Cryptocurrency Transaction Network Embedding From Static and Dynamic Perspectives: An Overview

Document Type

Article

Publication Date

5-1-2023

Abstract

Cryptocurrency, as a typical application scene of blockchain, has attracted broad interests from both industrial and academic communities. With its rapid development, the cryptocurrency transaction network embedding (CTNE) has become a hot topic. It embeds transaction nodes into low-dimensional feature space while effectively maintaining a network structure, thereby discovering desired patterns demonstrating involved users' normal and abnormal behaviors. Based on a wide investigation into the state-of-the-art CTNE, this survey has made the following efforts: 1) categorizing recent progress of CTNE methods, 2) summarizing the publicly available cryptocurrency transaction network datasets, 3) evaluating several widely-adopted methods to show their performance in several typical evaluation protocols, and 4) discussing the future trends of CTNE. By doing so, it strives to provide a systematic and comprehensive overview of existing CTNE methods from static to dynamic perspectives, thereby promoting further research into this emerging and important field.

Identifier

85149412361 (Scopus)

Publication Title

IEEE Caa Journal of Automatica Sinica

External Full Text Location

https://doi.org/10.1109/JAS.2023.123450

e-ISSN

23299274

ISSN

23299266

First Page

1105

Last Page

1121

Issue

5

Volume

10

Grant

CAAIXSJLJJ-2021-035A

Fund Ref

National Natural Science Foundation of China

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