4.8 Article

Lightweight Privacy-Preserving Scheme Using Homomorphic Encryption in Industrial Internet of Things

Journal

IEEE INTERNET OF THINGS JOURNAL
Volume 9, Issue 16, Pages 14542-14550

Publisher

IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
DOI: 10.1109/JIOT.2021.3066427

Keywords

Industrial Internet of Things; Data privacy; Security; Industries; Encryption; Servers; Privacy; Industrial Internet of Things (IIoT); IoT security; lightweight privacy; provenance; security

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The emerging technologies in IoT, such as smart sensors, 5G/6G wireless communication, and artificial intelligence, have revolutionized business operations by enabling efficient and privacy-preserving collection and transmission of real-time data. However, privacy concerns remain a major challenge. This study proposes a lightweight privacy-preserving scheme based on homomorphic encryption in IoT, effectively protecting user privacy through computationally efficient algorithms.
The emerging technologies, such as smart sensors, 5G/6G wireless communication, artificial intelligence, etc., have been maturing the future Internet of Things (IoT) by connecting the massive number of devices, which are expected to consistently collect and transmit real-time data to support business intelligence in an efficient and privacy-preserving way. The IoT can afford businesses predictive maintenance, improve field service, asset tracking, and further enhance customer satisfaction and facility management in industrial sectors. However, the privacy concern in IoT is a big challenge in IoT applications and services. This work proposed a lightweight privacy-preserving scheme based on homomorphic encryption in the context of the IoT, in which we investigated and analyzed the privacy issues between the data owners, untrustworthy third-party cloud servers, and the data users. Meanwhile, computationally efficient homomorphic algorithms are proposed to guarantee the privacy protection for the data users. Experimental results demonstrate that the proposed scheme can effectively prevent privacy breaches in IoT.

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