A Secure and Efficient Public Data Auditing Solution for the Cloud
Hong Wang, Lipeng Wang, Yanyan Yang, Mingsheng Hu, Zhijuan Jia, Zhong Chen, Shen Liu · 2024
To protect the security of cloud data, users must verify data integrity using hash-based schemes. However, current schemes create a linear computational overhead based on the size of cloud data. As the demand for big data storage continues to grow, this overhead becomes a significant burden. Improving the efficiency of data auditing schemes has become a critical issue. In response, we propose an efficient data auditing scheme that is independent of file size. This novel scheme involves outsourcing file data to cloud servers and utilizes a Provable Data Possession (PDP) scheme to ensure data integrity without the need for a centralized entity to manage any keys, thus eliminating single points of failure. Furthermore, our proposed scheme eliminates the need to manage public keys, as in traditional public key infrastructure-based schemes. The security of our proposed scheme has been analyzed, and experimental results demonstrate its efficiency.