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A Machine Learning and Blockchain Based Efficient Fraud Detection Mechanism.

Tehreem Ashfaq¹, Rabiya Khalid¹, Adamu Sani Yahaya^1,2

¹Department of Computer Science, COMSATS University Islamabad, Islamabad 44000, Pakistan.

Sensors (Basel, Switzerland)

|October 14, 2022

Summary

This summary is machine-generated.

This study introduces a secure machine learning model integrated with blockchain to detect Bitcoin fraud. It enhances transaction security by accurately identifying fraudulent patterns.

Keywords:

XGboost anomaly detection blockchain fraud detection machine learning random forest

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Area of Science:

Computer Science
Cybersecurity
Financial Technology

Background:

Fraud and anomalies are persistent challenges in e-banking and online transactions.
The evolution of the financial sector necessitates advanced fraud detection methods.
Blockchain technology offers enhanced security but also presents new avenues for fraud.

Purpose of the Study:

To propose a secure fraud detection model for the Bitcoin network.
To leverage machine learning and blockchain for identifying fraudulent transactions.
To enhance the security and integrity of financial transactions.

Main Methods:

Utilized machine learning algorithms: XGBoost and Random Forest (RF) for transaction classification.
Trained models on datasets of fraudulent and legitimate transaction patterns.
Integrated blockchain technology with machine learning for real-time fraud detection.
Performed security analysis of the proposed smart contract and developed an attacker model.

Main Results:

Achieved accurate classification of transactions using XGBoost and RF.
Demonstrated the effectiveness of the integrated machine learning and blockchain model in detecting fraudulent Bitcoin transactions.
Quantified model accuracy using precision and Area Under the Curve (AUC) metrics.
Validated the robustness and security of the proposed system against potential attacks.

Conclusions:

The proposed model effectively detects fraud and anomalies in the Bitcoin network.
Combining machine learning with blockchain technology provides a robust solution for financial transaction security.
The system demonstrates strong security against various attack vectors, ensuring reliable fraud detection.