39 citations · 39 across the 1 of their papers we have counts for
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cs.CR2025
IDFace: Face Template Protection for Efficient and Secure Identification
Sunpill Kim, Seunghun Paik, Chanwoo Hwang +3
As face recognition systems (FRS) become more widely used, user privacy becomes more important. A key privacy issue in FRS is protecting the user's face template, as the characteri…
cs.CR2024
HETAL: Efficient Privacy-preserving Transfer Learning with Homomorphic Encryption
Seewoo Lee, Garam Lee, Jung Woo Kim +2
Transfer learning is a de facto standard method for efficiently training machine learning models for data-scarce problems by adding and fine-tuning new classification layers to a m…
cs.CR2019★ 39 cited
Collecting and Analyzing Multidimensional Data with Local Differential Privacy
Ning Wang, Xiaokui Xiao, Yin Yang +5
Local differential privacy (LDP) is a recently proposed privacy standard for collecting and analyzing data, which has been used, e.g., in the Chrome browser, iOS and macOS. In LDP,…