DOI: 10.17587/prin.14.523-530

Bitcoin Transaction Analysis System

E. A. Basinya, Associate Professor, Leading Researcher, eabasynya@mephi.ru, N. Karapetyants, Assistant of Department, nkarapetyants@mephi.ru, M. Karapetyants, IICS Engineer, mkarapetyants@mephi.ru, National Research Nuclear University "MEPhl", Moscow, 115409, Russian Federation

Corresponding author: Evgeniy A. Basynya, Associate Professor, Leading Researcher, National Research Nuclear University "MEPhI", Moscow, 115409, Russian Federation, E-mail: eabаsynya@mephi.ru

The lack of a user identification system and the existence of a variety of 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. There is a need to develop new methods of cash identification in the Bitcoin network. The purpose 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 of the stages 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 multi-model 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.

Keywords: blockhain, Bitcoin, KYC, KYT, transaction analysis, clusterization, heuristic, DSS

pp. 523–530

For citation:
Basynya E. A., Karapetyants N., Karapetyants M. Bitcoin Transaction Analysis System, Programmnaya Ingeneria, 2023, vol. 14, no. 11, pp. 523—530. DOI: 10.17587/prin.14.523-530 (in Russian).

This work was supported by the Ministry of Science and Higher Education of the Russian Federation (state task project No. FSWU-2023-0031).

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