Optimized Data Compression for Efficient Cloud Storage

Authors- Vedashri Chorge, Dhiraj Jambhale, Aman Jain, Soham Jagtap, Professor Rashmi Jolhe

Abstract-– The exponential growth of digital data demands smarter and more secure cloud storage solutions. This project introduces an intelligent framework that integrates lossless data compression, AES encryption, and NLP-based PDF summarization to optimize storage, enhance security, and improve document usability. Compression reduces file size and bandwidth usage without compromising integrity, while encryption ensures safe transmission and access control using AWS S3 for scalability and efficient retrieval. To enhance document accessibility, NLP-powered summarization enables users to extract key insights from lengthy PDFs, reducing reading time and boosting productivity. Transformer-based models help streamline content management for research, corporate, and cloud-based applications. By combining compression, encryption, and intelligent summarization, the system delivers a secure, scalable, and efficient cloud storage solution. Performance evaluations confirm improved retrieval speed and reduced storage needs. Future upgrades may include AI-driven adaptive compression, real-time optimization, and advanced data security for enhanced cloud performance.

DOI: /10.61463/ijset.vol.13.issue2.324