计算机科学 ›› 2022, Vol. 49 ›› Issue (1): 328-335.doi: 10.11896/jsjkx.201200118

• 信息安全 • 上一篇    下一篇

基于DPoS共识机制的区块链社区演化的可视分析方法

温啸林, 李长林, 张馨艺, 刘尚松, 朱敏   

  1. 四川大学计算机学院 成都610065
  • 收稿日期:2020-12-11 修回日期:2021-04-23 出版日期:2022-01-15 发布日期:2022-01-18
  • 通讯作者: 朱敏(zhumin@scu.edu.cn)
  • 作者简介:wenxiaolin@stu.edu.scu.cn
  • 基金资助:
    成都市技术创新研发项目(2019-YF05-02121-SN)

Visual Analysis Method of Blockchain Community Evolution Based on DPoS Consensus Mechanism

WEN Xiao-lin, LI Chang-lin, ZHANG Xin-yi, LIU Shang-song, ZHU Min   

  1. College of Computer Science,Sichuan University,Chengdu 610065,China
  • Received:2020-12-11 Revised:2021-04-23 Online:2022-01-15 Published:2022-01-18
  • About author:WEN Xiao-lin,born in 1998,postgra-duate,is a member of China Computer Federation.His main research interests include information visualization and visual analytics.
    ZHU Min,born in 1971,Ph.D,professor,Ph.D supervisor,is a member of China Computer Federation.Her main research interests include information visualization,visual analytics and bioinformatics.
  • Supported by:
    Chengdu Science and Technology Bureau,China(2019-YF05-02121-SN).

摘要: DPoS(股权授权证明)是当前主流区块链共识机制之一,独特的节点竞选机制使其形成不断演化的区块链社区。对区块链社区演化模式进行分析可以发现共识机制的潜在风险,具有十分重要的研究意义。针对DPoS共识机制区块链数据,提出了一种新颖的共识机制效能组合分析策略,面向区块链社区演化模式,提出了一种多角度探索的可视分析方法。首先,量化了节点排名变化前后工作完成度与投票排名的差异,对共识机制的选择效能和激励效能进行组合分析;然后,针对共识机制组合效能、节点地域分布演化和节点间差异比较等方面设计可视化视图与交互手段;最后,基于EOS主链真实数据设计实现基于DPoS共识机制的区块链社区演化可视分析系统,并通过案例研究和专家评估验证所提方法的可用性及有效性。

关键词: DPoS, 共识机制, 可视分析, 区块链, 社区演化

Abstract: DPoS (delegated proof of stake) is one of the current mainstream blockchain consensus mechanisms,and the unique node election mechanism makes it form an evolving blockchain community.Analyzing the evolution model of the blockchain community can discover the potential risks of the consensus mechanism,which has very important research significance.For the DPoS consensus mechanism blockchain data,a novel combination analysis method of the consensus mechanism effectiveness is proposed,and a set of visual analysis methods are designed to help users analyze the evolutionary model of the blockchain community from multiple angles.First,it quantifies the difference between the degree of completion of the work and the voting ranking before and after the node ranking change and analyzes the selection efficiency and incentive efficiency of the consensus mechanism;then,it focuses on the combined efficiency of the consensus mechanism,the evolution of the geographical distribution of nodes,and the comparison of the evolutionary differences between nodes and designs visual views and interactive means;finally,it designs and implements a visual analysis system of blockchain community evolution based on the DPoS consensus mechanism based on the real data of the EOS main chain and verifies the usability and effectiveness of this method through case studies and expert evaluation.

Key words: Blockchain, Community evolution, Consensus mechanism, DPoS, Visual analysis

中图分类号: 

