With the accelerated adoption of end-to-end encryption, there is an opportunity to re-architect security and anti-abuse primitives in a manner that preserves new privacy expectations. In this paper, we consider two novel protocols for on-device blocklisting that allow a client to determine whether an object (e.g., URL, document, image, etc.) is harmful based on threat information possessed by a so-called remote enforcer in a way that is both privacy-preserving and trustworthy. Our protocols leverage a unique combination of private set intersection to promote privacy, cryptographic hashes to ensure resilience to false positives, cryptographic signatures to improve transparency, and Merkle inclusion proofs to ensure consistency and auditability. We benchmark our protocols -- one that is time-efficient, and the other space-efficient -- to demonstrate their practical use for applications such as email, messaging, storage, and other applications. We also highlight remaining challenges, such as privacy and censorship tensions that exist with logging or reporting. We consider our work to be a critical first step towards enabling complex, multi-stakeholder discussions on how best to provide on-device protections.

翻译：随着端到端加密的加速普及，我们有机会以维护新型隐私预期的方式重新设计安全与反滥用基础设施。本文提出了两种新颖的设备端黑名单协议，允许客户端基于所谓远程执行器持有的威胁信息，以既保护隐私又可信赖的方式判断某个对象（例如URL、文档、图像等）是否存在危害。我们的协议创新性地结合了私有集合求交以促进隐私保护、密码学哈希以确保对误报的鲁棒性、密码学签名以提升透明度，以及Merkle包含证明以确保一致性与可审计性。我们对两种协议（一种注重时间效率，另一种注重空间效率）进行了基准测试，以证明其在电子邮件、即时通讯、存储及其他应用场景中的实用价值。同时，我们指出了现存挑战，例如日志记录或报告机制中隐私与审查之间的冲突。我们认为，这项工作是推动关于如何最优地提供设备端保护的多方复杂讨论的关键第一步。