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
Fraud Detection System
Fraud Detection System

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