The cloud storage service becomes a rising trend based on the cloud computing, which promotes the remote data integrity auditing a hot topic. Some research can audit the integrity and correctness of user data and solve the problem of user privacy leakage. However, these schemes cannot use fewer data blocks to achieve better auditing results. In this paper ,we figure out that the random sampling used in most auditing schemes is not well apply to the problem of cloud service provider (CSP) deleting the data that users rarely use, and we adopt the probability proportionate to size sampling (PPS) to handle such situation. A new scheme named improving audit efficiency of remote data for cloud storage is designed. The proposed scheme supports the public auditing with fewer data blocks and constrains the server's malicious behavior to extend the auditing cycle. Compared with the relevant schemes, the experimental results show that the proposed scheme is more effective.
Summary
In recent years, cloud storage technology is developed maturely, so data owners could deposit data to relieve the storage pressure. In vehicular communication networks, vehicles tend to use low‐latency networks to transfer the valid road information and vehicle information generated by smart sensors in real time. Vehicular edge computing (VEC) networks satisfy the low‐latency requirements of the vehicular communication networks. However, vehicles have no space to store a copy of the data locally like using a local storage service. Vehicles, as users of cloud storage, pay attention to the integrity of the data especially. Unfortunately, many existing auditing schemes for integrity are not fully applicable to the VEC paradigm, because of significant differences in security assumptions. In this paper, a dynamic public audit protocol is proposed to the VEC paradigm. First, a new threat model is defined to formalize noncollusive and collusive attacks according to VEC servers and cloud server providers. Second, we propose a novel auditing protocol based on hash‐balanced binary tree (HBBT) and describe the auditing process and dynamic operations. Third, security analysis and experimental analysis are completed to demonstrate the safety and effectiveness of the proposed scheme.
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