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cs.CR2026
HelpBench: Assessing the Ability of LLMs to Provide Privacy, Safety, and Security Advice
Sarah Meiklejohn, Sunny Consolvo, Patrick Gage Kelley +5
This paper introduces HelpBench, a benchmark for assessing whether LLMs are capable of providing accurate help in response to questions about digital privacy, safety, and security.…
cs.CR2025
Trusted Machine Learning Models Unlock Private Inference for Problems Currently Infeasible with Cryptography
Ilia Shumailov, Daniel Ramage, Sarah Meiklejohn +4
We often interact with untrusted parties. Prioritization of privacy can limit the effectiveness of these interactions, as achieving certain goals necessitates sharing private data.…