Abstract
In order to additionally solve the problems of data leakage, tampering, and malicious sharing in the cloud environment, the study proposes a fog computing-based privacy data storage and query mechanism, which employs multilevel data partitioning and hybrid encrypted transmission. Meanwhile, a combined data resource sharing scheme based on virtualized shared datasets is proposed for efficient management of privacy data in enterprise sensing cloud systems. The experimental results show that the accuracy of data retrieval and recovery obtained by the research method is above 98% and are more stable in the case of data size growth. The data retrieval of the shared mechanism consumes less than 2 s, while the non-adaptive cloud storage scheme consumes up to 7 s. The experimental results show that the hybrid encryption mechanism in the scheme has a greater effect on ensuring data privacy and has a high practical value. The improved scheme proposed in the study helps to ensure data privacy, reduce data redundancy and has lower power loss under cloud data storage and query mechanism. Research not only reduces labor and time costs, but also improves the protection of private data. At the same time, it has also made practical and powerful contributions to promoting the interconnection of information systems in various industries and realizing the beautiful vision of informatization and smart life services.
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