期刊
IEEE TRANSACTIONS ON INDUSTRIAL INFORMATICS
卷 18, 期 7, 页码 4981-4989出版社
IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
DOI: 10.1109/TII.2021.3103547
关键词
Cloud computing; Servers; Data privacy; Encryption; Indexes; Privacy; Data models; Cloud-assisted internet of things (IoT); cloud storage; edge computing; intelligent computing; privacy retrieval
类别
资金
- Natural Science Foundation of Fujian Province of China [2020J06023]
- National Natural Science Foundation of China (NSFC) [62172046]
- UIC Start-up Research Fund [R72021202, TII-21-1052]
The article introduces a privacy-enhanced retrieval technology called PERT for cloud-assisted IoT, which preserves data privacy by hiding data transmission information, and the experiments have shown its effectiveness.
In the cloud-assisted Internet of things (IoT), most of the data are sent to the cloud for storage and processing. Data privacy and security are extreme concerns since retrieving data from the cloud will yield privacy disclosure risk due to the cloud's openness. To this end, this article proposes PERT, a privacy-enhanced retrieval technology for cloud-assisted IoT. This architecture is designed through an implicit index maintained by edge servers and a hierarchical retrieval model that preserves data privacy by hiding the information of data transmission between the cloud and the edge servers. For the hierarchical retrieval model, we designed a data partition strategy. The edge server stores partial data. In this way, data privacy is preserved since the attacker must get the data maintained by both cloud and edge servers. The detailed performance analysis and extensive experiments have displayed the effectiveness of the technology for data privacy. It is tested that the architecture can efficiently and securely retrieve the stored data while the computation cost is reduced through operation downsizing. Compared with the benchmark cloud encrypted storage model, the time cost of this method is significantly reduced when the number of users is relatively large.
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