Aggregation and Embedding for Group Membership Verification
This addresses privacy concerns in group verification systems, but it appears incremental as it builds on existing quantization and aggregation techniques.
The paper tackles the problem of preventing a server from reconstructing enrolled signatures and inferring client identities in group membership verification, achieving a trade-off between security and error rates as shown in theoretical and experimental results.
This paper proposes a group membership verification protocol preventing the curious but honest server from reconstructing the enrolled signatures and inferring the identity of querying clients. The protocol quantizes the signatures into discrete embeddings, making reconstruction difficult. It also aggregates multiple embeddings into representative values, impeding identification. Theoretical and experimental results show the trade-off between the security and the error rates.