Research On A Recoverable Cloud Data Audit Scheme Supporting Dynamic Operations

With the advanced development of communication and network technology,various data have penetrated into all aspects of people's daily life.More and more users would like to outsource their data to cloud servers.How to ensure the integrity of outsourced data has become a key issue that need to be addressed urgently in cloud storage.The cloud data auditing scheme can verify the data through auxiliary information to determine whether the integrity of the data is damaged,which provides a certain guarantee for the security of user's data.However,traditional cloud data auditing schemes focus on auditing the integrity of outsourced data,while ignoring the performance requirements of data dynamics and the functional requirements of subsequent operations after auditing failures.On the one hand,the existing data structure cannot support the requirement of efficient dynamic auditing when the file data is large,and the cloud data auditing schemes based on these structures cannot support the privacy protection of user's data and resist the replay attacks and replacing attacks from malicious cloud servers.On the other hand,in the traditional cloud data auditing scheme,user's key update will lead to recalculation of data block verification tags,fair arbitration for auditing results is lacked,and corrupted data cannot be efficiently located and recovered,resulting in the auditing program is less practical.To solve the above problems,the corresponding solutions are proposed in this paper,which are summarized as follows:(1)Privacy protecting cloud data auditing scheme with data dynamicsTo solve the low efficiency of data dynamics and the lack of data privacy protection in the current scheme,this paper designs a cloud data dynamic auditing scheme that supports privacy protection.The scheme first designs a new data structure,which optimizes the dynamic operations of data and improves the efficiency of dynamic auditing.Secondly,in order to ensure the privacy of user data,the random mask technology is used to mask the data aggregation,so that the auditor cannot obtain the original content of the data.Finally,by embedding a unique random mask value in the verification tag of each data block,the replay attacks and replacing attacks launched by the cloud server cannot pass the auditing verification.The comparison results of theoretical and simulation analysis can show that the scheme proposed can reduce the overhead of data dynamics and further improve the security of user data.(2)Recoverable cloud data auditing scheme with key update and data dynamicsTo solve the problems including low user's key update efficiency,the lack of reliable auditing result arbitration,and difficult to locate and recover corrupted data efficiently,this paper designs a recoverable cloud data auditing scheme that supports key update and fair arbitration based on the data dynamics of the above research.First,the scheme improves the key update mechanism,avoids the recalculation of the data verification tags caused by the key update,and improves the efficiency of key update.Secondly,a fair arbitration mechanism is designed,which can resist the framed attacks and collusion attacks of malicious TPA and cloud server,and improve the fairness of the auditing system.Finally,in the fair arbitration mechanism,the scheme uses the improved cuckoo filter technology and erasure code technology to achieve rapid location and safe recovery of corrupted data,so that user's data can be recovered in time when the auditing fails,improving the reliability of data acquisition.By the results of security analysis,theoretical analysis and simulation analysis,it can be known that the designed scheme is secure and has better performance.