Multi-input address incremental clustering for the Bitcoin blockchain based on Petri net model analysis  

作　　者：Fangchi Qin Yan Wu Fang Tao Lu Liu Leilei Shi Anthony J.Miller 

机构地区：[1]Jiangsu Key Laboratory of Security Technology for Industrial Cyberspace,School of Computer Science and Telecommunication Engineering,Jiangsu University,China [2]Birmingham Business School,University of Birmingham,UK [3]School of Informatics,University of Leicester,UK

出　　处：《Digital Communications and Networks》2022年第5期680-686,共7页数字通信与网络（英文版）

基　　金：The work reported in this paper has been partially supported by the National Key Research and Development Project(2020YFB1005503);the NSFC Projects(61502209 and U1836116);the Leading-edge Technology Program of Jiangsu Natural Science Foundation(BK20202001);the NSFC of Jiangsu Province Project(BK20201415);the UK-Jiangsu 20-20 World Class University Initiative programme,and the Natural Science Foundation of the Jiangsu Higher Education Institutions(Grant number:22KJB520016).

摘　　要：Bitcoin is a cryptocurrency based on blockchain.All historical Bitcoin transactions are stored in the Bitcoin blockchain,but Bitcoin owners are generally unknown.This is the reason for Bitcoin's pseudo-anonymity,therefore it is often used for illegal transactions.Bitcoin addresses are related to Bitcoin users'identities.Some Bitcoin addresses have the potential to be analyzed due to the behavior patterns of Bitcoin transactions.However,existing Bitcoin analysis methods do not consider the fusion of new blocks'data,resulting in low efficiency of Bitcoin address analysis.In order to address this problem,this paper proposes an incremental Bitcoin address cluster method to avoid re-clustering when new block data is added.Besides,a heuristic Bitcoin address clustering algorithm is developed to improve clustering accuracy for the Bitcoin Blockchain.Experimental results show that the proposed method increases Bitcoin address cluster efficiency and accuracy.

关 键 词：Bitcoin Blockchain Petri net Incremental clustering 

分 类 号：TP311.13[自动化与计算机技术—计算机软件与理论]