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cs.IT2025★ 1 cited
Mutual Information Bounds in the Shuffle Model
Pengcheng Su, Haibo Cheng, Ping Wang
The shuffle model enhances privacy by anonymizing users' reports through random permutation. This paper presents the first systematic study of the single-message shuffle model from…
cs.CR2025
Bayesian Advantage of Re-Identification Attack in the Shuffle Model
Pengcheng Su, Haibo Cheng, Ping Wang
The shuffle model, which anonymizes data by randomly permuting user messages, has been widely adopted in both cryptography and differential privacy. In this work, we present the fi…
cs.CR2025
Decomposition-Based Optimal Bounds for Privacy Amplification via Shuffling
Pengcheng Su, Haibo Cheng, Ping Wang
Shuffling has been shown to amplify differential privacy guarantees, enabling a more favorable privacy-utility trade-off. To characterize and compute this amplification, two fundam…