Bitcoin Transaction Analysis System

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.

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Publication Details

Journal
Programming and Computer Software
Published
2024-12-01
DOI
https://doi.org/10.1134/s0361768824700488
Primary Topic
Blockchain Technology Applications and Security
Type
article
Field-Weighted Citation Impact
0.00
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article

Bitcoin Transaction Analysis System

Nikolay Karapetyants, M. Karapetyants, E. A. Basynya
Programming and Computer Software
Blockchain Technology Applications and Security
article

Bitcoin Transaction Analysis System

Nikolay Karapetyants, M. Karapetyants, E. A. Basynya
article en

Abstract

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.

Programming and Computer SoftwareVol. 50(S2)
National Research Nuclear University MEPhI (RU)
Openalex Percentile: Top 59%
Blockchain Technology Applications and Security
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