Blockchain provides new technologies and ideas for the construction of agricultural product traceability system (APTS). However, if data is stored, supervised, and distributed on a multiparty equal blockchain, it will face major security risks, such as data privacy leakage, unauthorized access, and trust issues. How to protect the privacy of shared data has become a key factor restricting the implementation of this technology. We propose a secure and trusted agricultural product traceability system (BCST-APTS), which is supported by blockchain and CP-ABE encryption technology. It can set access control policies through data attributes and encrypt data on the blockchain. This can not only ensure the confidentiality of the data stored in the blockchain, but also set flexible access control policies for the data. In addition, a whole-chain attribute management infrastructure has been constructed, which can provide personalized attribute encryption services. Furthermore, a reencryption scheme based on ciphertext-policy attribute encryption (RE-CP-ABE) is proposed, which can meet the needs of efficient supervision and sharing of ciphertext data. Finally, the system architecture of the BCST-APTS is designed to successfully solve the problems of mutual trust, privacy protection, fine-grained, and personalized access control between all parties.
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 privacypreserving 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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