Analyzing and De-Anonymizing Bitcoin Networks:An IP Matching Method with Clustering and Heuristics  

作　　者：Teng Long Jiasheng Xu Luoyi Fu Xinbing Wang 

机构地区：[1]School of Information Engineering,China University of Geosciences,Beijing 100083,China [2]Department of Electronic Engineering,Shanghai Jiao Tong University,Shanghai 200240,China [3]Department of Computer Science and Engineering,Shanghai Jiao Tong University,Shanghai 200240,China

出　　处：《China Communications》2022年第6期263-278,共16页中国通信（英文版）

基　　金：supported by National Natural Science Foundation of China(No.62002332)。

摘　　要：The anonymity and de-anonymity of blockchain and Bitcoin have always been a hot topic in blockchain related research.Since Bitcoin was created by Nakamoto in 2009,it has,to some extent,deviated from its currency attribute as a trading medium but instead turned into an object for financial investment and operations.In this paper,the power-law distribution that the Bitcoin network obeys is given with mathematical proof,while traditional deanonymous methods such as clustering fail to satisfy it.Therefore,considering the profit-oriented characteristics of Bitcoin traders in such occasion,we put forward a de-anonymous heuristic approach that recognizes and analyzes the behavioral patterns of financial High-Frequency Transactions(HFT),with realtime exchange rate of Bitcoin involved.With heuristic approach used for de-anonymity,algorithm that deals with the adjacency matrix and transition probability matrix are also put forward,which then makes it possible to apply clustering to the IP matching method.Basing on the heuristic approach and additional algorithm for clustering,finally we established the de-anonymous method that matches the activity information of the IP with the transaction records in blockchain.Experiments on IP matching method are applied to the actual data.It turns out that similar behavioral pattern between IP and transaction records are shown,which indicates the superiority of IP matching method.

关 键 词：Bitcoin blockchain de-anonymization HEURISTICS 

分 类 号：F49[经济管理—产业经济] F821[自动化与计算机技术—计算机软件与理论] TP311.13[自动化与计算机技术—计算机科学与技术]