@inproceedings{oai:ipsj.ixsq.nii.ac.jp:00228652,
 author = {Seng, Pei Lie and Satoshi, Hasegaw and Tsubasa, Takahash and Seng, Pei Liew and Satoshi, Hasegawa and Tsubasa, Takahashi},
 book = {コンピュータセキュリティシンポジウム2023論文集},
 month = {Oct},
 note = {We study a protocol for distributed computation called shuffled check-in, which achieves strong privacy guarantees without requiring any further trust assumptions beyond a trusted shuffler. Leveraging differential privacy, we show that shuffled check-in achieves tight privacy guarantees through privacy amplification, with a novel analysis based on R'enyi differential privacy that improves privacy accounting over existing work. We also introduce a numerical approach to track the privacy of generic shuffling mechanisms, including Gaussian mechanism, which is the first evaluation of a generic mechanism under the distributed setting within the local/shuffle model in the literature. Empirical studies are also given to demonstrate the efficacy of the proposed approach., We study a protocol for distributed computation called shuffled check-in, which achieves strong privacy guarantees without requiring any further trust assumptions beyond a trusted shuffler. Leveraging differential privacy, we show that shuffled check-in achieves tight privacy guarantees through privacy amplification, with a novel analysis based on R'enyi differential privacy that improves privacy accounting over existing work. We also introduce a numerical approach to track the privacy of generic shuffling mechanisms, including Gaussian mechanism, which is the first evaluation of a generic mechanism under the distributed setting within the local/shuffle model in the literature. Empirical studies are also given to demonstrate the efficacy of the proposed approach.},
 pages = {275--281},
 publisher = {情報処理学会},
 title = {Privacy amplification via shuffled check-ins},
 year = {2023}
}