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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…
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
An Information-theoretic Security Analysis of Honeyword
Pengcheng Su, Haibo Cheng, Wenting Li +1
Honeyword is a representative "honey" technique that employs decoy objects to mislead adversaries and protect the real ones. To assess the security of a Honeyword system, two metri…