YingtongDou/CARE-GNN
Code for CIKM 2020 paper Enhancing Graph Neural Network-based Fraud Detectors against Camouflaged Fraudsters
This project helps fraud analysts and risk managers improve their ability to detect subtle, 'camouflaged' fraud within complex transaction networks. It takes your existing data, structured as a multi-relation graph (like connections between users, merchants, and items), along with node labels and features, and produces a more accurate fraud detection model. This tool is designed for professionals who need to identify fraudulent accounts or activities that deliberately mimic legitimate behavior.
306 stars. No commits in the last 6 months.
Use this if you need to detect sophisticated fraud where fraudsters try to blend in with normal users, making them hard to spot with traditional methods.
Not ideal if your fraud detection needs are basic, or if your data isn't structured as a multi-relation graph.
Stars
306
Forks
62
Language
Python
License
Apache-2.0
Category
Last pushed
Oct 11, 2022
Commits (30d)
0
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