Bitcoin Transaction Analysis System

被引:0
作者
Basynya, E. A. [1 ]
Karapetyants, N. [1 ]
Karapetyants, M. [1 ]
机构
[1] Natl Res Nucl Univ MEPhI, Moscow 115409, Russia
关键词
blockchain; Bitcoin; KYC; KYT; transaction analysis; clusterization; heuristic; DSS;
D O I
10.1134/S0361768824700488
中图分类号
TP31 [计算机软件];
学科分类号
081202 ; 0835 ;
摘要
The lack of a user identification system and the existence of various ways to obfuscate a transaction on the Bitcoin network is of great interest to attackers and can be used by them to conduct illegal activities. The aim of this work is to develop a method of transaction verification in the Bitcoin network to improve the efficiency of the process of identification of illegally obtained funds and their sources. The work solves the following tasks: the development of a method for transaction verification in the Bitcoin network and the development of a decision support system, which includes the proposed method. The article describes each stage of the method: collection, aggregation, processing, and analysis of information. The information analysis stage proposes a clustering method that takes into account an extended set of empirical rules (heuristics) of transaction analysis, as well as information about Bitcoin network address owners. The scientific novelty lies in increasing the efficiency of the identification process of illegally obtained funds and their sources through a comprehensive analysis of transactions, including the extended collection of information and its subsequent aggregation in the multimodel database of the decision support system. In contrast to existing methods, the reliability of the identification of Bitcoin network subjects is increased through the use of intelligent methods of data analysis. The results of this work will provide an opportunity to develop new and improve existing transaction analysis tools in future research, which will allow more effective identification of funds in the Bitcoin network associated with illegal activities.
引用
收藏
页码:S104 / S112
页数:9
相关论文
共 12 条
[1]  
[Anonymous], 2023, The 2023 Crypto Crime Report
[2]  
Basynya E.A., 2023, Programmnaya Ingeneria, V14, P493, DOI [10.17587/prin.14.492-501, DOI 10.17587/PRIN.14.492-501]
[3]   ANALYZING THE ERROR RATES OF BITCOIN CLUSTERING HEURISTICS [J].
Gong, Yanan ;
Chow, Kam-Pui ;
Ting, Hing-Fung ;
Yiu, Siu-Ming .
ADVANCES IN DIGITAL FORENSICS XVIII, 2022, 653 :187-205
[4]   Bitcoin address clustering method based on multiple heuristic conditions [J].
He X. ;
He K. ;
Lin S. ;
Yang J. ;
Mao H. .
IET Blockchain, 2022, 2 (02) :44-56
[5]  
Jeyasheela rakkini M. J., 2022, Soft Computing: Theories and Applications: Proceedings of SoCTA 2021. Lecture Notes in Networks and Systems (425), P25, DOI 10.1007/978-981-19-0707-4_3
[6]  
Kulkarni R.N., 2022, Lecture Notes in Networks and Systems, V446, DOI [10.1007/978-981-19-1559-815, DOI 10.1007/978-981-19-1559-815]
[7]  
Lin Chang-Yi, 2022, Procedia Computer Science, P3217, DOI 10.1016/j.procs.2022.09.379
[8]  
Mezquita Yeray, 2023, Blockchain and Applications, 4th International Congress. Lecture Notes in Networks and Systems (595), P162, DOI 10.1007/978-3-031-21229-1_16
[9]   BitSQL: A SQL-based Bitcoin Analysis System [J].
Mun, Hyunsu ;
Lee, Youngseok .
2022 IEEE INTERNATIONAL CONFERENCE ON BLOCKCHAIN AND CRYPTOCURRENCY (IEEE ICBC 2022), 2022,
[10]   Context matters: Methods for Bitcoin tracking [J].
Tironsakkul, Tin ;
Maarek, Manuel ;
Eross, Andrea ;
Just, Mike .
FORENSIC SCIENCE INTERNATIONAL-DIGITAL INVESTIGATION, 2022, 42-43