Abstract

In cloud computing, data owners host their data on cloud servers, and users (data consumers) can access the data from the cloud servers. This new paradigm of data hosting service also introduces new security challenges that require an independent auditing service to check the integrity of the data in the cloud. Some existing methods for checking the integrity of the data cannot handle this problem efficiently and they cannot deal with the error condition. Thus, a secure and efficient dynamic auditing protocol should reject requests that are made with improper authentication. In addition, an excellent remote data authentication method should be able to collect information for statistical analysis, such as validation results. In this paper, first we design an auditing framework for cloud storage systems and propose an efficient and privacy-preserving auditing protocol. Then, we extend our auditing protocol to support dynamic data operations, which is efficient and has been proven to be secure in the random oracle model. We extended our auditing protocol further to support bidirectional authentication and statistical analysis. In addition, we use a better load distribution strategy, which greatly reduces the computational overhead of the client. Last, we provide an error response scheme, and our experiments show that our solution has good error-handling ability and offers lower overhead expenses for computation and communication than other approaches.

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