Authors: Jayshree Pansare, Karan Singh, Affan Ali Sayyed, Rushikesh Langhi, Prathamesh Dive
Abstract: The rapid expansion of digital communication platforms has significantly increased the need for secure and efficient messaging systems. Modern users rely heavily on chat-based applications for academic collaboration, professional coordination, and personal communication. However, traditional messaging systems often fail to provide an optimal balance between data security and efficient information management. While some platforms emphasize usability, they frequently compromise on privacy, whereas others focus on encryption but lack intelligent tools to manage large volumes of conversational data. This research presents a Secret Chat Room with AI Summarization System, a web-based platform designed to address both security and usability challenges. The system integrates end-to-end encryption using AES and RSA algorithms to ensure confidentiality and protect messages from unauthorized access. Additionally, it employs WebSocket-based real-time communication to enable low-latency and efficient message exchange between users. A key contribution of this work is the integration of an AI-based summarization module that utilizes transformer-based model Gemini Summarization. This module processes chat histories and generates concise summaries, allowing users to quickly understand lengthy discussions without manually reviewing all messages. This feature significantly reduces information overload and enhances productivity. The system follows a modular architecture consisting of authentication, encryption, messaging, and AI components. Experimental observations indicate that the system achieves efficient performance with minimal latency while maintaining strong security standards. The proposed solution is suitable for applications in education, enterprise communication, and collaborative environments.
DOI: http://doi.org/10.5281/zenodo.20937546
