计算机科学 ›› 2021, Vol. 48 ›› Issue (11): 116-123.doi: 10.11896/jsjkx.210200134

• 区块链技术* 上一篇    下一篇

基于区块链的DApp数据与行为分析

胡腾1,2, 王艳平1, 张小松1, 牛伟纳1   

  1. 1 电子科技大学计算机科学与工程学院 成都611731
    2 中国工程物理研究院计算机应用研究所 四川 绵阳621900
  • 收稿日期:2021-02-22 修回日期:2021-05-29 出版日期:2021-11-15 发布日期:2021-11-10
  • 通讯作者: 张小松(johnsonzxs@uestc.edu.cn)
  • 作者简介:mailhuteng@gmail.com
  • 基金资助:
    国家自然科学基金(U19A2066);四川省科技计划项目-重点研发项目(2020YFG0294);成都市科技项目-重点研发支撑计划-重大科技应用示范项目(2019-YF09-00048-CG)

Data and Behavior Analysis of Blockchain-based DApp

HU Teng1,2, WANG Yan-ping1, ZHANG Xiao-song1, NIU Wei-na1   

  1. 1 School of Computer Science and Engineering,University of Electronic Science and Technology of China,Chengdu 611731,China
    2 Institute of Computer Application,China Academy of Engineering Physics,Mianyang,Sichuan 621900,China
  • Received:2021-02-22 Revised:2021-05-29 Online:2021-11-15 Published:2021-11-10
  • About author:HU Teng,born in 1988,Ph.D.His main research interests include cybersecurity-related issues with artificial intelligence,blockchain,and big data techno-logies.
    ZHANG Xiao-song,born in 1968,Ph.D,professor.His main research interests include software vulnerability analysis,program analysis,network security,and data security.
  • Supported by:
    National Natural Science Foundation of China (U19A2066),Sichuan Science and Technology Plan Projects-Key Research and Development Projects (2020YFG0294) and Chengdu Science and Technology Project-Key R & D Support Program-Major Science and Technology Application Demonstration Project (2019-YF09-00048-CG).

摘要: 区块链技术近年来发展迅速,很多组织和企业开始使用基于区块链和智能合约的去中心化应用(Decentralized Applications,DApp)来增强其信息系统的功能、安全性以及扩展新业务。但由于区块链和智能合约本身可能存在安全与性能问题,因此DApp也会带来新的问题。为了深入研究和分析DApp的数据与行为现象,从而帮助用户更好地应用区块链和DApp,首先收集了21类共2 565个DApp,并收集了这些DApp从2015年7月30日至2020年5月4日(约1 000万区块高度)的相关数据,共包括16 302个智能合约,7 678 185个EOA,95 889 930笔外部交易和30 833 719笔内部交易;然后从数量、时间、类型以及智能合约这4个角度对DApp分布进行了深入分析,从中总结出了一些发现,这些发现可以为DApp开发者与区块链研究者提供有价值的参考。

关键词: DApp, 区块链, 实证研究, 数据分析, 以太坊

Abstract: Blockchain technology has evolved rapidly in recent years,as a result,many organizations and enterprises have started using decentralized applications (DApps) based on blockchain and smart contracts to enhance the functionality and security of their information systems,or to expand new businesses.However,DApps may also introduce new problems due to the possible security and performance issues of blockchain and smart contracts.In order to deeply study and analyze the data and behavioral phenomena of DApps so as to help users better apply blockchain and DApps,a total of 2 565 DApps in 21 categories are first collected,as well as data related to these DApps from July 30,2015 to May 4,2020 (about 10 million block heights),including 16 302 smart contracts,7 678 185 EOA,95 889 930 external transactions,and 30 833 719 internal transactions.Then the DApp distribution is deeply analyzed from four perspectives:number,time,category,and smart contract,and some findings are summarized from them,which can provide valuable references for DApp developers and blockchain researchers.

