About this document
Multi-Perspective E-commerce Fraud Detection by swamylns707 is a document available to read on EtoBox.
This document presents a novel fraud detection method for e-commerce transactions that combines machine learning and process mining to monitor real-time user behaviors. The proposed system addresses the limitations of existing methods by dynamically detecting changes in user behaviors and transaction processes through a hybrid approach. Key contributions include a conformance checking method, a user behavior detection method based on Petri nets, and an SVM model for classifying fraudulent behaviors.
- Author
- swamylns707
- Language
- EN