Privacy-Enhanced Cooperative Storage Scheme for Contact-Free Sensory Data in AIoT with Efficient Synchronization
Article No.: 84, Pages 1 - 19
Abstract
The growing popularity of contact-free smart sensing has contributed to the development of the Artificial Intelligence of Things (AIoT). The contact-free sensory data has great potential to mine and analyze the hidden information for AIoT-enabled applications. However, due to the limited storage resource of contact-free smart sensing devices, data is naturally stored in the cloud, which is at risk of privacy leakage. Cloud storage is generally considered insecure. On one hand, the openness of the cloud environment makes the data easy to be attacked, and the complex AIoT environment also makes the data transmission process vulnerable to the third party. On the other hand, the Cloud Service Provider (CSP) is untrusted. In this article, to ensure the security of data from contact-free smart sensing devices, a Cloud-Edge-End cooperative storage scheme is proposed, which takes full advantage of the differences in the cloud, edge, and end. Firstly, the processed sensory data is stored separately in the three layers by utilizing well-designed data partitioning strategy. This scheme can increase the difficulty of privacy leakage in the transmission process and avoid internal and external attacks. Besides, the contact-free sensory data is highly time-dependent. Therefore, combined with the Cloud-Edge-End cooperation model, this article proposes a delta-based data update method and extends it into a hybrid update mode to improve the synchronization efficiency. Theoretical analysis and experimental results show that the proposed cooperative storage method can resist various security threats in bad situations and outperform other update methods in synchronization efficiency, significantly reducing the synchronization overhead in AIoT.
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Index Terms
- Privacy-Enhanced Cooperative Storage Scheme for Contact-Free Sensory Data in AIoT with Efficient Synchronization
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Publication History
Published: 11 May 2024
Online AM: 02 September 2023
Accepted: 25 June 2023
Revised: 31 May 2023
Received: 20 December 2022
Published in TOSN Volume 20, Issue 4
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- National Key R&D Program of China
- National Natural Science Foundation of China (NSFC)
- Beijing Natural Science Foundation
- Guangdong Provincial Natural Science Foundation
- Key University Science Research Project of Anhui Province
- Special Project of Guangdong Provincial Department of Education in Key Fields of Colleges and Universities
- Joint Project of Production, Teaching and Research of Zhuhai
- Guangdong Key Lab of AI and Multi-modal Data Processing, BNU-HKBU United International College (UIC), Zhuhai
- UIC General Project
- UIC Start-up Research Fund
- Zhuhai Basic and Applied Basic Research Foundation
- Joint Project of Production, Teaching and Research of Zhuhai
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