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A Randomness Detection Method of ZigBee Protocol in a Wireless Sensor Network
This study investigates the randomness detection of cryptographic algorithms in network security. To effectively test and verify the security of ZigBee protocol in the Internet of Things, the study combines with the characteristics of ZigBee networks, and it rationally organizes and divides test mod...
Autores principales: | , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2018
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6263650/ https://www.ncbi.nlm.nih.gov/pubmed/30445740 http://dx.doi.org/10.3390/s18113962 |
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author | Tang, Yongli Lian, Huanhuan Li, Lixiang Wang, Xiaojun Yan, Xixi |
author_facet | Tang, Yongli Lian, Huanhuan Li, Lixiang Wang, Xiaojun Yan, Xixi |
author_sort | Tang, Yongli |
collection | PubMed |
description | This study investigates the randomness detection of cryptographic algorithms in network security. To effectively test and verify the security of ZigBee protocol in the Internet of Things, the study combines with the characteristics of ZigBee networks, and it rationally organizes and divides test modes based on the binary matrix rank theory test. Then this paper proposes a randomness detection method of ZigBee protocol in a wireless sensor network. The proposed method solves the one-sidedness that the binary matrix rank test simply assesses random sequences by linear correlation. The proposed assessment method can effectively appraise whether the ZigBee protocol has an encryption mechanism and encryption strength. Simulation results show that this method has the characteristics of fewer errors and high reliability. |
format | Online Article Text |
id | pubmed-6263650 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2018 |
publisher | MDPI |
record_format | MEDLINE/PubMed |
spelling | pubmed-62636502018-12-12 A Randomness Detection Method of ZigBee Protocol in a Wireless Sensor Network Tang, Yongli Lian, Huanhuan Li, Lixiang Wang, Xiaojun Yan, Xixi Sensors (Basel) Article This study investigates the randomness detection of cryptographic algorithms in network security. To effectively test and verify the security of ZigBee protocol in the Internet of Things, the study combines with the characteristics of ZigBee networks, and it rationally organizes and divides test modes based on the binary matrix rank theory test. Then this paper proposes a randomness detection method of ZigBee protocol in a wireless sensor network. The proposed method solves the one-sidedness that the binary matrix rank test simply assesses random sequences by linear correlation. The proposed assessment method can effectively appraise whether the ZigBee protocol has an encryption mechanism and encryption strength. Simulation results show that this method has the characteristics of fewer errors and high reliability. MDPI 2018-11-15 /pmc/articles/PMC6263650/ /pubmed/30445740 http://dx.doi.org/10.3390/s18113962 Text en © 2018 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/). |
spellingShingle | Article Tang, Yongli Lian, Huanhuan Li, Lixiang Wang, Xiaojun Yan, Xixi A Randomness Detection Method of ZigBee Protocol in a Wireless Sensor Network |
title | A Randomness Detection Method of ZigBee Protocol in a Wireless Sensor Network |
title_full | A Randomness Detection Method of ZigBee Protocol in a Wireless Sensor Network |
title_fullStr | A Randomness Detection Method of ZigBee Protocol in a Wireless Sensor Network |
title_full_unstemmed | A Randomness Detection Method of ZigBee Protocol in a Wireless Sensor Network |
title_short | A Randomness Detection Method of ZigBee Protocol in a Wireless Sensor Network |
title_sort | randomness detection method of zigbee protocol in a wireless sensor network |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6263650/ https://www.ncbi.nlm.nih.gov/pubmed/30445740 http://dx.doi.org/10.3390/s18113962 |
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