Paper 2025/1189
Performance and Privacy: A Low-Latency Secure Anonymous Authentication Protocol with OPRF
Abstract
erforming privacy-preserving queries, particularly anonymous authentication, against large-scale datasets presents critical tradeoffs between security, latency, scalability. Existing cryptographic solutions often impose linear computation or communication overheads. This paper introduces a novel, efficient protocol for secure anonymous authentication, uniquely combining matrix partitioning via hash prefixes with Oblivious Pseudorandom Functions in a three-server semi-honest model. Crucially, compared to our previous work published at TrustCom 2024, this enhanced protocol eliminates the dependency on a designated fully trusted server, achieving security when any single server is corrupted. Furthermore, our protocol demonstrates significant performance improvements over current state-of-the-art methods. It achieves sub-linear online communication complexity. Evaluations show that for datasets of size 𝑚 ≈ 106 , our protocol reduces online communication by at least 30% compared to other sub-linear schemes, while maintaining competitive online computation times. Security is proven via simulation, and comprehensive experiments confirm practicality for datasets up to 𝑚 = 10^8
Metadata
- Available format(s)
-
PDF
- Category
- Cryptographic protocols
- Publication info
- Preprint.
- Keywords
- Privacy-preserving authenticationOblivious pseudorandom functionBloom filter
- Contact author(s)
-
hu_121421 @ dgut edu cn
793615497 @ gq com
liyin @ dgut edu cn - History
- 2025-06-27: approved
- 2025-06-25: received
- See all versions
- Short URL
- https://ia.cr/2025/1189
- License
-
CC BY-NC
BibTeX
@misc{cryptoeprint:2025/1189,
author = {Wenjv Hu and Yanping Ye and Yin Li},
title = {Performance and Privacy: A Low-Latency Secure Anonymous Authentication Protocol with {OPRF}},
howpublished = {Cryptology {ePrint} Archive, Paper 2025/1189},
year = {2025},
url = {https://eprint.iacr.org/2025/1189}
}
