标题： 无线联邦学习中多服务器的渐近最优安全聚合 显示英文标题

标题： Asymptotically Optimal Secure Aggregation for Wireless Federated Learning with Multiple Servers

摘要： 在本文中，我们研究了在具有多个好奇服务器的\emph{无线的}联邦学习系统中安全聚合问题的传输延迟。我们提出了一种隐私保护的编码聚合方案，其中服务器无法推断出分布式用户本地梯度的任何信息，也無法推斷出聚合值。在我们的方案中，每个用户使用多秘密共享方法将其本地梯度编码为$\sK$个仅针对不同服务器的机密消息，每个服务器转发接收到的机密消息的总和，而用户依次采用人工噪声对齐技术以促进安全传输。通过这些总和，用户可以恢复所有本地梯度的聚合值。我们证明了信息论意义上的隐私保证，并表征了上行链路和下行链路通信延迟，用\emph{归一化交付时间}（NDT）来衡量，两者都随着服务器数量$\sK$的增加而单调减少，而在用户数量$\sM$的大部分范围内则增加。最后，我们建立了所考虑系统的NDT下界，并理论证明了在条件$\sK \gg \sM \gg 0$和$\sK \gg \sM$下，该方案分别达到了最优的上行链路和下行链路NDT。 对于任意的$\sK$和$\sM$，所提出的方案在乘法间隙$4$内实现了上行链路的最优 NDT。 显示英文摘要

摘要： In this paper, we investigate the transmission latency of the secure aggregation problem in a \emph{wireless} federated learning system with multiple curious servers. We propose a privacy-preserving coded aggregation scheme where the servers can not infer any information about the distributed users' local gradients, nor the aggregation value. In our scheme, each user encodes its local gradient into $\sK$ confidential messages intended exclusively for different servers using a multi-secret sharing method, and each server forwards the summation of the received confidential messages, while the users sequentially employ artificial noise alignment techniques to facilitate secure transmission. Through these summations, the user can recover the aggregation of all local gradients. We prove the privacy guarantee in the information-theoretic sense and characterize the uplink and downlink communication latency measured by \emph{normalized delivery time} (NDT), both of which decrease monotonically with the number of servers $\sK$ while increasing over most of the range of the number of users $\sM$. Finally, we establish a lower bound on the NDT of the considered system and theoretically prove that the scheme achieves the optimal uplink and downlink NDT under the conditions $\sK \gg \sM \gg 0$ and $\sK \gg \sM$, respectively. For arbitrary $\sK$ and $\sM$, the proposed scheme achieves the optimal uplink NDT within a multiplicative gap of $4$.