Boreas: Fully Anonymous Sealed-Bid Auction
With the rise of e-commerce, sealed-bid auctions are widely used in various online scenarios. In auctions, bidders’ bids and participants’ identities are considered critical private information. However, existing works either only achieve bid privacy or fail to provide complete protection of identity. In this work, we propose the first sealed-bid auction scheme that achieves both bid privacy and identity privacy, called <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">Boreas</i>. We propose three fundamental protocols as the building blocks. In particular, <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">anonymous submission</i> enables sellers to submit items anonymously, <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">oblivious bidding</i> and <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">locker transaction</i> enable the seller and the winner to confirm the auction results and complete the transaction without knowing each other’s identity. Meanwhile, we formally define the security goal of identity privacy and formalize a new security property called: <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">fully anonymous</i>. We prove the security of our scheme in the semi-honest adversary model. We implement Boreas and run experiments comparing its performance against existing schemes. Our experiments show that Boreas improves computation time by 12.6% and reduces communication costs by 10<sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">3</sup>× in handling a large-scale auction, while offering stronger security guarantee.
Authors
- Kun He (ORCID: https://orcid.org/0000-0003-3472-419X)
- Min Shi (ORCID: https://orcid.org/0000-0001-9922-2153)
- Meng Jia (ORCID: https://orcid.org/0000-0003-3623-3490)
- Jing Chen (ORCID: https://orcid.org/0000-0002-7212-5297)
- Ruiying Du (ORCID: https://orcid.org/0000-0002-3634-3385)
- Zhongzi Huang (ORCID: https://orcid.org/0009-0000-4338-8138)
- Erjun Zhou (ORCID: https://orcid.org/0009-0001-3831-7789)
Institutions
- Wuhan University (CN)
Publication Details
- Journal
- IEEE Transactions on Information Forensics and Security
- Published
- 2025-01-01
- DOI
- https://doi.org/10.1109/tifs.2025.3593063
- Primary Topic
- Law, Economics, and Judicial Systems
- Type
- article
- Field-Weighted Citation Impact
- 0.00
Funders
- National Natural Science Foundation of China