An Edge Computing-enhanced Internet of Things Framework for Privacy-preserving in Smart City. (January 2020)

• Record Type: Journal Article
• Authors: Gheisari, Mehdi; Wang, Guojun; Chen, Shuhong
• Is Part Of: Computers & electrical engineering. Volume 81(2020)
• Publication Date: 2020-01
• Subjects: Privacy-preserving -- Smart city -- Ontology -- Edge computing -- Internet of things -- Owner -- Privacy -- IoT -- Cloud computing; Computer engineering -- Periodicals; Electrical engineering -- Periodicals; Electrical engineering -- Data processing -- Periodicals; Ordinateurs -- Conception et construction -- Périodiques; Électrotechnique -- Périodiques; Électrotechnique -- Informatique -- Périodiques; Computer engineering; Electrical engineering; Electrical engineering -- Data processing; Periodicals; Electronic journals; 621.302854
• DOI: 10.1016/j.compeleceng.2019.106504
• Languages: English
• ISSNs: 0045-7906

Abstract

Abstract: To supervise massive generated data by the Internet of Things (IoT) efficiently, we face two issues that should be addressed which are: (1) heterogeneity or satisfying diversity among IoT devices, and (2) privacy-preserving or preventing unintentional disclosure of sensitive data. Through observation, we found that existing solutions apply one common privacy-preserving rule for all devices while they address the heterogeneity issue separately that lead to unappealing performance. In this paper, we propose a framework for addressing the heterogeneity issue and privacy-preserving of IoT devices at the network edge using a novel proposed ontology data model. Besides, it leverages the proposed ontology to obtain a privacy-preserving method by frequently changing the privacy-preserving behaviors of IoT devices. Through simulation, we show that our solution overhead is less than 9 percent in the worst situation so that it is affordable to most IoT devices in one of its applications that is smart city.