Modern messengers use advanced end-to-end encryption protocols to protect message content even if user secrets are ever temporarily exposed. Yet, encryption alone does not prevent user tracking, as protocols often attach metadata, such as sequence numbers, public keys, or even plain user identifiers. This metadata reveals the social network as well as communication patterns between users. Existing protocols that hide metadata in Signal (i.e., Sealed Sender), for MLS-like constructions (Hashimoto et al., CCS 2022), or in mesh networks (Bienstock et al., CCS 2023) are relatively inefficient or specially tailored for only particular settings. Moreover, all existing practical solutions reveal crucial metadata upon exposures of user secrets.

Federated Learning (FL) solutions with central Differential Privacy (DP) have seen large improvements in their utility in recent years arising from the matrix mechanism, while FL solutions with distributed (more private) DP have lagged behind. In this work, we introduce the distributed matrix mechanism to achieve the best-of-both-worlds; better privacy of distributed DP and better utility from the matrix mechanism. We accomplish this using a novel cryptographic protocol that securely transfers sensitive values across client committees of different training iterations with constant communication overhead. This protocol accommodates the dynamic participation of users required by FL, including those that may drop out from the computation. We provide experiments which show that our mechanism indeed significantly improves the utility of FL models compared to previous distributed DP mechanisms, with little added overhead.

The majority of secure messengers have single, centralized service providers that relay ciphertexts between users to enable asynchronous communication. However, in some scenarios such as mass protests in censored networks, relying on a centralized provider is fatal. Mesh messengers attempt to solve this problem by building ad hoc networks in which user clients perform the ciphertext-relaying task. Yet, recent analyses of widely deployed mesh messengers discover severe security weaknesses (Albrecht et al. CT-RSA'21 & USENIX Security'22).