Data Compression for Achieving Cost-Efficient and Secure Data Storage over Public Cloud: A Proposed Model
Subhash Rathod, Ratnashil N. Khobragade, Vilas M. Thakare, K. H. Walse, Gajendra R. Bamnote, Sushama Pawar · Apple Academic Press eBooks · 2025
Every day, millions of digital images are being generated and stored in the cloud. To free up space and give one another access to their confidential information from everywhere on any gadget, thousands of users have switched to the internet for hosting their confidential information. However, the privacy and security of private information can only be based on the dependability of the company that provides the cloud service. Most of the public cloud service providers do not assure data security and privacy. To guarantee data privacy and security, one must move to a private cloud. Also, higher data storage cost, access restriction, and data privacy are the major concerns in cloud platforms. Work in this regard has been achieved but with a minimalistic approach. This paper studies the technical challenges that come with constructing a cloud-based image processing system. We have explored various image processing tasks such as compression, which helps 244 to minimize storage cost, and fragmentation which helps to store images in chunks and provide extra security layers. To assess the system’s efficacy, we ran a number of comprehensive research projects.