论文标题

被池扭曲:在工作证明采矿中发现自私异常

Twisted by the Pools: Detection of Selfish Anomalies in Proof-of-Work Mining

论文作者

Li, Sheng-Nan, Campajola, Carlo, Tessone, Claudio J.

论文摘要

许多加密货币的核心是在工作证明技术上运行的分散验证网络。在这些系统中,验证是由所谓的矿工完成的,后者可以在解决计算困难问题后数字签名。传统观点通常认为该方案是安全和稳定的,因为矿工被激励遵循多数人的行为。但是,在实践中是否发生某些战略采矿行为仍然是一个主要问题。在本文中,我们通过关注安全威胁来瞄准这个问题:一种自私的采矿攻击,其中恶意矿工与没有立即揭示其新矿区的区块偏离了协议。我们提出了一项统计测试,以分析五种流行的加密货币的每个矿工的行为:比特币,莱特币,摩纳哥,以太坊和比特币现金。我们的方法基于这样的认识,即自私的采矿行为将在矿工连续的块发现的统计数据中引起可识别的异常。其次,我们应用基于启发式的地址聚类来提高这种行为的可检测性。我们发现在摩纳哥和比特币现金中发现异常的矿工存在明显的存在,并且在以太坊中的程度较小。最后,我们扩展了检测协调的自私采矿攻击的方法,在摩纳哥发现采矿卡特尔,矿工可能会秘密地共享有关新矿区的信息。我们的分析通过提供了上述战略采矿行为确实在实践中进行的第一个经验证据,从而有助于加密货币系统的安全研究。

The core of many cryptocurrencies is the decentralised validation network operating on proof-of-work technology. In these systems, validation is done by so-called miners who can digitally sign blocks once they solve a computationally-hard problem. Conventional wisdom generally considers this protocol as secure and stable as miners are incentivised to follow the behaviour of the majority. However, whether some strategic mining behaviours occur in practice is still a major concern. In this paper we target this question by focusing on a security threat: a selfish mining attack in which malicious miners deviate from protocol by not immediately revealing their newly mined blocks. We propose a statistical test to analyse each miner's behaviour in five popular cryptocurrencies: Bitcoin, Litecoin, Monacoin, Ethereum and Bitcoin Cash. Our method is based on the realisation that selfish mining behaviour will cause identifiable anomalies in the statistics of miner's successive blocks discovery. Secondly, we apply heuristics-based address clustering to improve the detectability of this kind of behaviour. We find a marked presence of abnormal miners in Monacoin and Bitcoin Cash, and, to a lesser extent, in Ethereum. Finally, we extend our method to detect coordinated selfish mining attacks, finding mining cartels in Monacoin where miners might secretly share information about newly mined blocks in advance. Our analysis contributes to the research on security in cryptocurrency systems by providing the first empirical evidence that the aforementioned strategic mining behaviours do take place in practice.

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