Function Secret Sharing for PSI-CA:With Applications to Private Contact Tracing
This work addresses the problem of lightweight privacy-preserving contact tracing for individuals, offering an incremental improvement by leveraging FSS.
This paper proposes a token-based solution for private contact tracing using Function Secret Sharing (FSS), specifically Distributed Point Functions (DPF). The method enables secure keyword search on raw sets of keywords and aggregates numerical payloads from multiple matches without additional interaction.
In this work we describe a token-based solution to Contact Tracing via Distributed Point Functions (DPF) and, more generally, Function Secret Sharing (FSS). The key idea behind the solution is that FSS natively supports secure keyword search on raw sets of keywords without a need for processing the keyword sets via a data structure for set membership. Furthermore, the FSS functionality enables adding up numerical payloads associated with multiple matches without additional interaction. These features make FSS an attractive tool for lightweight privacy-preserving searching on a database of tokens belonging to infected individuals.