Harry W. H. Wong (The Chinese University of Hong Kong), Jack P. K. Ma (The Chinese University of Hong Kong), Hoover H. F. Yin (The Chinese University of Hong Kong), Sherman S. M. Chow (The Chinese University of Hong Kong)

Threshold ECDSA recently regained popularity due to decentralized applications such as DNSSEC and cryptocurrency asset custody. Latest (communication-optimizing) schemes often assume all n or at least n' >= t participating users remain honest throughout the pre-signing phase, essentially degenerating to n'-out-of-n' multiparty signing instead of t-out-of-n threshold signing. When anyone misbehaves, all signers must restart from scratch, rendering prior computation and communication in vain. This hampers the adoption of threshold ECDSA in time-critical situations and confines its use to a small signing committee.

To mitigate such denial-of-service vulnerabilities prevalent in state-of-the-art, we propose a robust threshold ECDSA scheme that achieves the t-out-of-n threshold flexibility "for real" throughout the whole pre-signing and signing phases without assuming an honest majority. Our scheme is desirable when computational resources are scarce and in a decentralized setting where faults are easier to be induced. Our design features 4-round pre-signing, O(n) cheating identification, and self-healing machinery over distributive shares. Prior arts mandate abort after an O(n^2)-cost identification, albeit with 3-round pre-signing (Canetti et al., CCS '20), or O(n) using 6 rounds (Castagnos et al., TCS '23). Empirically, our scheme saves up to ~30% of the communication cost, depending on at which stage the fault occurred.

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Lightning Community Shout-Outs to:

(1) Jonathan Petit, Secure ML Performance Benchmark (Qualcomm) (2) David Balenson, The Road to Future Automotive Research Datasets: PIVOT Project and Community Workshop (USC Information Sciences Institute) (3) Jeremy Daily, CyberX Challenge Events (Colorado State University) (4) Mert D. Pesé, DETROIT: Data Collection, Translation and Sharing for Rapid Vehicular App Development (Clemson University) (5) Ning…

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Chongzhou Fang (University of California, Davis), Najmeh Nazari (University of California, Davis), Behnam Omidi (George Mason University), Han Wang (Temple University), Aditya Puri (Foothill High School, Pleasanton, CA), Manish Arora (LearnDesk, Inc.), Setareh Rafatirad (University of California, Davis), Houman Homayoun (University of California, Davis), Khaled N. Khasawneh (George Mason University)

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Matthew Revelle, Matt Parker, Kevin Orr (Kudu Dynamics)

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