A Privacy-Enhanced Retrieval Technology for the Cloud-Assisted Internet of Things
| Autor: | Kapal Dev, Yang Quan, Tian Wang, Weizheng Wang, Thippa Reddy Gadekallu, Xuewei Shen Shen |
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| Rok vydání: | 2022 |
| Předmět: |
Information privacy
business.industry Computer science Cloud computing Encryption Storage model Computer Science Applications Control and Systems Engineering Server Benchmark (computing) Enhanced Data Rates for GSM Evolution Electrical and Electronic Engineering business Information Systems Computer network Data transmission |
| Zdroj: | IEEE Transactions on Industrial Informatics. 18:4981-4989 |
| ISSN: | 1941-0050 1551-3203 |
| DOI: | 10.1109/tii.2021.3103547 |
| Popis: | In the Cloud-assisted Internet of Things (IoT), most of the data is sent to the cloud for storage and processing. Data privacy and security are major concerns. To this end, this paper 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 to offload parts of data stored in edge servers that paves for preservation of data privacy. The extensive experiments have displayed the effectiveness of the technology for data privacy. It is also verified that the architecture can reduce computational cost. Compared with the benchmark cloud encrypted storage model, the time cost of this method is significantly reduced. |
| Databáze: | OpenAIRE |
| Externí odkaz: |
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