Research On Data Integrity Verification Mechanism In Cloud Computing Based On The Storage Of Evidence

With the rapid advent of the era of cloud, cloud computing has been rapid development.Cloud computing is not just a simple application software and databases into the center of the large-scale data centers, but with greater flexibility, allowing arbitrary endpoints involved in the interaction of cloud services, cloud storage services at this point has been reflected. Cloud storage for massive data storage provides a new service model. Because the data to cloud servers of third-party outsourcing service providers to manage the user eventually lost control of the data. Therefore, cloud storage is facing a number of security issues,data integrity verification Mechanism in Cloud computing is one of the problem.The traditional method for integrity verification needs all data to be downloaded to the machine to verify,but this method for the very large amount of data to cloud storage is not applicable. Read the recent literature found that currently address this issue, the main problems existing in the current data integrity verification is data block, computational overhead, limited time and public validation. In this paper, for the data block and computational problem, analysis Tripartite model validation and CBF algorithm, this paper make the following improvements:(1) For cloud storage block change caused by data update,thereby increasing the computation overhead.This paper proposes the use of semi-supervised clustering method to guidance the document block, through the use of semi-supervised clustering algorithm ICop-Kmeans file preprocessing to reduce the impact of the file data update block, saving computational overhead.(2) In this paper, we present a data integrity verification algorithm based on Counting Bloom Fileter(CBF),for integrity verification of dynamic data in cloud storage.The algorithm uses cryptographic hash function technology advantages on computational overhead and CBF high space efficiency characteristics,we save computational,storage and communication overhead.In addition,the data block size impact on the overall cost is greatly reduced.(3) Combining the above two aspects we present a data integrity verification algorithm which can support for third-party verification.Finally, analysis and simulation results show that in the data dynamically changing environment the algorithm implements lightweight integrity verification within the data lifecycle,especially in the challenge-response process, the computational overhead of cloud server and third-party auditor is reduced.