Xuanji Meng (Tsinghua University), Xiao Sui (Shandong University), Zhaoxin Yang (Tsinghua University), Kang Rong (Blockchain Platform Division,Ant Group), Wenbo Xu (Blockchain Platform Division,Ant Group), Shenglong Chen (Blockchain Platform Division,Ant Group), Ying Yan (Blockchain Platform Division,Ant Group), Sisi Duan (Tsinghua University)

We present Rondo, a scalable and reconfiguration-friendly distributed randomness beacon (DRB) protocol in the partially synchronous model. Rondo is the first DRB protocol that is built from batched asynchronous verifiable secret sharing (bAVSS) and meanwhile avoids the high $O(n^3)$ message cost, where $n$ is the number of nodes. Our key contribution lies in the introduction of a new variant of bAVSS called batched asynchronous verifiable secret sharing with partial output (bAVSS-PO). bAVSS-PO is a weaker primitive than bAVSS but allows us to build a secure and more scalable DRB protocol. We propose a bAVSS-PO protocol Breeze. Breeze achieves the optimal $O(n)$ messages for the sharing stage and allows Rondo to offer better scalability than prior DRB protocols.
Additionally, to support the reconfiguration, we introduce Rondo-BFT, a dynamic and partially synchronous Byzantine fault-tolerant protocol inspired by Dyno (S&P 2022). Unlike Dyno, Rondo-BFT provides a communication pattern that generates randomness beacon output periodically, making it well-suited for DRB applications.

We implement our protocols and evaluate the performance on Amazon EC2 using up to 91 instances. Our evaluation results show that Rondo achieves higher throughput than existing works and meanwhile offers better scalability, where the performance does not degrade as significantly as $n$ grows.

View More Papers

Towards Establishing a Systematic Security Framework for Next Generation...

Tolga O. Atalay (A2 Labs LLC), Tianyuan Yu (UCLA), Lixia Zhang (UCLA), Angelos Stavrou (A2 Labs LLC)

Read More

Automated Mass Malware Factory: The Convergence of Piggybacking and...

Heng Li (Huazhong University of Science and Technology), Zhiyuan Yao (Huazhong University of Science and Technology), Bang Wu (Huazhong University of Science and Technology), Cuiying Gao (Huazhong University of Science and Technology), Teng Xu (Huazhong University of Science and Technology), Wei Yuan (Huazhong University of Science and Technology), Xiapu Luo (The Hong Kong Polytechnic University)

Read More

URVFL: Undetectable Data Reconstruction Attack on Vertical Federated Learning

Duanyi Yao (Hong Kong University of Science and Technology), Songze Li (Southeast University), Xueluan Gong (Wuhan University), Sizai Hou (Hong Kong University of Science and Technology), Gaoning Pan (Hangzhou Dianzi University)

Read More

Evaluating Machine Learning-Based IoT Device Identification Models for Security...

Eman Maali (Imperial College London), Omar Alrawi (Georgia Institute of Technology), Julie McCann (Imperial College London)

Read More