A comprehensive survey on deep graph representation learning methods

IA Chikwendu, X Zhang, IO Agyemang… - Journal of Artificial …, 2023 - jair.org
There has been a lot of activity in graph representation learning in recent years. Graph
representation learning aims to produce graph representation vectors to represent the …

Blockchain Data Mining With Graph Learning: A Survey

Y Qi, J Wu, H Xu, M Guizani - IEEE Transactions on Pattern …, 2023 - ieeexplore.ieee.org
Blockchain data mining has the potential to reveal the operational status and behavioral
patterns of anonymous participants in blockchain systems, thus providing valuable insights …

Decentralized finance (DeFi): A survey

E Jiang, B Qin, Q Wang, Z Wang, Q Wu, J Weng… - arXiv preprint arXiv …, 2023 - arxiv.org
Decentralized Finance (DeFi) is a new paradigm in the creation, distribution, and utilization
of financial services via the integration of blockchain technology. Our research conducts a …

Inspection-L: self-supervised GNN node embeddings for money laundering detection in bitcoin

WW Lo, GK Kulatilleke, M Sarhan, S Layeghy… - Applied …, 2023 - Springer
Criminals have become increasingly experienced in using cryptocurrencies, such as Bitcoin,
for money laundering. The use of cryptocurrencies can hide criminal identities and transfer …

Tracking phishing on Ethereum: Transaction network embedding approach for accounts representation learning

Z Lin, X Xiao, G Hu, Q Li, B Zhang, X Luo - Computers & Security, 2023 - Elsevier
The transaction volume of Ethereum has been witnessing a year-on-year increase, which
has unfortunately been accompanied by significant losses due to phishing scams. To …

MP-GCN: a phishing nodes detection approach via graph convolution network for ethereum

T Yu, X Chen, Z Xu, J Xu - Applied Sciences, 2022 - mdpi.com
Blockchain is making a big impact in various applications, but it is also attracting a variety of
cybercrimes. In blockchain, phishing transfers the victim's virtual currency to make huge …

Tsgn: Transaction subgraph networks assisting phishing detection in ethereum

J Wang, P Chen, X Xu, J Wu, M Shen, Q Xuan… - arXiv preprint arXiv …, 2022 - arxiv.org
Due to the decentralized and public nature of the Blockchain ecosystem, the malicious
activities on the Ethereum platform impose immeasurable losses for the users. Existing …

[HTML][HTML] A review on deep anomaly detection in Blockchain

O Mounnan, O Manad, L Boubchir… - Blockchain: Research …, 2024 - Elsevier
The last few years have witnessed the widespread use of blockchain technology in several
works, due to its effectiveness in terms of privacy, security, and trustworthiness. However, the …

EtherShield: Time-interval Analysis for Detection of Malicious Behavior on Ethereum

B Pan, N Stakhanova, Z Zhu - ACM Transactions on Internet Technology, 2024 - dl.acm.org
Advances in blockchain technology have attracted significant attention across the world. The
practical blockchain applications emerging in various domains, ranging from finance …

Graph learning-based blockchain phishing account detection with a heterogeneous transaction graph

J Kim, S Lee, Y Kim, S Ahn, S Cho - Sensors, 2023 - mdpi.com
Recently, cybercrimes that exploit the anonymity of blockchain are increasing. They steal
blockchain users' assets, threaten the network's reliability, and destabilize the blockchain …