网络与信息安全学报 (Oct 2022)
Proof of storage with corruption identification and recovery for dynamic group users
Abstract
The outsourced storage mode of cloud computing leads to the separation of data ownership and management rights of data owners, which changes the data storage network model and security model.To effectively deal with the software and hardware failures of the cloud server and the potential dishonest service provider and also ensure the availability of the data owners’ data, the design of secure and efficient data availability and recoverability auditing scheme has both theoretical and practical importance in solving the concern of users and ensuring the security of cloud data.However, most of the existing studies were designed for the security and efficiency of data integrity or recoverability schemes, without considering the fast identification and reliable recovery of damaged data under dynamic group users.Thus, to quickly identify and recover damaged data, a publicly verifiable proof of storage scheme was proposed for dynamic group cloud users.The designed scheme enabled a trusted third-party auditor to efficiently identify the damaged files through a challenge-response protocol and allowed the cloud storage server to effectively recover them when the degree of data damage is less than an error correction ability threshold.The scheme combined association calculation and accumulation calculation, which effectively reduced the number of calculations for the identification of damaged data.By combining erasure coding and shared coding technology, the scheme achieved effective recovery of damaged data of dynamic group users.At the same time, the scheme also supported dynamic user revocation, which ensured the integrity audit and reliable recovery of the collective data after user revocation.The network model and threat model of the designed scheme were defined and the security of the scheme under the corresponding security model was proved.Through the prototype implementation of the scheme in the real environment and the modular performance analysis, it is proved that the proposed scheme can effectively identify the damaged data and reliably recover the cloud data when the data is damaged.Besides, compared with other schemes, it is also proved that the proposed scheme has less computational overhead in identifying and recovering damaged data.
