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Privacy-preserving edge-assisted image retrieval and classification in IoT |
Xuan LI1,2,3, Jin LI4( ), Siuming YIU2, Chongzhi GAO4, Jinbo XIONG1,3 |
1. College of Mathematics and Informatics, Fujian Normal University, Fuzhou 350117, China 2. Department of Computer Science, The University of Hong Kong, Hong Kong 999077, China 3. Fujian Provincial Key Laboratory of Network Security and Cryptology, Fuzhou 350117, China 4. School of Computational Science and Education Software, Guangzhou University, Guangzhou 510006, China |
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Abstract Internet of Things (IoT) has drawn much attention in recent years. However, the image data captured by IoT terminal devices are closely related to users’ personal information, which are sensitive and should be protected. Though traditional privacy-preserving outsourced computing solutions such as homomorphic cryptographic primitives can support privacy-preserving computing, they consume a significant amount of computation and storage resources. Thus, it becomes a heavy burden on IoT terminal devices with limited resources. In order to reduce the resource consumption of terminal device, we propose an edge-assisted privacy-preserving outsourced computing framework for image processing, including image retrieval and classification. The edge nodes cooperate with the terminal device to protect data and support privacy-preserving computing on the semitrusted cloud server. Under this framework, edge-assisted privacy-preserving image retrieval and classification schemes are proposed in this paper. The security analysis and performance evaluation show that the proposed schemes greatly reduce the computational, communication and storage burden of IoT terminal device while ensuring image data security.
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Keywords
Internet of Things
outsourced computation
privacy protection
cryptographic primitive
image processing
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Corresponding Author(s):
Jin LI
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Just Accepted Date: 25 July 2018
Online First Date: 30 January 2019
Issue Date: 25 June 2019
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