Hydra

Support Dynamic BFT With Weaker Assumptions and Explicit Request Handling

Journal Article (2026)
Author(s)

Xuyang Liu (The University of Auckland, Beijing Institute of Technology)

Zijian Zhang (Beijing Institute of Technology)

Zhen Li (Beijing Institute of Technology)

Haibo Sun (Beijing Institute of Technology)

Meng Li (Hefei University of Technology, Beijing University of Posts and Telecommunications)

Jing Sun (The University of Auckland)

Jiamou Liu (The University of Auckland)

Yong Liu (Qianxin Technology Group Company)

Mauro Conti (University of Padua, TU Delft - Electrical Engineering, Mathematics and Computer Science)

More Authors (External organisation)

Research Group
Cyber Security
DOI related publication
https://doi.org/10.1109/TDSC.2025.3647269 Final published version
More Info
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Publication Year
2026
Language
English
Research Group
Cyber Security
Journal title
IEEE Transactions on Dependable and Secure Computing
Issue number
3
Volume number
23
Pages (from-to)
4481-4497
Downloads counter
4
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Abstract

This paper presents Hydra, a dynamic BFT protocol that allows replicas to join and leave the system dynamically. It addresses the limitations of traditional static BFTs in managing membership changes and can be used to simplify the implementation of many features in modern blockchain applications. Hydra relies on weaker assumptions to achieve standard properties compared to the existing solution Dyno and introduces a configuration auto-transition protocol to ensure liveness. Through temporary configurations and explicitly defined replica responsibilities for request handling, Hydra pipelines membership requests alongside regular requests and realizes clarity, achieving a more efficient and smoother configuration transitions. It also employs a non-blocking configuration discovery mechanism, enabling new replicas to participate in consensus quickly. We formally prove Hydra's correctness under the dynamic BFT model. Experimental results demonstrate Hydra's ability to maintain throughput fluctuations within 5% during various replica join and leave scenarios, outperforming Dyno and existing BFT system supporting reconfiguration in both stability and efficiency. Hydra effectively manages scenarios that Dyno circumvents with stronger assumptions and quickly restores throughput to normal levels.

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File under embargo until 29-06-2026