Web Application for Privacy-Preserving Scheduling
Web applications currently used for scheduling meetings – such as Doodle – do not protect the privacy of their users, i.e., compute the results based on the clear inputs of the participants. Though privacy-friendly variants of Doodle already exist based on public-key encryption [TUD], these solutions assume a trusted party whose private key can be used to decrypt all inputs. Secure computation, which allows two parties to jointly compute a function while both parties keep their inputs private, is a promising approach to provide privacy for the users' inputs without the use of a trusted poll initiator.
The goal of this thesis is to develop a web application where users can participate in a poll for scheduling meetings. This is achieved by secret-sharing the votes among two non-colluding servers, which then perform secure two-party computation to solve the scheduling problem defined beforehand.
- [TUD]: TU Dresden: dudle.inf.tu-dresden.de
- [DSZ15]: Daniel Demmler, Thomas Schneider and Michael Zohner: ABY – A Framework for Efficient Mixed-Protocol Secure Two-Party Computation. In NDSS'15.