Attribute-Based Privacy Preserving Public Auditing Framework for Cloud Storage System

The rapid adoption of cloud storage services has created an urgent need for robust data security solutions. While cloud outsourcing offers significant benefits in terms of scalability and cost-effectiveness, it also brings challenges related to data integrity, privacy, and unauthorized access. This research proposes an Attribute-Based Privacy-Preserving Public Auditing framework for cloud storage systems to ensure data integrity while maintaining user data confidentiality. The proposed framework utilizes advanced cryptographic techniques, including homomorphic encryption and bilinear pairing, to allow third-party auditors (TPAs) to validate data integrity without gaining access to the actual content. By incorporating symmetric key cryptography, the system ensures that TPAs can perform audits securely while preserving privacy. Additionally, the framework is designed to support efficient auditing processes, preventing the leakage of sensitive information during the examination. This study addresses the growing security concerns in cloud storage, providing a comprehensive solution that balances both privacy and data integrity.