Sourav Das (University of Illinois at Urbana-Champaign), Zhuolun Xiang (Aptos), Ling Ren (University of Illinois at Urbana-Champaign)

The $q$-Strong Diffie-Hellman~($q$-SDH) parameters are foundational to efficient constructions of many cryptographic primitives such as zero-knowledge succinct non-interactive argument of knowledge, polynomial/vector commitments, verifiable secret sharing, and randomness beacon. The only existing method to generate these parameters securely is highly sequential, requires strong network synchrony assumptions, and has very high communication and computation cost. For example, to generate parameters for any given $q$, each party incurs a communication cost of $Omega(nq)$ and requires $Omega(n)$ rounds. Here $n$ is the number of parties in the secure multiparty computation protocol. Since $q$ is typically large, i.e., on the order of billions, the cost is highly prohibitive.

In this paper, we present a distributed protocol to generate $q$-SDH parameters in an asynchronous network. In a network of $n$ parties, our protocol tolerates up to one-third of malicious parties. Each party incurs a communication cost of $O(q + n^2log q)$ and the protocol finishes in $O(log q + log n)$ expected rounds. We provide a rigorous security analysis of our protocol. We implement our protocol and evaluate it with up to 128 geographically distributed parties. Our evaluation illustrates that our protocol is highly scalable and results in a 2-6$times$ better runtime and 4-13$times$ better per-party bandwidth usage compared to the state-of-the-art synchronous protocol for generating $q$-SDH parameters.

View More Papers

Cyclops: Binding a Vehicle’s Digital Identity to its Physical...

Lewis William Koplon, Ameer Ghasem Nessaee, Alex Choi (University of Arizona, Tucson), Andres Mentoza (New Mexico State University, Las Cruces), Michael Villasana, Loukas Lazos, Ming Li (University of Arizona, Tucson)

Read More

FP-Fed: Privacy-Preserving Federated Detection of Browser Fingerprinting

Meenatchi Sundaram Muthu Selva Annamalai (University College London), Igor Bilogrevic (Google), Emiliano De Cristofaro (University of California, Riverside)

Read More

MirageFlow: A New Bandwidth Inflation Attack on Tor

Christoph Sendner (University of Würzburg), Jasper Stang (University of Würzburg), Alexandra Dmitrienko (University of Würzburg), Raveen Wijewickrama (University of Texas at San Antonio), Murtuza Jadliwala (University of Texas at San Antonio)

Read More

Pencil: Private and Extensible Collaborative Learning without the Non-Colluding...

Xuanqi Liu (Tsinghua University), Zhuotao Liu (Tsinghua University), Qi Li (Tsinghua University), Ke Xu (Tsinghua University), Mingwei Xu (Tsinghua University)

Read More