2025
conference-paper
OpenAlex
Heonhui Jung, Whoi Ree Ha, Kevin Nam, Youyeon Joo et autres
Graph Neural Networks (GNNs) are increasingly used in domains such as finance and bioinformatics, where both node features and edge structures can contain sensitive information. While Fully Homomorphic Encryption (FHE) offers a promising solution for privacy-preserving GNN inference, existing approaches such as …
kr, fr
(code pays fourni par la source)
Accès ouvert
2025
conference-paper
OpenAlex
Kevin Nam, Heonhui Jung, Hyunyoung Oh, Yunheung Paek
Processing-in-memory (PIM) architectures are promising for accelerating intensive workloads due to their high internal bandwidth. This paper introduces a technique for accelerating Fully Homomorphic Encryption over the Torus (TFHE), a promising yet intensive application, on a realistic PIM system. Existing TFHE accelerators …
kr
(code pays fourni par la source)
Accès ouvert
2024
article
OpenAlex
Heonhui Jung, Hyunyoung Oh
This study introduces a hardware accelerator to support various Post-Quantum Cryptosystem (PQC) schemes, addressing the quantum computing threat to cryptographic security. PQCs, while more secure, also bring significant computational demands, which are especially problematic for lightweight devices. Previous hardware accelerators are typically …
kr
(code pays fourni par la source)
Accès ouvert
2024
preprint
OpenAlex
Heonhui Jung, Hyunyoung Oh
This study introduces a hardware accelerator to support various Post-Quantum Cryptosystem (PQC) schemes, addressing the quantum computing threat to cryptographic security. PQCs, while more secure, also bring significant computational demands, especially problematic for lightweight devices. Previous hardware accelerators are typically scheme-specific, which …
kr
(code pays fourni par la source)