Research On Integrity Verification Mechanism Based On Cloud Storage

At present,with the rapid development of cloud computing in recent years,its related products have also been the development of blowout,and cloud storage in the cloud computing products occupy an important position,due to the amount of data presented an explosive increase in data Of the storage also put forward new requirements,the traditional storage has been far from being able to meet the current storage requirements,the emergence of cloud storage to meet people’s demand for massive data storage,but with the cloud storage-related security issues,Cloud storage to bring convenience to people at the same time also for illegal data theft provides a way.Security issues become a bottleneck in the development of cloud storage,how to make the user’s data to ensure security,not intentionally or unintentionally tampering,in what way allows users to more easily know the security of the data,whether the damage.This paper focuses on the verification of data integrity on cloud storage.By comparing the advantages and disadvantages of the existing integrity verification mechanism.And further propose a new integrity verification mechanism to better assist in data integrity verification.The main contents of the thesis include:1.The paper first combs and analyzes several current verification methods,and focuses on the MHT model.Then,the R-MHT model is proposed.After the R-MHT model is defined and the function is defined,two kinds of detection processes in the model are constructed,and three kinds of operation algorithms of R-MHT model modification,insertion and deletion are given.2.For the proposed R-MHT model,theoretically,theoretically,the calculation,communication and storage complexity are obtained.The calculated complexity is compared with that of POR,PDP and MHT,and the advantages of R-MHT model are obtained.Then,the simulation experiment is carried out on Hadoop.Through the simulation experiment on Hadoop,we can get the advantage of R-MHT model in response time of R-MHT model under certain data block.