Secure the Drug Components using Data Mining

In the pharmaceutical and healthcare industries, the secure handling of sensitive drug component data is crucial. This project presents a comprehensive system for the secure storage, encryption, and controlled access of drug datasets using modern encryption techniques and cloud-based storage. Users can upload drug-related CSV files through a web interface, which are then processed and encrypted selectively before being uploaded to Amazon S3. Each file is associated with a unique encryption key, which is securely stored and can only be retrieved by authorized users via password-based authentication. The backend is built with Spring Boot, implementing robust encryption logic, metadata storage, and integration with AWS S3. The frontend (developed using Next.js) enables users to upload, view, and manage their encrypted files in an intuitive interface. Key features of the system include role-based access control, data confidentiality, and secure key retrieval mechanisms, ensuring that only legitimate users can decrypt and access sensitive data. This project demonstrates a scalable and secure solution for privacy preserving storage of drug components, making it highly relevant in scenarios where data confidentiality and regulatory compliance are critical. It also lays the groundwork for future integration of machine learning or data mining pipelines once decryption is authorized, ensuring both security and analytical capabilities.