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

Institutions

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

Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Boreas: Fully Anonymous Sealed-Bid Auction

Kun He, Min Shi, Meng Jia, Jing Chen et al.
IEEE Transactions on Information Forensics and Security
Law, Economics, and Judicial Systems
article

Boreas: Fully Anonymous Sealed-Bid Auction

Kun He, Min Shi, Meng Jia, Jing Chen, Ruiying Du, Zhongzi Huang, Erjun Zhou
article en

Abstract

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.

IEEE Transactions on Information Forensics and SecurityVol. 20
Wuhan University (CN)
National Natural Science Foundation of China
Openalex Percentile: Top 74%
Law, Economics, and Judicial Systems
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.