Multi-Modal Security Integration and Role-Based Access Control for Secure File Management System

This paper presents a non-deterministic multi-modal security integration and role-based access control for a secure file management system by integrating biometric verification, one-time passwords, and grid pattern selection. By using libraries like OpenCV for face recognition, PyAudio for audio recognition, graph matching algorithm for grid selection and Flask for building a responsive web interface, this system addresses the present shortcomings in authentication and file management systems but, at the same time, offers an adaptive security model that maximizes organizational efficiency and protects sensitive information. This storage of data includes algorithms such as Advanced Encryption Standards and Rivest-Shamir-Adleman. This system is equipped with role-based access control in which only the authorized users can access the application with specific permission, where administrators can assign files with specific permissions and streamline data management within organizations while ensuring full data protection. The proposed architecture provides permissions, enabling administrators to give and revoke access according to the requirements. This radical solution marks a major quantum step in secure file management—a strong model for organizations with an interest in upgrading data security strategies in the face of continually improving threats.