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

File Hijacking Vulnerability: The Elephant in the Room

Chendong Yu (Institute of Information Engineering, Chinese Academy of Sciences and School of Cyber Security, University of Chinese Academy of Sciences), Yang Xiao (Institute of Information Engineering, Chinese Academy of Sciences and School of Cyber Security, University of Chinese Academy of Sciences), Jie Lu (Institute of Computing Technology of the Chinese Academy of Sciences), Yuekang…

Read More

You Can Use But Cannot Recognize: Preserving Visual Privacy...

Qiushi Li (Tsinghua University), Yan Zhang (Tsinghua University), Ju Ren (Tsinghua University), Qi Li (Tsinghua University), Yaoxue Zhang (Tsinghua University)

Read More

WIP: Security Vulnerabilities and Attack Scenarios in Smart Home...

Haoqiang Wang (Chinese Academy of Sciences, University of Chinese Academy of Sciences, Indiana University Bloomington), Yichen Liu (Indiana University Bloomington), Yiwei Fang, Ze Jin, Qixu Liu (Chinese Academy of Sciences, University of Chinese Academy of Sciences, Indiana University Bloomington), Luyi Xing (Indiana University Bloomington)

Read More

Automatic Adversarial Adaption for Stealthy Poisoning Attacks in Federated...

Torsten Krauß (University of Würzburg), Jan König (University of Würzburg), Alexandra Dmitrienko (University of Wuerzburg), Christian Kanzow (University of Würzburg)

Read More