Aug 19, 2021 · We proposed a multi-channel graph classification model (MCGC) with multiple feature extraction channels for GNN.

To extract richer information, we proposed a multi-channel graph classification model (MCGC) with multiple feature extraction channels for GNN. The transaction ...

Aug 19, 2021 · The proposed multi-channel graph classification model (MCGC) can not only achieve state-of-the-art performance in the graph classification ...

The transaction pattern graphs and MCGC are more able to detect potential phishing scammers by extracting the transaction pattern features of the target users.

Aug 19, 2021 · Addressing to this problem, we defined the transaction pat- tern graphs for users and transformed the phishing scam detection into a graph.

We proposed a novel transaction network embedding algorithm transE based on the multi-channel random walk to model the detection of Ethereum phishing scam ...

This paper characterizes and detects Ethereum phishing gangs, and introduces a novel detection model named PGDetector, which can find out the potential risky ...

The transaction pattern graphs and MCGC are more able to detect potential phishing scammers by extracting the transaction pattern features of the target users.

We aim to identify different ac- counts by combining the local topology and interaction patterns of the target accounts. In this article, the Ethereum phishing ...

We propose PDTGA, a method that applies graph representation learning based on temporal graphs attention to improve the effectiveness of phishing scams ...