Fine-Grained Ranked Multi-Keyword Search Over Hierarchical Data for IoT-Oriented Health System
With the rapid advance of the Internet of Things (IoT) and cloud computing technologies, the IoT-oriented health is expected to greatly improve the quality of healthcare service. However, data security and privacy concerns have become one of the biggest issues in smart health applications. As a pote...
| Main Authors: | , , |
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| Format: | Article |
| Language: | English |
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IEEE
2019-01-01
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| Series: | IEEE Access |
| Subjects: | |
| Online Access: | https://ieeexplore.ieee.org/document/8782454/ |
| _version_ | 1818611563161976832 |
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| author | Jianfei Sun Shengnan Hu Xuyun Nie |
| author_facet | Jianfei Sun Shengnan Hu Xuyun Nie |
| author_sort | Jianfei Sun |
| collection | DOAJ |
| description | With the rapid advance of the Internet of Things (IoT) and cloud computing technologies, the IoT-oriented health is expected to greatly improve the quality of healthcare service. However, data security and privacy concerns have become one of the biggest issues in smart health applications. As a potential and promising solution, attribute-based keyword search (ABKS) can provide fine-grained keyword search and access control over the encrypted data at the same time. Nevertheless, prior ABKS schemes cannot simultaneously support fine-grained, effective, and accurate data retrieval over hierarchical data. In this paper, to tackle these issues, we propose a fine-grained ranked multi-keyword search scheme over hierarchical data by leveraging ciphertext-policy hierarchical attribute-based encryption (CP-HABE) and ranked multi-keyword search (RMKS) technologies. Then, we prove that our proposed scheme is selectively secure through security analysis and we also show the practicability and feasibility of the proposed scheme by performance evaluation. |
| first_indexed | 2024-12-16T15:32:19Z |
| format | Article |
| id | doaj.art-d0a3738c29a243e38d1e468a5aee907c |
| institution | Directory Open Access Journal |
| issn | 2169-3536 |
| language | English |
| last_indexed | 2024-12-16T15:32:19Z |
| publishDate | 2019-01-01 |
| publisher | IEEE |
| record_format | Article |
| series | IEEE Access |
| spelling | doaj.art-d0a3738c29a243e38d1e468a5aee907c2022-12-21T22:26:18ZengIEEEIEEE Access2169-35362019-01-01710196910198010.1109/ACCESS.2019.29284418782454Fine-Grained Ranked Multi-Keyword Search Over Hierarchical Data for IoT-Oriented Health SystemJianfei Sun0https://orcid.org/0000-0002-6944-8378Shengnan Hu1Xuyun Nie2https://orcid.org/0000-0003-2868-0442School of Information and Software Engineering, University of Electronic Science and Technology of China, Chengdu, ChinaSchool of Information and Software Engineering, University of Electronic Science and Technology of China, Chengdu, ChinaSchool of Information and Software Engineering, University of Electronic Science and Technology of China, Chengdu, ChinaWith the rapid advance of the Internet of Things (IoT) and cloud computing technologies, the IoT-oriented health is expected to greatly improve the quality of healthcare service. However, data security and privacy concerns have become one of the biggest issues in smart health applications. As a potential and promising solution, attribute-based keyword search (ABKS) can provide fine-grained keyword search and access control over the encrypted data at the same time. Nevertheless, prior ABKS schemes cannot simultaneously support fine-grained, effective, and accurate data retrieval over hierarchical data. In this paper, to tackle these issues, we propose a fine-grained ranked multi-keyword search scheme over hierarchical data by leveraging ciphertext-policy hierarchical attribute-based encryption (CP-HABE) and ranked multi-keyword search (RMKS) technologies. Then, we prove that our proposed scheme is selectively secure through security analysis and we also show the practicability and feasibility of the proposed scheme by performance evaluation.https://ieeexplore.ieee.org/document/8782454/Internet of Thingsfine-grained and rankedmulti-keyword retrievalhierarchical data |
| spellingShingle | Jianfei Sun Shengnan Hu Xuyun Nie Fine-Grained Ranked Multi-Keyword Search Over Hierarchical Data for IoT-Oriented Health System IEEE Access Internet of Things fine-grained and ranked multi-keyword retrieval hierarchical data |
| title | Fine-Grained Ranked Multi-Keyword Search Over Hierarchical Data for IoT-Oriented Health System |
| title_full | Fine-Grained Ranked Multi-Keyword Search Over Hierarchical Data for IoT-Oriented Health System |
| title_fullStr | Fine-Grained Ranked Multi-Keyword Search Over Hierarchical Data for IoT-Oriented Health System |
| title_full_unstemmed | Fine-Grained Ranked Multi-Keyword Search Over Hierarchical Data for IoT-Oriented Health System |
| title_short | Fine-Grained Ranked Multi-Keyword Search Over Hierarchical Data for IoT-Oriented Health System |
| title_sort | fine grained ranked multi keyword search over hierarchical data for iot oriented health system |
| topic | Internet of Things fine-grained and ranked multi-keyword retrieval hierarchical data |
| url | https://ieeexplore.ieee.org/document/8782454/ |
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