发表机构
University of Bordeaux, Bordeaux-INP, CNRS-LaBRI（波尔多大学，波尔多国立理工学院，法国国家科学研究中心-拉布里实验室）
机构由 AI 辅助整理，请以论文原文为准。AI 中文总结
AUPE提出首个协作式拜占庭容错对等采样协议，利用可信节点消除偏差，在10,000节点模拟中优于现有方案，即使面对26%恶意节点仍保持近乎完美韧性。
AI 中文摘要
对等采样是分布式系统中的关键原语，用于在无许可区块链系统等大规模场景中管理覆盖网络和传播信息。其目的是维护并定期更新整个系统成员关系的本地部分快照（即视图）。这些协议经常成为恶意行为者的攻击目标，他们试图破坏更高级别的协议。通常，控制一组拜占庭节点的对手试图通过增加其在诚实节点视图中的代表性，来操纵合法节点对拜占庭节点存在的感知。虽然最先进的拜占庭容错对等采样协议缓解了这种偏差，但随着恶意节点数量的增加，其有效性显著下降。本文介绍了AUPE，这是首个协作式拜占庭容错对等采样协议，它利用可信节点（如Intel的SGX功能设备）的存在，协作跟踪系统中标识符的传播，并在本地消除拜占庭节点的代表性偏差。使用10,000个节点的模拟表明，AUPE优于最先进的解决方案，即使面对控制26%节点的对手，也能实现近乎完美的韧性。总体而言，通过仅包含10%的可信节点，AUPE将BRAHMS的容错能力提高了高达60%，同时限制了对手攻击的影响，即使对手拥有高达40%的节点。
英文摘要
Peer sampling is a crucial primitive in distributed systems, used to manage overlays and disseminate information in large-scale scenarios such as permissionless blockchain systems. Its purpose is to maintain and regularly update a local and partial snapshot, or view, of the complete system's membership. These protocols are often targeted by malicious actors who aim to disrupt higher-level protocols. Typically, an adversary who controls a set of byzantine nodes attempts to manipulate how legitimate nodes perceive the presence of byzantine ones by increasing their representation in the view of honest nodes. While state-of-the-art byzantine-tolerant peer sampling protocols mitigate this bias, their effectiveness decreases significantly as the number of malicious nodes increases. This paper introduces AUPE, the first collaborative Byzantine-tolerant peer sampling protocol that leverages the presence of trusted nodes, such as Intel's SGX capable devices, to collaboratively track the spread of identifiers in the system and locally debias the representation of byzantine nodes. Simulations with 10,000 nodes demonstrate that AUPE outperforms state-of-the-art solutions, achieving nearperfect resilience even when faced with an adversary controlling 26% of the nodes. Overall, by including as few as 10% of trusted nodes, AUPE increases the tolerance of BRAHMS by up to 60% while limiting the impact of the adversary's attack, even when possessing up to 40% of the nodes.
Journal refInternational Symposium on Network Computing and Applications NCA, Oct 2024, Bertinoro (FC), Italy. pp.17-24
