5 papers
WHERE to Generate Matters: Budget-Aware Synthetic Augmentation for Label Skewed Federated Learning
Sangwoo Lee, Sunghwan Park, Jaewoo Lee
Label skew in federated learning (FL) causes client drift and degrades global accuracy. Synthetic data augmentation can reduce this imbalance; however, full class balancing require…
REAN: Reconstruction-aware ECG Anonymization Based on Privacy--Utility Orthogonality
Taerin Ki, Sunghwan Park, Junyoung Park +1
A shared electrocardiogram (ECG) is itself a biometric fingerprint that can re-identify a patient and reveal personal information. Recent ECG anonymizers transform the signal befor…
Unlearnable Faces: Privacy Protection Surviving Extraction Pipeline
Byunghoon Oh, Sunghwan Park, Jaewoo Lee
Unlearnable examples keep publicly shared photos from being learned by unauthorized face-recognition models. An imperceptible perturbation, added before sharing, makes any model tr…
Persona Attack: Incremental Memory Injection Jailbreak Attack against Large Language Models
Junyoung Park, Seongyong Ju, Sunghwan Park +1
As Large Language Models evolve for user convenience, vulnerability to jailbreak attacks continues to be reported despite ongoing efforts in safety training. Traditional jailbreak…
Retrieval Augmented Classification for Confidential Documents
Yeseul E. Chang, Rahul Kailasa, Simon Shim +2
Unauthorized disclosure of confidential documents demands robust, low-leakage classification. In real work environments, there is a lot of inflow and outflow of documents. To conti…