Anonymous Broadcast Channels (ABCs) allow a group of clients to announce messages without revealing the exact author. Modern ABCs operate in a client-server model, where anonymity depends on some threshold (e.g, 1 of 2) of servers being honest. ABCs are an important application in their own right, e.g., for activism and whistleblowing. Recent work on ABCs (Riposte, Blinder) has focused on minimizing the bandwidth cost to clients and servers when supporting large broadcast channels for such applications. But, particularly for low bandwidth settings, they impose large costs on servers, make cover traffic costly, and make volunteer operators unlikely. In this paper, we describe the design, implementation, and evaluation of ZipNet, an anonymous broadcast channel that: 1) scales to hundreds of anytrust servers by minimizing the computational costs of each server, 2) substantially reduces the servers' bandwidth costs by outsourcing the aggregation of client messages to untrusted (for privacy) infrastructure, and 3) supports cover traffic that is both cheap for clients to produce and for servers to handle.

Internet of Things (IoT) devices, once deployed, must remain secure for their entire lifetime, which can be as long as 20 years. Over this lifetime, devices must be able to update which ciphers they use to meet evolving security requirements. However, devices cannot rely on software updates for their cryptography because software implementations consume too much energy. At the same time, fixed function hardware accelerators such as an AES engine cannot support new ciphers. This paper presents Falcon, a hardware architecture for accelerating a broad range of cryptography on energy limited devices. Rather than accelerate a fixed set of current ciphers, Falcon provides a general execution engine that accelerates dominant and emerging ciphers, such as AES, Cha-Cha, SHA-256, RSA, ECC with Curve25519, as well as post-quantum ciphers such as R-LWE. For cryptography, Falcon provides the flexibility of software while reducing the energy consumption of cryptography by 5-60x compared to software. This reduction makes it feasible for IoT applications to upgrade the ciphers they use after deployment, allowing them to keep up to date with security best practices without reducing their deployment lifetime or reducing the application workload. In an application monitoring the temperature of sensitive medical supplies in hospitals, Falcon doubles the deployment lifetime (2.2x).