sepandhaghighi/Ethereum-Fraud-Detection-Models
Ethereum Fraud Detection Models
This project helps financial institutions, blockchain platforms, or anyone handling Ethereum transactions to identify and prevent fraudulent activities. It takes historical Ethereum transaction data as input and provides models that predict whether new transactions are likely to be fraudulent. The primary users are fraud analysts, compliance officers, and risk managers who need to secure digital asset transactions.
No commits in the last 6 months.
Use this if you need to detect unusual or deceptive patterns in Ethereum transactions to prevent financial loss and enhance security.
Not ideal if your focus is on fraud detection outside of the Ethereum blockchain or if you require an off-the-shelf, integrated fraud detection solution rather than foundational models.
Stars
22
Forks
1
Language
Jupyter Notebook
License
MIT
Category
Last pushed
Oct 06, 2022
Commits (30d)
0
Get this data via API
curl "https://pt-edge.onrender.com/api/v1/quality/ml-frameworks/sepandhaghighi/Ethereum-Fraud-Detection-Models"
Open to everyone — 100 requests/day, no key needed. Get a free key for 1,000/day.
Higher-rated alternatives
GoogleCloudPlatform/fraudfinder
Fraudfinder: A comprehensive lab series on how to build a real-time fraud detection system on...
benedekrozemberczki/awesome-fraud-detection-papers
A curated list of data mining papers about fraud detection.
jube-home/aml-fraud-transaction-monitoring
Open source AML and Fraud Detection using Machine Learning for Real-Time Transaction Monitoring
safe-graph/DGFraud
A Deep Graph-based Toolbox for Fraud Detection
curiousily/Credit-Card-Fraud-Detection-using-Autoencoders-in-Keras
iPython notebook and pre-trained model that shows how to build deep Autoencoder in Keras for...