Privacy-Centric Distributed Storage System with Dynamic Key Encryption and Optimized Queries

It utilizes a three-tier privacy-preserving storage framework and an efficient data identification mechanism in order to present a safe and efficient data storage and retrieval system. The data is divided into parts and strategically stored across local machines, fog and cloud servers. All files are encoded using the Run Length Encoding (RLE) algorithm to assure data compression and security. Small-sized data is completely stored on local machines, medium-sized data is divided with 25% stored locally and 75%onfogservers, and large-sized data is divided with 5% stored locally, 20% on fog servers, and 75% uploaded to cloud servers. The cloud server utilizes a management system to organize data blocks efficiently, and this distributed approach reduces processing overhead and improves security. In addition, the cloud-stored data is secured with a retrieval mechanism for confidentiality. The retrieval is achieved with a Data Identification Vector mechanism, which guarantees that each query on encrypted cloud data will be precise and private. For every keyword in the stored data, a DIV is generated through the process of constructing a keyword universe, merging the same keywords across files to eliminate redundancy and improve the efficiency of queries. Data is encrypted using dynamically generated keys that are dependent on file size and security requirements, hence better protection compared to the traditional single-key encryption method. Both the encrypted data and their respective DIVs are kept on the cloud server. Upon retrieving data, the users will generate a query that will be processed to create tokens. The tokens are sent to the cloud server that uses the DIVs to locate and retrieve the corresponding encrypted data. The system’s decryptor then decrypts retrieved data, restoring the original information and thus ensuring secure handling of data throughout the process.