Edge-Cloud Integrated Fraud Detection for E-Commerce Transactions Using Hybrid Siamese-LSTM Model

Key Points

• This research aims to develop an effective fraud detection system for e-commerce transactions using a hybrid model.
• Utilized a hybrid Siamese-LSTM model for better pattern recognition in transaction data.
• Integrated edge-cloud computing architecture to enhance processing speed and efficiency.
• Analyzed e-commerce transaction datasets to assess model performance.
• Achieved a significant reduction in fraud rates compared to traditional methods.
• Demonstrated improved accuracy in fraud detection with a lower false positive rate.
• Showed enhanced processing speed due to edge-cloud integration.