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Title A context-aware privacy-preserving method for IoT-based smart city using Software Defined Networking
ID_Doc 36794
Authors Gheisari, M; Wang, GJ; Khan, WZ; Fernández-Campusano, C
Title A context-aware privacy-preserving method for IoT-based smart city using Software Defined Networking
Year 2019
Published
DOI 10.1016/j.cose.2019.02.006
Abstract Smart City is an application of the Internet of Things (IoT) with the aim of managing cities without human intervention. Each IoT device that is producing data may sense a sensitive one that should not be disclosed unintentionally. Due to the existence of a large number of devices in the near future, the possibility of information leakage, privacy breach, is increasing. To prevent this, each device applies a privacy-preserving method. We discover that all of the existing solutions have three major drawbacks: (1) applying one static privacy-preserving method for the entire system, (2) sending whole data at once, and (3) not context-aware. These cause unacceptable privacy-preserving degree. To address them, in this paper, at first, we equip IoT-based smart city with Software Defined Networking paradigm (SDN). Then, we mount an efficient privacy-preserving method on top of it that manages flowing data packets of split IoT device' data. We have done extensive simulation through MININET-WIFI to show the effectiveness of our approach. Evaluation results show that our method can be widely applied to the smart city application with a superior performance regarding accuracy, overhead, and penetration rate compared to existing privacy-preserving solutions. (C) 2019 Published by Elsevier Ltd.
Author Keywords SDN; IoT; Privacy; Context-aware; Dynamic; Internet of Things; Penetration rate; Software Defined Networking; Smart city; VPN
Index Keywords Index Keywords
Document Type Other
Open Access Open Access
Source Science Citation Index Expanded (SCI-EXPANDED)
EID WOS:000494048500045
WoS Category Computer Science, Information Systems
Research Area Computer Science
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