still) in each other's contact list. Mutual contact discovery has the additional advantage that it can be implemented in a more privacy friendly fashion (e.g. protecting the social graph from the server) than traditional, one-sided contact discovery, without necessarily relying on trusted hardware.

Publicly Auditable Privacy Revocation

This seminar presents research on anonymous credentials with Publicly Auditable Privacy Revocation (PAPR). PAPR credentials simultaneously provide conditional user privacy and auditable privacy revocation for credential systems.

PrePaMS: Privacy-Preserving Participant Management for Studies with Rewards

Felix will introduce PrePaMS, an efficient participation management system that supports prerequisite checks and reward procedures in a privacy-preserving way. By using a set of proven cryptographic primitives and mechanisms, participations are protected so that service providers and organizers cannot derive the identity of participants even within the reward process.