  • TP391.41
[1]陈为,沈则潜,陶煜波.数据可视化(第2版)[M].北京:电子工业出版社,2019.
[2]ZHENG Z,XIE S,DAI H N,et al.Blockchain Challenges and Opportunities:A survey[J].International Journal of Web and Grid Services,2018,14(4):352-375.
[3]BANO S,SONNINO A,Al-BASSAM M,et al.SoK:Consensus in the Age of Blockchains[C]//Proceedings of the 1st ACM Conference on Advances in Financial Technologies.2019:183-198.
[4]ZOHAR A.Securing and Scaling Cryptocurrencies[C]//Twenty-Sixth International Joint Conference on Artificial Intelligence.2017:5161-5165.
[5]FERDOUS M S,CHOWDHURY M J M,HOQUE M A,et al.Blockchain Consensus Algorithms:A Survey[J].arXiv:2001.07091,2020.
[6]GUO S T,WANG R J,ZHANG F L.Summary of Principle and Application of Blockchain[J].Computer Science,2021,48(2):271-281.
[7]TAN S P,YANG C.Research and Improvement of Blockchain's DPoS Consensus Mechanism[J].Modern Computer (Professio-nal Edition),2019(6):4.
[8]HUANG J C,XU X H,WANG S C.Improved Scheme of Dele-gated Proof of Stake Consensus Mechanism[J].Journal of Computer Applications,2019,39(7):2162-2167.
[9]JI Y X,HUANG J H,WANG Z,et al.Improved PBFT Consensus Algorithm Based on Trust Matching[J].Computer Science,2021,48(2):303-310.
[10]CHEN M R,LIN Y,LAN W,et al.Improvement of DPoS Consensus Mechanism Based on Positive Incentive[J].Computer Science,2020,47(2):269-275.
[11]TOVANICH N,HEULOT N,FEKETE J D,et al.Visualization of Blockchain Data:A Systematic Review[J].IEEE Transactions on Visualization and Computer Graphics,2019,27(7):3135-3152.
[12]BATTISTA G D,DONATO V D,PATRIGNANI M,et al.Bit-coneview:Visualization of Flows in the Bitcoin Transaction Graph[C]//Visualization for Cyber Security.IEEE,2015:1-8.
[13]DAN M G,BIRCH D,AKROYD D,et al.Visualizing Dynamic Bitcoin Transaction Patterns[J].Big Data,2016,4(2):109-119.
[14]GAULDIE D,LANGEVIN S,SCHRETLEN P,et al.Louvain Clustering for Big Data Graph Visual Analytics[C]//IEEE Visweek 2013.IEEE,2013.
[15]ISENBERG P,KINKELDEY C,FEKETE J D.Exploring entity behavior on the bitcoin blockchain [C]//VIS 2017-IEEE Conference on Visualization.2017:1-2.
[16]SUN Y,XIONG H,YIU S,et al.BitVis:An Interactive Visua-lization System for Bitcoin Accounts Analysis[C]//2019 Crypto Valley Conference on Blockchain Technology (CVCBT).IEEE,2019:21-25.
[17]YUE X W,SHU X,ZHU X,et al.Bitextract:Interactive Visua-lization for Extracting Bitcoin Exchange Intelligence[J].IEEE Transactions on Visualization and Computer Graphics,2018,25(1):162-171.
[18]CHAWATHE S.Monitoring Blockchains with Self-OrganizingMaps[C]//2018 17th IEEE International Conference On Trust,Security And Privacy In Computing And Communications/12th IEEE International Conference On Big Data Science And Engineering (TrustCom/BigDataSE).IEEE,2018:1870-1875.
[19]NORVILL R,PONTIVEROS B B F,STATE R,et al.Visual Emulation for Ethereum's Virtual Machine[C]//NOMS 2018-2018 IEEE/IFIP Network Operations and Management Symposium.IEEE,2018:1-4.
[20]AHMED M,SHUMAILOV I,ANDERSON R.Tendrils ofCrime:Visualizing the Diffusion of Stolen Bitcoins[C]//International Workshop on Graphical Models for Security.Springer,Cham,2018:1-12.
[21]BISTARELLI S,SANTINI F.Go with the-Bitcoin-Flow,withVisual Analytics[C]//Proceedings of the 12th International Conference on Availability,Reliability and Security.2017:1-6.
[22]OGGIER F,PHETSOUVANH S,DATTA A.BiVA:Bitcoinnetwork visualization & analysis[C]//2018 IEEE International Conference on Data Mining Workshops (ICDMW).IEEE,2018:1469-1474.
[23]KUZUNO H,KARAM C.Blockchain explorer:An AnalyticalProcess and Investigation Environment for Bitcoin[C]//2017 APWG Symposium on Electronic Crime Research (eCrime).IEEE,2017:9-16.
