Name
Title | ||
|---|---|---|
An Edge Computing-enhanced Internet of Things Framework for Privacy-preserving in Smart City |
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. |
Year | DOI | Venue |
|---|---|---|
2020 | 10.1016/j.compeleceng.2019.106504 | Computers & Electrical Engineering |
Keywords | Field | DocType |
Privacy-preserving,Smart city,Ontology,Edge computing,Internet of things,Owner,Privacy,IoT,Cloud computing | Edge computing,Computer science,Computer security,Internet of Things,Computer network,Smart city | Journal |
Volume | ISSN | Citations |
81 | 0045-7906 | 2 |
PageRank | References | Authors |
0.36 | 5 | 3 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Mehdi Gheisari | 1 | 37 | 7.38 |
| Guojun Wang | 2 | 437 | 47.52 |
| Shuhong Chen | 3 | 6 | 2.84 |