collaborators

5 papers

cs.CR2026

WHET: Welding Homomorphic Encryption to Accelerator Architectures

Jongmin Kim, Hyesung Ji, Wonseok Choi +2

Fully homomorphic encryption (FHE) enables computations on encrypted data without decryption, offering strong data privacy at the expense of substantial computational and memory ov…

cs.CR2026

GPIR: Enabling Practical Private Information Retrieval with GPUs

Hyesung Ji, Hyunah Yu, Jongmin Kim +3

Private information retrieval (PIR) allows private database queries; however, it is hindered by intense server-side computation and memory traffic. Numerous modern lattice-based PI…

cs.CR2026

Theodosian: A Deep Dive into Memory-Hierarchy-Centric FHE Acceleration

Wonseok Choi, Hyunah Yu, Jongmin Kim +3

Fully homomorphic encryption (FHE) enables secure computation on encrypted data, mitigating privacy concerns in cloud and edge environments. However, due to its high compute and me…

cs.CR2025

IVE: An Accelerator for Single-Server Private Information Retrieval Using Versatile Processing Elements

Sangpyo Kim, Hyesung Ji, Jongmin Kim +3

Private information retrieval (PIR) is an essential cryptographic protocol for privacy-preserving applications, enabling a client to retrieve a record from a server's database with…

cs.CR2025

Cheddar: A Swift Fully Homomorphic Encryption Library Designed for GPU Architectures

Wonseok Choi, Jongmin Kim, Jung Ho Ahn

Fully homomorphic encryption (FHE) frees cloud computing from privacy concerns by enabling secure computation on encrypted data. However, its substantial computational and memory o…