1 citations · 1 across the 3 of their papers we have counts for
4 papers
Rethinking the Capability of Fine-Tuned Language Models for Automated Vulnerability Repair
Woorim Han, Yeongjun Kwak, Miseon Yu +4
Learning-based automated vulnerability repair (AVR) techniques that utilize fine-tuned language models have shown promise in generating vulnerability patches. However, questions re…
VFLIP: A Backdoor Defense for Vertical Federated Learning via Identification and Purification
Yungi Cho, Woorim Han, Miseon Yu +3
Vertical Federated Learning (VFL) focuses on handling vertically partitioned data over FL participants. Recent studies have discovered a significant vulnerability in VFL to backdoo…
Precise Extraction of Deep Learning Models via Side-Channel Attacks on Edge/Endpoint Devices
Younghan Lee, Sohee Jun, Yungi Cho +3
With growing popularity, deep learning (DL) models are becoming larger-scale, and only the companies with vast training datasets and immense computing power can manage their busine…
FLGuard: Byzantine-Robust Federated Learning via Ensemble of Contrastive Models
Younghan Lee, Yungi Cho, Woorim Han +2
Federated Learning (FL) thrives in training a global model with numerous clients by only sharing the parameters of their local models trained with their private training datasets.…