Remote data integrity auditing, as a key technology for cloud storage, allows verifier to check cloud data integrity without downloading entire file from cloud server (CS). In practice, user might only concern the integrity of the files containing the specific keyword and would like to perform data dynamic operations on data. In this paper, we construct a practical keyword-based remote data integrity auditing scheme supporting full data dynamics. In such a scheme, a novel construction called keyword tag is designed. Using the keyword tag, TPA is able to simultaneously check whether CS correctly keeps all files containing the specific keyword. TPA can detect CS's misbehaviors once CS does not keep these files correctly. Furthermore, our scheme supports full data dynamics, including file-level updates and block-level updates. The keyword tag is updated when the user performs the file-level updates. To support block-level updates, we introduce an index switcher set to maintain the relationship between the block index and the authenticator index. We can avoid the recalculation of the authenticators by using authenticator indexes to generate authenticators. After cloud data are updated, data integrity still can be guaranteed. Security analysis and experimental results show that our scheme is provably secure and efficient.

Public auditing is a significant technique in cloud-based Internet of Things (IoT) systems, which enables the verifier to check the integrity of IoT data stored in the cloud. Nowadays, data become a core property for owners. Once the data of one owner are sold to another one, the ownership of these data has to be transferred. However, the existing public auditing schemes with data transfer require all the authenticators corresponding to the transferred data to be transformed to the new ones for integrity auditing. It incurs significant computation cost because of recomputing the new authenticators for all transferred data, especially when a vast quantity of data is being transferred. In addition, the data privacy and the identity privacy of the data owner cannot be protected for the verifier in such schemes. Thus, how to achieve efficient data transfer and privacy protection are key challenges in public auditing with data transfer for cloud-based IoT data. In this article, we propose a privacy-preserving identity-based public auditing scheme with efficient data transfer for cloud-based IoT data (PPADT). In PPADT, all the authenticators corresponding to the transferred data blocks do not need to be transformed. We only need to transform an aggregated authenticator in the integrity auditing phase. It means that the computation cost of data transfer is independent of the number of transferred data blocks. Furthermore, the data owner’s identity privacy can be ensured with the assistance of the private key generator. The data privacy can also be guaranteed by employing the random masking technique.