Privacy-Preserving IoT Data Retrieval Scheme With Lightweight Fine-Grained Access Control in Cloud Computing
With the rapid development of cloud computing technology, cloud services, represented by cloud storage and data retrieval, have been widely researched in Internet of Things (IoT). As a result, various data retrieval schemes have been proposed. The multikeyword Ranked Searchable Encryption Scheme (MRSE) was developed to improve the accuracy and experience of users searching data. However, MRSE has its drawbacks, such as the security risk of key leakage and limited functionality. Therefore, this article proposes a Privacy-preserving IoT Data Retrieval Scheme (PDRS) that supports lightweight fine-grained access control. We analyze the risk of key information leakage in MRSE, and perform permutation operations on encrypted indexes and trapdoors in PDRS to prevent key leakage and improve system security. Furthermore, in IoT scenarios with multiusers and multikeys, the secure user identity authentication mechanism ensures that only authorized users can acquire legitimate keys to generate search trapdoors, preventing malicious users from impersonating legitimate users and accessing private data. A novel polynomial-based access control is designed to realize attribute-based fine-grained access control, which enables resource-limited devices to limit data access to data users and achieves lightweight overhead. Finally, a formal theoretical analysis demonstrates that PDRS is secure. Simulation experiments verify that PDRS is efficient and lightweight.
Authors
- Junsong Fu (ORCID: https://orcid.org/0000-0002-2445-1987)
- Qianhong Wu (ORCID: https://orcid.org/0000-0002-6407-4194)
- Lunzhi Deng (ORCID: https://orcid.org/0000-0002-9688-1062)
- Zhiquan Liu (ORCID: https://orcid.org/0000-0002-3934-2177)
- Na Wang (ORCID: https://orcid.org/0000-0002-8687-8820)
- Wen Zhou
Institutions
- Beijing University of Posts and Telecommunications (CN)
- Guizhou Normal University (CN)
- Jinan University (CN)
- Beihang University (CN)
Publication Details
- Journal
- IEEE Internet of Things Journal
- Published
- 2024-12-18
- DOI
- https://doi.org/10.1109/jiot.2024.3519578
- Citations
- 2
- Primary Topic
- Privacy-Preserving Technologies in Data
- Type
- article
- Field-Weighted Citation Impact
- 0.69
Funders
- National Natural Science Foundation of China