# Aggregation and Embedding for Group Membership Verification

arXiv: https://arxiv.org/abs/1812.03943 · HTML: https://mlsanity.com/paper/1812.03943/

## Key facts

- Cited by 1 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 10 Dec 2018.

## Built on by (most cited first, 1 of 1)

- [AggNet: Learning to Aggregate Faces for Group Membership Verification](https://mlsanity.com/paper/2206.08683/) (2022)

## Abstract (arXiv)

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.