LIGHTWEIGHT PRIVACY-PRESERVING AUDITING MECHANISM FOR SHARED CLOUD STORAGE

Abstract

This research introduces a simple privacy-preserving auditing approach for shared cloud storage that ensures data integrity without imposing a significant computational burden or jeopardizing user privacy. By employing robust cryptographic techniques such as homomorphic authenticators and random masking, the method enables an independent auditor to verify the data's accuracy without observing the data itself. It is well-suited for use in real-world collaborative cloud environments due to its support for dynamic data operations, including alteration, insertion, and deletion. The method is capable of managing large datasets with multiple users due to its capacity to reduce computation and communication costs. In order to prevent unauthorized audits and data leaks, secure user management and access control are also included. Based on the results of the experiments, the proposed mechanism is a viable alternative for secure shared cloud storage due to its ability to integrate privacy, efficiency, and security.