9 citations · 17 across the 5 of their papers we have counts for
6 papers
The Robustness of Graph k-shell Structure under Adversarial Attacks
B. Zhou, Y. Q. Lv, Y. C. Mao +3
The k-shell decomposition plays an important role in unveiling the structural properties of a network, i.e., it is widely adopted to find the densest part of a network across a bro…
DeepInsight: Interpretability Assisting Detection of Adversarial Samples on Graphs
Junhao Zhu, Yalu Shan, Jinhuan Wang +3
With the rapid development of artificial intelligence, a number of machine learning algorithms, such as graph neural networks have been proposed to facilitate network analysis or g…
TSGN: Transaction Subgraph Networks for Identifying Ethereum Phishing Accounts
Jinhuan Wang, Pengtao Chen, Shanqing Yu +1
Blockchain technology and, in particular, blockchain-based transaction offers us information that has never been seen before in the financial world. In contrast to fiat currencies,…
Sampling Subgraph Network with Application to Graph Classification
Jinhuan Wang, Pengtao Chen, Bin Ma +4
Graphs are naturally used to describe the structures of various real-world systems in biology, society, computer science etc., where subgraphs or motifs as basic blocks play an imp…
Adversarial Attacks to Scale-Free Networks: Testing the Robustness of Physical Criteria
Qi Xuan, Yalu Shan, Jinhuan Wang +2
Adversarial attacks have been alerting the artificial intelligence community recently, since many machine learning algorithms were found vulnerable to malicious attacks. This paper…
Subgraph Networks with Application to Structural Feature Space Expansion
Qi Xuan, Jinhuan Wang, Minghao Zhao +4
Real-world networks exhibit prominent hierarchical and modular structures, with various subgraphs as building blocks. Most existing studies simply consider distinct subgraphs as mo…