[24]KINKELDEY C,FEKETE J D,BLASCHEK T,et al.Visualizing and Analyzing Entity Activity on the Bitcoin Network[J].arXiv:1912.08101,2019.
[25]BOGNER A.Seeing is Understanding:Anomaly Detection inBlockchains with Visualized Features[C]//Proceedings of the 2017 ACM International Joint Conference on Pervasive and Ubiquitous Computing and Proceedings of the 2017 ACM International Symposium on Wearable Computers.2017:5-8.
[26]ZHONG Z,WEI S,ZHAO Y,et al.SilkViser:A Visual Explorer of Blockchain-based Cryptocurrency Transaction Data[J].ar-Xiv:2009.02651,2020.
[1] 王子凯, 朱健, 张伯钧, 胡凯.
区块链与智能合约并行方法研究与实现
Research and Implementation of Parallel Method in Blockchain and Smart Contract
计算机科学, 2022, 49(9): 312-317. https://doi.org/10.11896/jsjkx.210800102
[2] 李博, 向海昀, 张宇翔, 廖浩德.
面向食品溯源场景的PBFT优化算法应用研究
Application Research of PBFT Optimization Algorithm for Food Traceability Scenarios
计算机科学, 2022, 49(6A): 723-728. https://doi.org/10.11896/jsjkx.210800018
[3] 周航, 姜河, 赵琰, 解相朋.
适用于各单元共识交易的电力区块链系统优化调度研究
Study on Optimal Scheduling of Power Blockchain System for Consensus Transaction ofEach Unit
计算机科学, 2022, 49(6A): 771-776. https://doi.org/10.11896/jsjkx.210600241
[4] 傅丽玉, 陆歌皓, 吴义明, 罗娅玲.
区块链技术的研究及其发展综述
Overview of Research and Development of Blockchain Technology
计算机科学, 2022, 49(6A): 447-461. https://doi.org/10.11896/jsjkx.210600214
[5] 高健博, 张家硕, 李青山, 陈钟.
RegLang:一种面向监管的智能合约编程语言
RegLang:A Smart Contract Programming Language for Regulation
计算机科学, 2022, 49(6A): 462-468. https://doi.org/10.11896/jsjkx.210700016
[6] 毛典辉, 黄晖煜, 赵爽.
符合监管合规性的自动合成新闻检测方法研究
Study on Automatic Synthetic News Detection Method Complying with Regulatory Compliance
计算机科学, 2022, 49(6A): 523-530. https://doi.org/10.11896/jsjkx.210300083
[7] 王思明, 谭北海, 余荣.
面向6G可信可靠智能的区块链分片与激励机制
Blockchain Sharding and Incentive Mechanism for 6G Dependable Intelligence
计算机科学, 2022, 49(6): 32-38. https://doi.org/10.11896/jsjkx.220400004
[8] 孙浩, 毛瀚宇, 张岩峰, 于戈, 徐石成, 何光宇.
区块链跨链技术发展及应用
Development and Application of Blockchain Cross-chain Technology
计算机科学, 2022, 49(5): 287-295. https://doi.org/10.11896/jsjkx.210800132
[9] 阳真, 黄松, 郑长友.
基于区块链与改进CP-ABE的众测知识产权保护技术研究
Study on Crowdsourced Testing Intellectual Property Protection Technology Based on Blockchain and Improved CP-ABE
计算机科学, 2022, 49(5): 325-332. https://doi.org/10.11896/jsjkx.210900075
[10] 任畅, 赵洪, 蒋华.
一种量子安全拜占庭容错共识机制
Quantum Secured-Byzantine Fault Tolerance Blockchain Consensus Mechanism
计算机科学, 2022, 49(5): 333-340. https://doi.org/10.11896/jsjkx.210400154
[11] 冯了了, 丁滟, 刘坤林, 马科林, 常俊胜.
区块链BFT共识算法研究进展
Research Advance on BFT Consensus Algorithms
计算机科学, 2022, 49(4): 329-339. https://doi.org/10.11896/jsjkx.210700011
[12] 王鑫, 周泽宝, 余芸, 陈禹旭, 任昊文, 蒋一波, 孙凌云.
一种面向电能量数据的联邦学习可靠性激励机制
Reliable Incentive Mechanism for Federated Learning of Electric Metering Data
计算机科学, 2022, 49(3): 31-38. https://doi.org/10.11896/jsjkx.210700195
[13] 张潆藜, 马佳利, 刘子昂, 刘新, 周睿.
以太坊Solidity智能合约漏洞检测方法综述
Overview of Vulnerability Detection Methods for Ethereum Solidity Smart Contracts
计算机科学, 2022, 49(3): 52-61. https://doi.org/10.11896/jsjkx.210700004
[14] 杨昕宇, 彭长根, 杨辉, 丁红发.
基于演化博弈的理性拜占庭容错共识算法
Rational PBFT Consensus Algorithm with Evolutionary Game
计算机科学, 2022, 49(3): 360-370. https://doi.org/10.11896/jsjkx.210900110
[15] 范家幸, 王志伟.
基于门限环签名的分级匿名表决方案
Hierarchical Anonymous Voting Scheme Based on Threshold Ring Signature
计算机科学, 2022, 49(1): 321-327. https://doi.org/10.11896/jsjkx.201000032
Viewed
Full text


Abstract

Cited

  Shared   
  Discussed   
No Suggested Reading articles found!