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.

View More Papers

coucouArray ( [post_type] => ndss-paper [post_status] => publish [posts_per_page] => 4 [orderby] => rand [tax_query] => Array ( [0] => Array ( [taxonomy] => category [field] => id [terms] => Array ( [0] => 66 ) ) ) [post__not_in] => Array ( [0] => 13236 ) )

Faster Secure Comparisons with Offline Phase for Efficient Private...

Florian Kerschbaum (University of Waterloo), Erik-Oliver Blass (Airbus), Rasoul Akhavan Mahdavi (University of Waterloo)

Read More

RR: A Fault Model for Efficient TEE Replication

Baltasar Dinis (Instituto Superior Técnico (IST-ULisboa) / INESC-ID / MPI-SWS), Peter Druschel (MPI-SWS), Rodrigo Rodrigues (Instituto Superior Técnico (IST-ULisboa) / INESC-ID)

Read More

Analysing Adversarial Threats to Rule-Based Local-Planning Algorithms for Autonomous...

Andrew Roberts (Tallinn University of Technology), Mohsen Malayjerdi (Tallinn University of Technology), Mauro Bellone (Tallinn University of Technology), Olaf Maennel (The University of Adelaide), Ehsan Malayjerdi (Tallinn University of Technology)

Read More

PISE: Protocol Inference using Symbolic Execution and Automata Learning

Ron Marcovich, Orna Grumberg, Gabi Nakibly (Technion, Israel Institute of Technology)

Read More

Privacy Starts with UI: Privacy Patterns and Designer Perspectives in UI/UX Practice

Anxhela Maloku (Technical University of Munich), Alexandra Klymenko (Technical University of Munich), Stephen Meisenbacher (Technical University of Munich), Florian Matthes (Technical University of Munich)

Vision: Profiling Human Attackers: Personality and Behavioral Patterns in Deceptive Multi-Stage CTF Challenges

Khalid Alasiri (School of Computing and Augmented Intelligence Arizona State University), Rakibul Hasan (School of Computing and Augmented Intelligence Arizona State University)

From Underground to Mainstream Marketplaces: Measuring AI-Enabled NSFW Deepfakes on Fiverr

Mohamed Moustafa Dawoud (University of California, Santa Cruz), Alejandro Cuevas (Princeton University), Ram Sundara Raman (University of California, Santa Cruz)