17 citations · 43 across the 5 of their papers we have counts for
5 papers
HE-DAP: Homomorphic Encryption-based Dynamic Adaptive Parameter Optimization for Statistical Computation
Yun-Soo Park, Hyunmin Choi, Hyoungshick Kim +1
Homomorphic encryption (HE) enables privacy-preserving analytics but remains hindered by high computational overhead. We find that the inverse square root-a key primitive in many s…
PP-STAT: An Efficient Privacy-Preserving Statistical Analysis Framework using Homomorphic Encryption
Hyunmin Choi
With the widespread adoption of cloud computing, the need for outsourcing statistical analysis to third-party platforms is growing rapidly. However, handling sensitive data such as…
Blind-Match: Efficient Homomorphic Encryption-Based 1:N Matching for Privacy-Preserving Biometric Identification
Hyunmin Choi, Jiwon Kim, Chiyoung Song +2
We present Blind-Match, a novel biometric identification system that leverages homomorphic encryption (HE) for efficient and privacy-preserving 1:N matching. Blind-Match introduces…
UniHENN: Designing Faster and More Versatile Homomorphic Encryption-based CNNs without im2col
Hyunmin Choi, Jihun Kim, Seungho Kim +4
Homomorphic encryption (HE) enables privacy-preserving deep learning by allowing computations on encrypted data without decryption. However, deploying convolutional neural networks…
Blind-Touch: Homomorphic Encryption-Based Distributed Neural Network Inference for Privacy-Preserving Fingerprint Authentication
Hyunmin Choi, Simon Woo, Hyoungshick Kim
Fingerprint authentication is a popular security mechanism for smartphones and laptops. However, its adoption in web and cloud environments has been limited due to privacy concerns…