Key words: Blockchain, DApp, Data analysis, Empirical study, Ethereum

中图分类号: 

  • TP309.2
[1]SWAN M.Blockchain:Blueprint for a new economy[M].O'Reilly Media,Inc.,2015.
[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]CHEN W,ZHENG Z,CUI J,et al.Detecting ponzi schemes on ethereum:Towards healthier blockchain technology[C]//Proceedings of the 2018 World Wide Web Conference.2018:1409-1418.
[4]FERNANDEZ-CARAMES T M,FRAGA-LAMAS P.A review on the application of blockchain to the next generation of cybersecure industry 4.0 smart factories[J].IEEE Access,2019,7:45201-45218.
[5]LI X,JIANG P,CHEN T,et al.A survey on the security ofblockchain systems[J].Future Generation Computer Systems,2020,107:841-853.
[6]WOOD G.Ethereum:A secure decentralised generalised tran-saction ledger [OL].https://files.gitter.im/ethereum/yellowpaper/VIyt/Paper.pdf.
[7]CHEN T,LI Z,ZHU Y,et al.Understanding ethereum viagraph analysis[J].ACM Transactions on Internet Technology (TOIT),2020,20(2):1-32.
[8]METCALFE W.Ethereum,Smart Contracts,DApps[M].Block-chain and Crypt Currency.Singapore:Springer,2020:77-93.
[9]KE Y J,JING M H,ZHENG H Y.Application Research ofBlockchain Technology in Trust Industry[J].Computer Science,2020,47(6A):591-595.
[10]FENG T,JIAO Y,FANG J L,et al.Medical Health Data Secu-rity Model Based on Alliance Blockchain[J].Computer Science,2020,47(4):305-311.
[11]ZHANG Q M,LU J H,LI S Z,et al.Building Innovative Enterprise Customer Service Technology Platform Based on Blockchain[J].Computer Science,2020,47(6A):639-642.
[12]BOWLES N.Cryptokitties,explained...mostly [EB/OL].The New York Times.2017 Dec.[2017-12-28].https://www.nytimes.com/2017/12/28/style/cryptokitties-want-a-blockchain-snuggle.html.
[13]TEPPER F.People have spent over $1 M buying virtual cats on the Ethereum Blockchain [EB/OL].[2017-12-03].https://techcrunch.com/2017/12/03/people-have-spent-over-1m-buying-virtual-cats-on-the-ethereum-blockchain/.
[14]LI Z H.Ethereum Smart Contract Optimization and Transaction Network Security Analysis [D].Chendu:University of Electronic Science and Technology of China,2020.
[15]CHEN T,LI Z,ZHANG Y,et al.Dataether:Data exploration framework for ethereum[C]//2019 IEEE 39th International Conference on Distributed Computing Systems (ICDCS).2019:1369-1380.
[16]BUTERIN V,WOOD G,WILCKE J.Ethereum homestead do-cumentation[OL].https://ethdocs.org/en/latest/index.html.
[17]BUTERINV.A next-generation smart contract and decentra-lized application platform[OL].http://blog.lavoiedubitcoin.info/public/Bibliotheque/EthereumWhitePaper.pdf.
[18]Ethereum Solidity.Solidity documentation[EB/OL].[2019].https://solidity.readthedocs.io/en/v0.5.11/index.html.
[19]State of the dapps [EB/OL].[2020].https://stateofthedapps.com/.
[20]Dappradar [EB/OL].[2019].https://dappradar.com/.
[21]Dapp.com [EB/OL].[2020].https://dapp.com/.
[22]Dappreview [EB/OL].[2020].https://dapp.review/.
[23]TEAM E.Etherscan:The ethereum block explorer [EB/OL].[2017].https://etherscan.io/.
[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] 黄松, 杜金虎, 王兴亚, 孙金磊.
以太坊智能合约模糊测试技术研究综述
Survey of Ethereum Smart Contract Fuzzing Technology Research
计算机科学, 2022, 49(8): 294-305. https://doi.org/10.11896/jsjkx.220500069
[3] 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
[4] 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
[5] 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
[6] 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
[7] 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
[8] 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
[9] 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
[10] 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
[11] 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
[12] 丛颖男, 王兆毓, 朱金清.
关于法律人工智能数据和算法问题的若干思考
Insights into Dataset and Algorithm Related Problems in Artificial Intelligence for Law
计算机科学, 2022, 49(4): 74-79. https://doi.org/10.11896/jsjkx.210900191
[13] 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
[14] 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
[15] 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
Viewed
Full text


Abstract

Cited

  Shared   
  Discussed   
No Suggested Reading articles found!