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With the accelerated adoption of end-to-end encryption, there is anopportunity to re-architect security and anti-abuse primitives in a manner thatpreserves new privacy expectations. In this paper, we consider two novelprotocols for on-device blocklisting that allow a client to determine whetheran object (e.g., URL, document, image, etc.) is harmful based on threatinformation possessed by a so-called remote enforcer in a way that is bothprivacy-preserving and trustworthy. Our protocols leverage a unique combinationof private set intersection to promote privacy, cryptographic hashes to ensureresilience to false positives, cryptographic signatures to improvetransparency, and Merkle inclusion proofs to ensure consistency andauditability. We benchmark our protocols -- one that is time-efficient, and theother space-efficient -- to demonstrate their practical use for applicationssuch as email, messaging, storage, and other applications. We also highlightremaining challenges, such as privacy and censorship tensions that exist withlogging or reporting. We consider our work to be a critical first step towardsenabling complex, multi-stakeholder discussions on how best to provideon-device protections.

Robust, privacy-preserving, transparent, and auditable on-device blocklisting