2019
DOI: 10.1109/mnet.001.1800507
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Toward Data Security in Edge Intelligent IIoT

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Cited by 42 publications
(21 citation statements)
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“…However, massive data need time to be transferred directly to the cloud for processing, which adds computation overhead. This computation overhead increases the latency, bandwidth, and may even lead to the unavailability of IIoT applications [2]. To address this issue, the concept of Edge/fog computing has been defined, and data can now be processed much closer to the source.…”
Section: Resultsmentioning
confidence: 99%
See 2 more Smart Citations
“…However, massive data need time to be transferred directly to the cloud for processing, which adds computation overhead. This computation overhead increases the latency, bandwidth, and may even lead to the unavailability of IIoT applications [2]. To address this issue, the concept of Edge/fog computing has been defined, and data can now be processed much closer to the source.…”
Section: Resultsmentioning
confidence: 99%
“…As a result, this led to a new industrial revolution: Industry 4.0. A new term Industrial Internet of Things (IIoT) has been used to collectively refer to proposed IoT solutions in this space [2].…”
Section: Introductionmentioning
confidence: 99%
See 1 more Smart Citation
“…They proposed a vulnerability analysis framework (VAF) that can be used to analyze 1363 vulnerabilities for IIoT systems. Data security in edge-based IIoT is investigated in [ 44 ]. Authors identify four main challenges reliable data storage, convenient data usage, efficient data search, and secure data deletion, and they proposed a cloud-fog-edge device storage framework for IIoT that addresses the challenges identified.…”
Section: Related Workmentioning
confidence: 99%
“…For the Internet case, M0 device configuration was used for simulation on all nodes, while for IoT devices three types of configurations M1-M3 were applied. Device parameters were selected on the basis of the real hardware used in Industrial Edge Computing studies [21], [22] and Cyber-Physical systems [23], [24] used for studying connected automated vehicles, together with large scaled video analysis platforms; their values are presented in Table I. Device M1 represents Raspberry PI 3 hardware, M2 is a LinkIt Smart 7688 Du IoT device, and M3 is ESP32 SoC. These values represent the maximum values of the parameters the device can reach.…”
Section: B Controllable Parametersmentioning
confidence: 99%