Citation
Abstract
The Wireless Sensor Network in the Internet of Things (WSN-IoT) has been flourishing as another global breakthrough over the past few years. The WSN-IoT is reforming the way we live today by spreading through all areas of life, including the dangerous demographic aging crisis and the subsequent decline of jobs. For a company to increase revenues and cost-effectiveness growth should be customer-centered and agile within an organization. WSN-IoT networks have simultaneously faced threats, such as sniffing, spoofing, and intruders. However, WSN-IoT networks are often made up of multiple embedded devices (sensors and actuators) with limited resources that are joined via various connections in a low-power and lossy manner. However, to our knowledge, no research has yet been conducted into the security methods. Recently, a Contiki operating system’s partial implementation of Routing Protocol for Low Power & Lossy Network RPL’s security mechanisms was published, allowing us to evaluate RPL’s security methods. This paper presents a critical analysis of security issues in the WSN-IoT and applications of WSN-IoT, along with network management details using machine learning. The paper gives insights into the Internet of Things in Low Power Networks (IoT-LPN) architecture, research challenges of the Internet of Things in Low Power Networks, network attacks in WSN-IoT infrastructures, and the significant WSN-IoT objectives that need to be accompanied by current WSN-IoT frameworks. Several applied WSN-IoT security mechanisms and recent contributions have been considered, and their boundaries have been stated to be a significant research area in the future. Moreover, various low-powered IoT protocols have been further discussed and evaluated, along with their limitations. Finally, a comparative analysis is performed to assess the proposed work’s performance. The study shows that the proposed work covers a wide range of factors, whereas the rest of the research in the literature is limited.
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Official URL or Download Paper: https://www.mdpi.com/2079-9292/12/3/482
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Additional Metadata
Item Type: | Article |
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Divisions: | Faculty of Computer Science and Information Technology |
DOI Number: | https://doi.org/10.3390/electronics12030482 |
Publisher: | Multidisciplinary Digital Publishing Institute |
Keywords: | Internet of things; Industrial internet of things (IIoT); Low powered; Computer networks; Contiki; IoT security; Network management; Machine learning; Industry; Innovation; Infrastructure |
Depositing User: | Ms. Nur Aina Ahmad Mustafa |
Date Deposited: | 09 Sep 2024 03:56 |
Last Modified: | 09 Sep 2024 03:56 |
Altmetrics: | http://www.altmetric.com/details.php?domain=psasir.upm.edu.my&doi=10.3390/electronics12030482 |
URI: | http://psasir.upm.edu.my/id/eprint/107633 |
Statistic Details: | View Download Statistic |
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