16 citations · 19 across the 5 of their papers we have counts for
6 papers
Degree-Constrained Interval Optimization for Minimax Polynomial Approximation in Homomorphic Encryption
Jiheon Woo, Donggyun Ryu, Yongjune Kim
Homomorphic encryption (HE) enables privacy-preserving inference under arithmetic constraints that restrict encrypted evaluation to additions and multiplications. As a result, non-…
CGF-Softmax: A Cumulant-Based Softmax Reformulation for Efficient Inference under Homomorphic Encryption
Hanjun Park, Byeongseo Min, Jiheon Woo +5
Homomorphic encryption (HE) is a prominent framework for privacy-preserving machine learning, enabling inference directly on encrypted data. However, evaluating softmax, a core com…
Mutual Information Minimization for Side-Channel Attack Resistance via Optimal Noise Injection
Jiheon Woo, Donggyun Ryu, Daewon Seo +4
Side-channel attacks (SCAs) pose a serious threat to system security by extracting secret keys through physical leakages such as power consumption, timing variations, and electroma…
Attention-aware Semantic Communications for Collaborative Inference
Jiwoong Im, Nayoung Kwon, Taewoo Park +3
We propose a communication-efficient collaborative inference framework in the domain of edge inference, focusing on the efficient use of vision transformer (ViT) models. The partit…
Communication-Efficient and Drift-Robust Federated Learning via Elastic Net
Seonhyeong Kim, Jiheon Woo, Daewon Seo +1
Federated learning (FL) is a distributed method to train a global model over a set of local clients while keeping data localized. It reduces the risks of privacy and security but f…
Generalized LRS Estimator for Min-entropy Estimation
Jiheon Woo, Chanhee Yoo, Young-Sik Kim +2
The min-entropy is a widely used metric to quantify the randomness of generated random numbers, which measures the difficulty of guessing the most likely output. It is difficult to…