Research On Multi-challenge Verification Algorithms For Cloud Storage Data Integrity

Features such as the elastic scalability of cloud storage reduce the hardware and management costs of data storage for data owners.However,the data owner loses direct control over the data after hosting the data to the cloud service provider,making the data integrity a security risk of malicious corruption or deletion.Data integrity verification has become an important method for testing the integrity of data stored in the cloud.However,existing validation schemes use random sampling to validate some data when facing the challenge of multiple consecutive rounds of validation,when the probability of corrupted data being extracted cannot guarantee the detection of all corrupted data with a small number of limited validations.In addition,existing validation schemes cannot safely and efficiently aggregate multiple validation challenges at the same time to reduce the validation overhead.To this end,this paper addresses the validation of multiple challenges,and its main work is as follows:For multiple consecutive validation challenges,to increase the probability of corrupted data being extracted during each validation round and thus increase the number of corrupted data detected in a limited number of validations,this paper proposes a data integrity verification algorithm for successive multi-round challenges.The algorithm first analyzes the impact of data corruption forms on data integrity.Next,the relationship between the integrity of unverified data blocks and verified data blocks is derived for continuous type corruption.Then the convolution kernel is designed based on the derived results,and the convolution is used to calculate the integrity probability inference value for each unverified data block.Finally,based on the results of the convolution calculation,stratified sampling and optimal allocation are used to improve the probability of corrupted data blocks being extracted.For multiple verifiers to challenge the same data at the same time,to aggregate multiple validation challenges securely and efficiently,and thus reduce the duplication overhead in the process of computing evidence for cloud service providers,this paper proposes a simultaneous multi-challenge data integrity verification algorithm.The algorithm first analyzes the probability of having duplicate challenge data in multiple validation challenges.Secondly,the token of challenge information is designed based on existing security assumptions to ensure the unforgeability of challenge information.Then multiple validation challenges are aggregated and unique validation evidence is computed and the validity of the aggregated evidence is guaranteed.Finally,the verifier verifies the returned verification evidence based on the token of the challenge information,thus ensuring the authenticity and consistency of the verification results.Finally,the theoretical analysis and experimental results show that the successive multichallenge verification algorithm in this paper achieves that the verifier can dynamically adjust the extraction strategy of data blocks based on the existing verification results and reduce the number of verifications required to detect all corruptions;the simultaneous multi-challenge verification algorithm in this paper achieves effective aggregation of multiple verification challenges and reduces the duplication overhead caused by repeated computation of the same data while realizing that the cloud service provider returns unique validation evidence for multiple validation challenges,which ensures the safety and validity of the validation evidence.