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Article

Privacy-Preserving and Lightweight Selective Aggregation with Fault-Tolerance for Edge Computing-Enhanced IoT

Key Laboratory of Communication and Information Systems, School of Electronic Information Engineering, Beijing Jiaotong University, Beijing 100044, China
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Author to whom correspondence should be addressed.
Academic Editor: Jose Manuel Molina López
Sensors 2021, 21(16), 5369; https://doi.org/10.3390/s21165369
Received: 12 June 2021 / Revised: 23 July 2021 / Accepted: 6 August 2021 / Published: 9 August 2021
(This article belongs to the Special Issue Data Security and Privacy in the IoT)
Edge computing has been introduced to the Internet of Things (IoT) to meet the requirements of IoT applications. At the same time, data aggregation is widely used in data processing to reduce the communication overhead and energy consumption in IoT. Most existing schemes aggregate the overall data without filtering. In addition, aggregation schemes also face huge challenges, such as the privacy of the individual IoT device’s data or the fault-tolerant and lightweight requirements of the schemes. In this paper, we present a privacy-preserving and lightweight selective aggregation scheme with fault tolerance (PLSA-FT) for edge computing-enhanced IoT. In PLSA-FT, selective aggregation can be achieved by constructing Boolean responses and numerical responses according to specific query conditions of the cloud center. Furthermore, we modified the basic Paillier homomorphic encryption to guarantee data privacy and support fault tolerance of IoT devices’ malfunctions. An online/offline signature mechanism is utilized to reduce computation costs. The system characteristic analyses prove that the PLSA-FT scheme achieves confidentiality, privacy preservation, source authentication, integrity verification, fault tolerance, and dynamic membership management. Moreover, performance evaluation results show that PLSA-FT is lightweight with low computation costs and communication overheads. View Full-Text
Keywords: Internet of Things (IoT); edge computing; selective aggregation; privacy-preserving; fault tolerance Internet of Things (IoT); edge computing; selective aggregation; privacy-preserving; fault tolerance
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MDPI and ACS Style

Wang, Q.; Mu, H. Privacy-Preserving and Lightweight Selective Aggregation with Fault-Tolerance for Edge Computing-Enhanced IoT. Sensors 2021, 21, 5369. https://doi.org/10.3390/s21165369

AMA Style

Wang Q, Mu H. Privacy-Preserving and Lightweight Selective Aggregation with Fault-Tolerance for Edge Computing-Enhanced IoT. Sensors. 2021; 21(16):5369. https://doi.org/10.3390/s21165369

Chicago/Turabian Style

Wang, Qiannan, and Haibing Mu. 2021. "Privacy-Preserving and Lightweight Selective Aggregation with Fault-Tolerance for Edge Computing-Enhanced IoT" Sensors 21, no. 16: 5369. https://doi.org/10.3390/s21165369

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