Yue Huang (Tsinghua University), Xin Wang (Tsinghua University and State Key Laboratory of Cryptography and Digital Economy Security), Haibin Zhang (Yangtze Delta Region Institute of Tsinghua University, Zhejiang), Sisi Duan (Tsinghua University, Zhongguancun Laboratory, Shandong Institute of Blockchains and State Key Laboratory of Cryptography and Digital Economy Security)

Conventional Byzantine fault-tolerant protocols focus on the workflow within a group of nodes. In recent years, many applications of consensus involve communication across groups. Examples include communication between infrastructures running replicated state machine, sharding-based protocols, and cross-chain bridges. Unfortunately, little effort has been made to model the properties for communication across groups.

In this work, we propose a new primitive called cross-consensus reliable broadcast (XRBC). The XRBC primitive models the security properties of communication between two groups, where at least one group executes a consensus protocol. We provide three constructions of XRBC under varying assumptions and present three applications for our XRBC protocols: a cross-shard coordination protocol via a case study of Reticulum (NDSS 2024), a protocol for cross-shard transactions via a case study of Chainspace (NDSS 2018), and a solution for cross-chain bridge. Our evaluation results show that our protocols are highly efficient and benefit different applications. For example, in our case study on Reticulum, our approach achieves 61.16% lower latency than the vanilla approach.

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Yue Liu (Southeast University), Zexiang Zhang (National University of Defense Technology), Jiaxun Zhu (Zhejiang University), Hao Zheng (Independent Researcher), Jiaqing Huang (Independent Researcher), Wenbo Shen (Zhejiang University), Gaoning Pan (Hangzhou Dianzi University), Yuliang Lu (National University of Defense Technology), Min Zhang (National University of Defense Technology), Zulie Pan (National University of Defense Technology), Guang Cheng…

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Filipo Sharevski (DePaul University), Jennifer Vander Loop (DePaul University), Sarah Ferguson (DePaul University), Viktorija Paneva (LMU Munich)

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Xue Tan (Institute of Big Data, Fudan University, Shanghai, China and College of Computer Science and Artificial Intelligence, Fudan University, Shanghai, China), Hao Luan (Institute of Big Data, Fudan University, Shanghai, China and College of Computer Science and Artificial Intelligence, Fudan University, Shanghai, China), Mingyu Luo (Institute of Big Data, Fudan University, Shanghai, China and…

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