The exponential growth of storage capacities and computational power has precipitated a significant increase in data accumulation, inadvertently leading to the proliferation of duplicate files across local and shared environments. These redundancies consume critical storage resources, degrade system performance, and waste network bandwidth during repeated file downloads. This report details the technical design and implementation blueprint for the Data Download Duplication Alert System (DDAS)—a multi-tier platform designed to monitor, detect, and prevent duplicate files. The architecture integrates a Node.js and Express.js backend with WebSocket communication, a browser extension for pre-download alerts, and a Java Swing-based desktop application for real-time directory monitoring. Leveraging the SHA-256 hashing algorithm, along with byte-by-byte content comparison and chunk sampling techniques, the system classifies file uniqueness regardless of metadata discrepancies. The report encompasses the problem statement, system architecture, duplicate detection methodology, API specifications, and performance analysis, demonstrating a practical approach to optimizing resource usage and data management.

Keywords: data deduplication, SHA-256 hashing, real-time monitoring, file management, browser extension, storage optimization, computer architecture