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Framework and algorithms for identifying honest blocks in blockchain

文献类型：期刊论文

作者Wang, Xu1,2,3; Gan, Guohua3,4,5; Wu, Ling-Yun1,2,3
刊名PLOS ONE
出版日期2020-01-08
卷号15期号:1页码:14
ISSN号1932-6203
DOI10.1371/journal.pone.0227531
英文摘要Blockchain technology gains more and more attention in the past decades and has been applied in many areas. The main bottleneck for the development and application of blockchain is its limited scalability. Blockchain with directed acyclic graph structure (BlockDAG) is proposed in order to alleviate the scalability problem. One of the key technical problems in BlockDAG is the identification of honest blocks which are very important for establishing a stable and invulnerable total order of all the blocks. The stability and security of BlockDAG largely depends on the precision of honest block identification. This paper presents a novel universal framework based on graph theory, called MaxCord, for identifying the honest blocks in BlockDAG. By introducing the concept of discord, the honest block identification is modelled as a generalized maximum independent set problem. Several algorithms are developed, including exact, greedy and iterative filtering algorithms. The extensive comparisons between proposed algorithms and the existing method were conducted on the simulated BlockDAG data to show that the proposed iterative filtering algorithm identifies the honest blocks both efficiently and effectively. The proposed MaxCord framework and algorithms can set the solid foundation for the BlockDAG technology.
资助项目Laboratory of Big Data and Blockchain, National Centerfor Mathematics and Interdisciplinary Sciences, Chinese Academy of Sciences
WOS研究方向Science & Technology - Other Topics
语种英语
WOS记录号WOS:000534337700049
出版者PUBLIC LIBRARY SCIENCE
源URL[http://ir.amss.ac.cn/handle/2S8OKBNM/51488]  
专题应用数学研究所
通讯作者Wu, Ling-Yun
作者单位1.Chinese Acad Sci, Key Lab Management Decis & Informat Syst, Inst Appl Math, Acad Math & Syst Sci, Beijing, Peoples R China
2.Univ Chinese Acad Sci, Sch Math Sci, Beijing, Peoples R China
3.Chinese Acad Sci, Lab Big Data & Blockchain, Natl Ctr Math & Interdisciplinary Sci, Beijing, Peoples R China
4.Beijing Taiyiyun Technol Co Ltd, Beijing, Peoples R China
5.Univ Sci & Technol Beijing, Beijing, Peoples R China
推荐引用方式
GB/T 7714		 Wang, Xu,Gan, Guohua,Wu, Ling-Yun. Framework and algorithms for identifying honest blocks in blockchain[J]. PLOS ONE,2020,15(1):14.
APA Wang, Xu,Gan, Guohua,&Wu, Ling-Yun.(2020).Framework and algorithms for identifying honest blocks in blockchain.PLOS ONE,15(1),14.
MLA Wang, Xu,et al."Framework and algorithms for identifying honest blocks in blockchain".PLOS ONE 15.1(2020):14.

入库方式： OAI收割

来源：数学与系统科学研究院

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