Knowledge Discovery in Cryptocurrency Transactions: A Survey

TL;DR

This survey reviews research on knowledge discovery in cryptocurrency transactions, focusing on transaction tracing, user behavior analysis, and tools, highlighting current methods and future directions in De-Fi and digital fiat money.

Contribution

It provides a comprehensive classification and summary of existing data mining techniques applied to cryptocurrency transaction analysis, including tools and future research directions.

Findings

Classification of research into three main aspects

Summary of methodologies and major findings

Discussion of tools and future research directions

Abstract

Cryptocurrencies gain trust in users by publicly disclosing the full creation and transaction history. In return, the transaction history faithfully records the whole spectrum of cryptocurrency user behaviors. This article analyzes and summarizes the existing research on knowledge discovery in the cryptocurrency transactions using data mining techniques. Specifically, we classify the existing research into three aspects, i.e., transaction tracings and blockchain address linking, the analyses of collective user behaviors, and the study of individual user behaviors. For each aspect, we present the problems, summarize the methodologies, and discuss major findings in the literature. Furthermore, an enumeration of transaction data parsing and visualization tools and services is also provided. Finally, we outline several future directions in this research area, such as the current rapid development of Decentralized Finance (De-Fi) and digital fiat money.