Secuscan AI: A Cloud-Based Intelligent System for Real-Time Fraud Detection and Threat Isolation

Abstract

SecuScan AI is an intelligent, web-based Unified Security Operations Center designed to optimize digital transaction security by detecting and isolating fraudulent activities dynamically. This system leverages machine learning techniques to analyze historical transaction patterns, real-time metadata, and anomaly indicators (such as velocity deviation and geographic mismatch) to accurately predict the fraud probability of incoming transactions. By integrating predictive analytics with backend architecture, the system enables automated threat escalation and blocking decisions, ensuring secure financial ecosystems while minimizing false positives and preventing system exploits. The application is developed using a hybrid backend featuring Python for ML processing and Node.js for high-speed API routing, along with a React-based frontend utilizing a glassmorphic, interactive user interface. Real-time data simulation and monitoring dashboards provide insights into system performance and model health, while alert mechanisms notify users of critical threats. By incorporating AI-driven detection and automation, this system enhances transaction security, improves threat response times, and ensures high integrity of financial services.