21 citations · 103 across the 21 of their papers we have counts for
4 papers · 1 filter
HE-Guardrail: A Homomorphic Guardrail Against Jailbreak Attacks for Encrypted Large Language Model Inference
Byeongseo Min, Yongwoo Lee, Young-Sik Kim +1
Homomorphic encryption (HE) has emerged as a promising approach to privacy-preserving machine learning (PPML), enabling computation directly over encrypted data. In HE-based PPML,…
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…
On the Efficient Estimation of Min-Entropy
Yongjune Kim, Cyril Guyot, Young-Sik Kim
The min-entropy is a widely used metric to quantify the randomness of generated random numbers in cryptographic applications; it measures the difficulty of guessing the most likely…