TY - JOUR
T1 - Identifying the vulnerabilities of bitcoin anonymous mechanism based on address clustering
AU - Zheng, Baokun
AU - Zhu, Liehuang
AU - Shen, Meng
AU - Du, Xiaojiang
AU - Guizani, Mohsen
N1 - Publisher Copyright:
© 2020, Science China Press and Springer-Verlag GmbH Germany, part of Springer Nature.
PY - 2020/3/1
Y1 - 2020/3/1
N2 - The anonymity mechanism of bitcoin is favored by the society, which promotes its usage and development. An adversary should not be able to discover the relation between bitcoin addresses and bitcoin users to ensure effective privacy. However, the relation among bitcoin transactions can be used to analyze the bitcoin privacy information, which seriously jeopardizes the bitcoin anonymity. Herein, we describe the vulnerabilities associated with the anonymity mechanism of bitcoin, including the relation among bitcoin addresses and the relation among bitcoin users. Further, we demonstrate that the existing methods do not guarantee the comprehensiveness, accuracy, and efficiency of the analysis results. We propose a heuristic clustering method to judge the relation among bitcoin addresses and employ the Louvain method to discover the relation among bitcoin users. Subsequently, we construct an address-associated database of historical transactions and implement real-time updates. Extensive experiments are used to demonstrate the comprehensiveness, accuracy, and efficiency of the proposed scheme. Specifically, the proposed scheme reveals the privacy vulnerability associated with the blockchain technology. We expect that our scheme can be applied to improve the blockchain technology.
AB - The anonymity mechanism of bitcoin is favored by the society, which promotes its usage and development. An adversary should not be able to discover the relation between bitcoin addresses and bitcoin users to ensure effective privacy. However, the relation among bitcoin transactions can be used to analyze the bitcoin privacy information, which seriously jeopardizes the bitcoin anonymity. Herein, we describe the vulnerabilities associated with the anonymity mechanism of bitcoin, including the relation among bitcoin addresses and the relation among bitcoin users. Further, we demonstrate that the existing methods do not guarantee the comprehensiveness, accuracy, and efficiency of the analysis results. We propose a heuristic clustering method to judge the relation among bitcoin addresses and employ the Louvain method to discover the relation among bitcoin users. Subsequently, we construct an address-associated database of historical transactions and implement real-time updates. Extensive experiments are used to demonstrate the comprehensiveness, accuracy, and efficiency of the proposed scheme. Specifically, the proposed scheme reveals the privacy vulnerability associated with the blockchain technology. We expect that our scheme can be applied to improve the blockchain technology.
KW - bitcoin
KW - blockchain
KW - cluster
KW - privacy
KW - transaction
UR - http://www.scopus.com/inward/record.url?scp=85079572043&partnerID=8YFLogxK
U2 - 10.1007/s11432-019-9900-9
DO - 10.1007/s11432-019-9900-9
M3 - Article
AN - SCOPUS:85079572043
SN - 1674-733X
VL - 63
JO - Science China Information Sciences
JF - Science China Information Sciences
IS - 3
M1 - 132101
ER -