On Private Data Collection of Hyperledger Fabric

Shan Wang, Ming Yang, Yue Zhang, Yan Luo, Tingjian Ge, Xinwen Fu, Wei Zhao
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引用次数: 14

Abstract

Hyperledger Fabric is a popular permissioned Blockchain framework for a consortium of organizations to develop Blockchain based applications and transact within the consortium. Hyperledger Fabric introduces a fine-grained access control mechanism called the private data collection (PDC), which allows private data to be shared by only a subset of participants. In this paper, we analyze PDC and show three classes of use cases in which misuse of Hyperledger Fabric features may endanger implemented Hyperledger Fabric systems. We present two groups of potential attacks including fake PDC results injection and PDC leakage against the misuse of the policy based consensus protocol. We use prototype systems to validate the discovered attacks. We also collected 6392 Hyprledger Fabric projects on GitHub and built a tool to statically analyse them. We find that 86.51% of the PDC related projects are potentially vulnerable to the fake PDC results injection attacks, and 91.67% have PDC leakage issues. We design new features for the Hyper-ledger Fabric framework to mitigate the attacks and show that the new features have minor impact on the system performance.
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关于超级账本结构的私有数据收集
Hyperledger Fabric是一个流行的许可区块链框架,用于组织联盟开发基于区块链的应用程序并在联盟内进行交易。Hyperledger Fabric引入了一种称为私有数据收集(PDC)的细粒度访问控制机制,该机制允许私有数据仅由一部分参与者共享。在本文中,我们分析了PDC,并展示了三种用例,在这些用例中,滥用Hyperledger Fabric特性可能危及已实现的Hyperledger Fabric系统。针对基于策略的共识协议的误用,提出了伪造PDC结果注入和PDC泄漏两组潜在攻击。我们使用原型系统来验证发现的攻击。我们还在GitHub上收集了6392个hyperledger Fabric项目,并构建了一个工具来静态分析它们。研究发现,86.51%的PDC相关项目存在伪造PDC结果注入攻击的潜在风险,91.67%存在PDC泄漏问题。我们为超级分类账结构框架设计了新功能来减轻攻击,并表明新功能对系统性能的影响很小。
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