Fraud Detection System
A sophisticated real-time transaction monitoring application using machine learning to detect fraudulent activities.
Java
JavaFX
MachineLearning
Weka
H2Database
Maven
DataAnalysis
RealTime

A comprehensive fraud detection system that leverages machine learning to analyze financial transactions in real-time, providing immediate alerts for suspicious activities without requiring external dependencies.
Technology Stack
- Java 17 with JavaFX 21 for the modern, responsive UI
- Weka 3.8.6 machine learning library with Random Forest algorithm
- H2 Database for local data storage
- Maven for project build and dependency management
Key Features
- Real-time transaction processing with configurable generation rate
- Machine learning-based anomaly detection
- Interactive dashboard with transaction tables and trend charts
- Customizable fraud threshold and sensitivity settings
- Transaction filtering by date range and type
- Data import/export capabilities
Technical Implementation
- Model-View Architecture with clean separation of concerns
- Feature engineering based on transaction amount, type, and location
- Self-contained operation with no external API dependencies
- Efficient machine learning pipeline optimized for desktop performance