3 papers
cs.CR2026
Scaling up FHE-based Privacy-Preserving ML: Higher Throughput, Longer Inputs for LLama-3-8B
Jaiyoung Park, Sejin Park, Jai Hyun Park +6
As large language models (LLMs) become ubiquitous, privacy concerns pertaining to inference keep growing. Fully homomorphic encryption (FHE) has emerged as a primary cryptographic…
cs.CR2026
Private Iris Recognition with High-Performance FHE
Jincheol Ha, Guillaume Hanrot, Taeyeong Noh +3
Among biometric verification systems, irises stand out because they offer high accuracy even in large-scale databases. For example, the World ID project aims to provide authenticat…
cs.CR2025
Encryption-Friendly LLM Architecture
Donghwan Rho, Taeseong Kim, Minje Park +4
Large language models (LLMs) offer personalized responses based on user interactions, but this use case raises serious privacy concerns. Homomorphic encryption (HE) is a cryptograp…