activity
20172022
most citedModeling and Understanding Ethereum Transaction Records via a Complex Network Approach

112 citations · 178 across the 7 of their papers we have counts for

collaborators

9 papers

cs.LG20229 cited

GANI: Global Attacks on Graph Neural Networks via Imperceptible Node Injections

Junyuan Fang, Haixian Wen, Jiajing Wu +3

Graph neural networks (GNNs) have found successful applications in various graph-related tasks. However, recent studies have shown that many GNNs are vulnerable to adversarial atta…

cs.CR2022

Heterogeneous Feature Augmentation for Ponzi Detection in Ethereum

Chengxiang Jin, Jie Jin, Jiajun Zhou +2

While blockchain technology triggers new industrial and technological revolutions, it also brings new challenges. Recently, a large number of new scams with a "blockchain" sock-pup…

cs.SI202249 cited

Complex Network Analysis of the Bitcoin Transaction Network

Bishenghui Tao, Hong-Ning Dai, Jiajing Wu +3

In this brief, we conduct a complex-network analysis of the Bitcoin transaction network. In particular, we design a new sampling method, namely random walk with flying-back (RWFB),…

cs.NI20226 cited

Understanding the Decentralization of DPoS: Perspectives From Data-Driven Analysis on EOSIO

Jieli Liu, Weilin Zheng, Dingyuan Lu +2

Recently, many Delegated Proof-of-Stake (DPoS)-based blockchains have been widely used in decentralized applications, such as EOSIO, Tron, and Binance Smart Chain. Compared with tr…

cs.SI2020112 cited

Modeling and Understanding Ethereum Transaction Records via a Complex Network Approach

Dan Lin, Jiajing Wu, Qi Yuan +1

As the largest public blockchain-based platform supporting smart contracts, Ethereum has accumulated a large number of user transaction records since its debut in 2014. Analysis of…

cs.LG20202 cited

MG-GCN: Fast and Effective Learning with Mix-grained Aggregators for Training Large Graph Convolutional Networks

Tao Huang, Yihan Zhang, Jiajing Wu +2

Graph convolutional networks (GCNs) have been employed as a kind of significant tool on many graph-based applications recently. Inspired by convolutional neural networks (CNNs), GC…