Privacy-Preserving Efficient Data Retrieval in IoMT Based on Low-Cost Fog Computing
The rapid development of Internet of Medical Things (IoMT) is remarkable. However, IoMT faces many problems including privacy disclosure, long delay of service orders, low retrieval efficiency of medical data, and high energy cost of fog computing. For these, this paper proposes a data privacy prote...
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| Format: | Article |
| Language: | English |
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Wiley
2021-01-01
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| Series: | Complexity |
| Online Access: | http://dx.doi.org/10.1155/2021/6211475 |
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| author | Na Wang Yuanyuan Cai Junsong Fu Jie Xu |
| author_facet | Na Wang Yuanyuan Cai Junsong Fu Jie Xu |
| author_sort | Na Wang |
| collection | DOAJ |
| description | The rapid development of Internet of Medical Things (IoMT) is remarkable. However, IoMT faces many problems including privacy disclosure, long delay of service orders, low retrieval efficiency of medical data, and high energy cost of fog computing. For these, this paper proposes a data privacy protection and efficient retrieval scheme for IoMT based on low-cost fog computing. First, a fog computing system is located between a cloud server and medical workers, for processing data retrieval requests of medical workers and orders for controlling medical devices. Simultaneously, it preprocesses physiological data of patients uploaded by IoMT, collates them into various data sets, and transmits them to medical institutions in this way. It makes the entire execution process of low latency and efficient. Second, multidimensional physiological data are of great value, and we use ciphertext retrieval to protect privacy of patient data in this paper. In addition, this paper uses range tree to build an index for storing physiological data vectors, and meanwhile a range retrieval method is also proposed to improve data search efficiency. Finally, bat algorithm (BA) is designed to allocate cost on a fog server group for significant energy cost reduction. Extensive experiments are conducted to demonstrate the efficiency of the proposed scheme. |
| format | Article |
| id | doaj-art-63ab967a7bfc4b039333912b034aa761 |
| institution | Kabale University |
| issn | 1076-2787 1099-0526 |
| language | English |
| publishDate | 2021-01-01 |
| publisher | Wiley |
| record_format | Article |
| series | Complexity |
| spelling | doaj-art-63ab967a7bfc4b039333912b034aa7612025-02-03T06:10:45ZengWileyComplexity1076-27871099-05262021-01-01202110.1155/2021/62114756211475Privacy-Preserving Efficient Data Retrieval in IoMT Based on Low-Cost Fog ComputingNa Wang0Yuanyuan Cai1Junsong Fu2Jie Xu3School of Cyber Science and Technology, Beihang University, Beijing, ChinaNational Engineering Laboratory for Agri-Product Quality Traceability, Beijing Technology and Business University, Beijing, ChinaSchool of Cyberspace Security, Beijing University of Posts and Telecommunications, Beijing, ChinaSchool of Cyberspace Security, Beijing University of Posts and Telecommunications, Beijing, ChinaThe rapid development of Internet of Medical Things (IoMT) is remarkable. However, IoMT faces many problems including privacy disclosure, long delay of service orders, low retrieval efficiency of medical data, and high energy cost of fog computing. For these, this paper proposes a data privacy protection and efficient retrieval scheme for IoMT based on low-cost fog computing. First, a fog computing system is located between a cloud server and medical workers, for processing data retrieval requests of medical workers and orders for controlling medical devices. Simultaneously, it preprocesses physiological data of patients uploaded by IoMT, collates them into various data sets, and transmits them to medical institutions in this way. It makes the entire execution process of low latency and efficient. Second, multidimensional physiological data are of great value, and we use ciphertext retrieval to protect privacy of patient data in this paper. In addition, this paper uses range tree to build an index for storing physiological data vectors, and meanwhile a range retrieval method is also proposed to improve data search efficiency. Finally, bat algorithm (BA) is designed to allocate cost on a fog server group for significant energy cost reduction. Extensive experiments are conducted to demonstrate the efficiency of the proposed scheme.http://dx.doi.org/10.1155/2021/6211475 |
| spellingShingle | Na Wang Yuanyuan Cai Junsong Fu Jie Xu Privacy-Preserving Efficient Data Retrieval in IoMT Based on Low-Cost Fog Computing Complexity |
| title | Privacy-Preserving Efficient Data Retrieval in IoMT Based on Low-Cost Fog Computing |
| title_full | Privacy-Preserving Efficient Data Retrieval in IoMT Based on Low-Cost Fog Computing |
| title_fullStr | Privacy-Preserving Efficient Data Retrieval in IoMT Based on Low-Cost Fog Computing |
| title_full_unstemmed | Privacy-Preserving Efficient Data Retrieval in IoMT Based on Low-Cost Fog Computing |
| title_short | Privacy-Preserving Efficient Data Retrieval in IoMT Based on Low-Cost Fog Computing |
| title_sort | privacy preserving efficient data retrieval in iomt based on low cost fog computing |
| url | http://dx.doi.org/10.1155/2021/6211475 |
| work_keys_str_mv | AT nawang privacypreservingefficientdataretrievaliniomtbasedonlowcostfogcomputing AT yuanyuancai privacypreservingefficientdataretrievaliniomtbasedonlowcostfogcomputing AT junsongfu privacypreservingefficientdataretrievaliniomtbasedonlowcostfogcomputing AT jiexu privacypreservingefficientdataretrievaliniomtbasedonlowcostfogcomputing |