Mohsen Minaei (Visa Research), Ranjit Kumaresan (Visa Research), Andrew Beams (Visa Research), Pedro Moreno-Sanchez (IMDEA Software Institute, MPI-SP), Yibin Yang (Georgia Institute of Technology), Srinivasan Raghuraman (Visa Research and MIT), Panagiotis Chatzigiannis (Visa Research), Mahdi Zamani (Visa Research), Duc V. Le (Visa Research)

Blockchain auction plays an important role in the price discovery of digital assets (e.g. NFTs). However, despite their importance, implementing auctions directly on blockchains such as Ethereum incurs scalability issues. In particular, the on-chain transactions scale poorly with the number of bidders, leading to network congestion, increased transaction fees, and slower transaction confirmation time. This lack of scalability significantly hampers the ability of the system to handle large-scale, high-speed auctions that are common in today’s economy.

In this work, we build a protocol where an auctioneer can conduct sealed bid auctions that run entirely off-chain when parties behave honestly, and in the event that $k$ bidders deviate (e.g., do not open their sealed bid) from an $n$-party auction protocol, then the on-chain complexity is only $O(k)$. This improves over existing solutions that require $O(n)$ on-chain complexity, even if a single bidder deviates from the protocol. In the event of a malicious auctioneer, our protocol still guarantees that the auction will successfully terminate. We implement our protocol and show that it offers significant efficiency improvements compared to existing on-chain solutions. Our use of zero-knowledge Succinct Non-interactive ARgument of Knowledge for arithmetic (zkSnark) to achieve scalability also ensures that the on-chain contract and other participants do not acquire any information about the bidders’ identities and their respective bids, except for the winner and the winning bid amount.

View More Papers

CHAMELEOSCAN: Demystifying and Detecting iOS Chameleon Apps via LLM-Powered...

Hongyu Lin (Zhejiang University), Yicheng Hu (Zhejiang University), Haitao Xu (Zhejiang University), Yanchen Lu (Zhejiang University), Mengxia Ren (Zhejiang University), Shuai Hao (Old Dominion University), Chuan Yue (Colorado School of Mines), Zhao Li (Hangzhou Yugu Technology), Fan Zhang (Zhejiang University), Yixin Jiang (Electric Power Research Institute)

Read More

UsersFirst in Practice: Evaluating a User-Centric Threat Modeling Taxonomy...

Alexandra Xinran Li (Carnegie Mellon University), Tian Wang (University of Illinois Urbana-Champaign), Yu-Ju Yang (University of Illinois Urbana-Champaign), Miguel Rivera-Lanas (Carnegie Mellon University), Debeshi Ghosh (Carnegie Mellon University), Hana Habib (Carnegie Mellon University), Lorrie Cranor (Carnegie Mellon University), Norman Sadeh (Carnegie Mellon University)

Read More