连续挖矿:比特币挖矿公平性的统计研究

Sheng-Nan Li, Zhao Yang, C. Tessone
{"title":"连续挖矿:比特币挖矿公平性的统计研究","authors":"Sheng-Nan Li, Zhao Yang, C. Tessone","doi":"10.1109/ICBC48266.2020.9169436","DOIUrl":null,"url":null,"abstract":"The Bitcoin system keeps its ledger consistent in a blockchain by solving cryptographic problems, in a method called \"Proof-of-Work\". The conventional wisdom asserts that the mining protocol is incentive-compatible. However, Eyal and Sirer in 2014 have discovered a mining attack strategy called selfish mining (SM), in which a miner (or a mining pool) publishes the blocks it mines selectively instead of immediately. SM strategy would have the impact of wasting resources of honest miners. Scholars proposed various extensions of the SM strategy and approaches to defense the SM attack. Whether selfish mining occurs in practice or not, has been subject of extensive debate. For the first time, in this paper we propose a method to identify selfish miners by detecting anomalies in the properties of consecutive blocks’ statistics. Furthermore, we extend our method to detect the mining cartels, in which miners secretly get together and share timely information. Our results provide evidence that these strategic behaviors take place in practice.","PeriodicalId":420845,"journal":{"name":"2020 IEEE International Conference on Blockchain and Cryptocurrency (ICBC)","volume":"28 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2020-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"17","resultStr":"{\"title\":\"Mining blocks in a row: A statistical study of fairness in Bitcoin mining\",\"authors\":\"Sheng-Nan Li, Zhao Yang, C. Tessone\",\"doi\":\"10.1109/ICBC48266.2020.9169436\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"The Bitcoin system keeps its ledger consistent in a blockchain by solving cryptographic problems, in a method called \\\"Proof-of-Work\\\". The conventional wisdom asserts that the mining protocol is incentive-compatible. However, Eyal and Sirer in 2014 have discovered a mining attack strategy called selfish mining (SM), in which a miner (or a mining pool) publishes the blocks it mines selectively instead of immediately. SM strategy would have the impact of wasting resources of honest miners. Scholars proposed various extensions of the SM strategy and approaches to defense the SM attack. Whether selfish mining occurs in practice or not, has been subject of extensive debate. For the first time, in this paper we propose a method to identify selfish miners by detecting anomalies in the properties of consecutive blocks’ statistics. Furthermore, we extend our method to detect the mining cartels, in which miners secretly get together and share timely information. Our results provide evidence that these strategic behaviors take place in practice.\",\"PeriodicalId\":420845,\"journal\":{\"name\":\"2020 IEEE International Conference on Blockchain and Cryptocurrency (ICBC)\",\"volume\":\"28 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2020-05-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"17\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2020 IEEE International Conference on Blockchain and Cryptocurrency (ICBC)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ICBC48266.2020.9169436\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2020 IEEE International Conference on Blockchain and Cryptocurrency (ICBC)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICBC48266.2020.9169436","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 17

摘要

比特币系统通过解决加密问题,以一种称为“工作量证明”的方法,在区块链中保持其分类账的一致性。传统观点认为,挖矿协议是激励兼容的。然而,Eyal和Sirer在2014年发现了一种名为“自私挖矿”(self mining, SM)的挖矿攻击策略,即矿工(或矿池)选择性地发布其挖出的区块,而不是立即发布。SM策略会造成诚实矿工资源的浪费。学者们提出了SM策略的各种扩展和防御SM攻击的方法。自私采矿在实践中是否存在,一直是广泛争论的主题。在本文中,我们首次提出了一种通过检测连续区块统计属性中的异常来识别自私矿工的方法。在此基础上,将该方法扩展到矿工秘密聚集并及时共享信息的挖矿卡特尔的检测中。我们的研究结果为这些战略行为在实践中发生提供了证据。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
查看原文
分享 分享
微信好友 朋友圈 QQ好友 复制链接
本刊更多论文
Mining blocks in a row: A statistical study of fairness in Bitcoin mining
The Bitcoin system keeps its ledger consistent in a blockchain by solving cryptographic problems, in a method called "Proof-of-Work". The conventional wisdom asserts that the mining protocol is incentive-compatible. However, Eyal and Sirer in 2014 have discovered a mining attack strategy called selfish mining (SM), in which a miner (or a mining pool) publishes the blocks it mines selectively instead of immediately. SM strategy would have the impact of wasting resources of honest miners. Scholars proposed various extensions of the SM strategy and approaches to defense the SM attack. Whether selfish mining occurs in practice or not, has been subject of extensive debate. For the first time, in this paper we propose a method to identify selfish miners by detecting anomalies in the properties of consecutive blocks’ statistics. Furthermore, we extend our method to detect the mining cartels, in which miners secretly get together and share timely information. Our results provide evidence that these strategic behaviors take place in practice.
求助全文
通过发布文献求助,成功后即可免费获取论文全文。 去求助
来源期刊
自引率
0.00%
发文量
0
期刊最新文献
Evaluation of Security and Performance of Master Node Protocol in the Bitcoin Peer-to-Peer Network Building Hybrid DApps using Blockchain Tactics -The Meta-Transaction Example FabricUnit: A Framework for Faster Execution of Unit Tests on Hyperledger Fabric Distributed Fractionalized Data Networks For Data Integrity Cross-chain Transactions
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
现在去查看 取消
×
提示
确定
0
微信
客服QQ
Book学术公众号 扫码关注我们
反馈
×
意见反馈
请填写您的意见或建议
请填写您的手机或邮箱
已复制链接
已复制链接
快去分享给好友吧!
我知道了
×
扫码分享
扫码分享
Book学术官方微信
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术
文献互助 智能选刊 最新文献 互助须知 联系我们:info@booksci.cn
Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。
Copyright © 2023 Book学术 All rights reserved.
ghs 京公网安备 11010802042870号 京ICP备2023020795号-1