An Edge Computing-enhanced Internet of Things Framework for Privacy-preserving in Smart City
An Edge Computing-enhanced Internet of Things Framework for Privacy-preserving in Smart City
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DOI：
10.1016/j.compeleceng.2019.106504
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发表时间：
2020-01-01
影响因子：
4.3
通讯作者：
Chen, Shuhong
中科院分区：
文献类型：
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作者：
Gheisari, Mehdi;Wang, Guojun;Chen, Shuhong
为了有效地监管物联网（IoT）生成的海量数据，我们面临两个需要解决的问题：（1）物联网设备之间的异构性或满足多样性，以及（2）隐私保护或防止敏感数据的无意泄露。通过观察，我们发现现有的解决方案对所有设备应用一种通用的隐私保护规则，但它们分别解决了异构性问题，从而导致性能不佳。在本文中，我们提出了一个框架，使用新颖的本体数据模型来解决网络边缘物联网设备的异构性问题和隐私保护。此外，它利用所提出的本体通过频繁改变物联网设备的隐私保护行为来获得隐私保护方法。通过模拟，我们表明，在最坏的情况下，我们的解决方案开销不到 9%，因此在其应用之一（智慧城市）中，大多数 IoT 设备都可以负担得起。 (C) 2019 Elsevier Ltd. 保留所有权利。
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 loT 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 loT devices in one of its applications that is smart city. (C) 2019 Elsevier Ltd. All rights reserved.