Practical Asynchronous Distributed Key Generation and Distributed Polynomial Sampling - Sourav Das
Channel: ConsensusLab
Date: 2023-06-16

Sourav Das (University of Illinois at Urbana-Champaign), Zhuolun Xiang (University of Illinois at Urbana-Champaign), Lefteris Kokoris-Kogias (IST Austria), Ling Ren (University of Illinois at Urbana-Champaign)

Distributed Key Generation (DKG) is a technique to bootstrap threshold cryptosystems without a trusted party. DKG is an essential building block to many decentralized protocols such as randomness beacons, threshold signatures, Byzantine consensus, and multiparty computation. While significant progress has been made recently, existing asynchronous DKG constructions are inefficient when the reconstruction threshold is larger than one-third of the total nodes. In this paper, we present a simple and concretely efficient asynchronous DKG (ADKG) protocol among 𝑛=3𝑡+1 nodes that can tolerate up to 𝑡 malicious nodes and support any reconstruction threshold ℓ≥𝑡. Our protocol has an expected 𝑂(𝜅𝑛3) communication cost, where 𝜅 is the security parameter, and only assumes the hardness of the Discrete Logarithm. The core ingredient of our ADKG protocol is an asynchronous protocol to secret share a random polynomial of degree ℓ≥𝑡, which has other applications, such as asynchronous proactive secret sharing and asynchronous multiparty computation. We implement our high-threshold ADKG protocol and evaluate it using a network of up to 128 geographically distributed nodes. Our evaluation shows that our high-threshold ADKG protocol reduces the running time by 90% and bandwidth usage by 80% over the state-of-the-art.

ConsensusDays 23 Session 1.1- Consensus Cryptography
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