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Secrecy Capacity of a Class of Erasure Wiretap Channels in WBAN

In wireless body area networks (WBANs), the secrecy of personal health information is vulnerable to attacks due to the openness of wireless communication. In this paper, we study the security problem of WBANs, where there exists an attacker or eavesdropper who is able to observe data from part of se...

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Autores principales: Wang, Bin, Deng, Jun, Sun, Yanjing, Guo, Wangmei, Feng, Guiguo
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2018
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6308839/
https://www.ncbi.nlm.nih.gov/pubmed/30486250
http://dx.doi.org/10.3390/s18124135
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author Wang, Bin
Deng, Jun
Sun, Yanjing
Guo, Wangmei
Feng, Guiguo
author_facet Wang, Bin
Deng, Jun
Sun, Yanjing
Guo, Wangmei
Feng, Guiguo
author_sort Wang, Bin
collection PubMed
description In wireless body area networks (WBANs), the secrecy of personal health information is vulnerable to attacks due to the openness of wireless communication. In this paper, we study the security problem of WBANs, where there exists an attacker or eavesdropper who is able to observe data from part of sensors. The legitimate communication within the WBAN is modeled as a discrete memoryless channel (DMC) by establishing the secrecy capacity of a class of finite state Markov erasure wiretap channels. Meanwhile, the tapping of the eavesdropper is modeled as a finite-state Markov erasure channel (FSMEC). A pair of encoder and decoder are devised to make the eavesdropper have no knowledge of the source message, and enable the receiver to recover the source message with a small decoding error. It is proved that the secrecy capacity can be achieved by migrating the coding scheme for wiretap channel II with the noisy main channel. This method provides a new idea solving the secure problem of the internet of things (IoT).
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spelling pubmed-63088392019-01-04 Secrecy Capacity of a Class of Erasure Wiretap Channels in WBAN Wang, Bin Deng, Jun Sun, Yanjing Guo, Wangmei Feng, Guiguo Sensors (Basel) Article In wireless body area networks (WBANs), the secrecy of personal health information is vulnerable to attacks due to the openness of wireless communication. In this paper, we study the security problem of WBANs, where there exists an attacker or eavesdropper who is able to observe data from part of sensors. The legitimate communication within the WBAN is modeled as a discrete memoryless channel (DMC) by establishing the secrecy capacity of a class of finite state Markov erasure wiretap channels. Meanwhile, the tapping of the eavesdropper is modeled as a finite-state Markov erasure channel (FSMEC). A pair of encoder and decoder are devised to make the eavesdropper have no knowledge of the source message, and enable the receiver to recover the source message with a small decoding error. It is proved that the secrecy capacity can be achieved by migrating the coding scheme for wiretap channel II with the noisy main channel. This method provides a new idea solving the secure problem of the internet of things (IoT). MDPI 2018-11-26 /pmc/articles/PMC6308839/ /pubmed/30486250 http://dx.doi.org/10.3390/s18124135 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
Wang, Bin
Deng, Jun
Sun, Yanjing
Guo, Wangmei
Feng, Guiguo
Secrecy Capacity of a Class of Erasure Wiretap Channels in WBAN
title Secrecy Capacity of a Class of Erasure Wiretap Channels in WBAN
title_full Secrecy Capacity of a Class of Erasure Wiretap Channels in WBAN
title_fullStr Secrecy Capacity of a Class of Erasure Wiretap Channels in WBAN
title_full_unstemmed Secrecy Capacity of a Class of Erasure Wiretap Channels in WBAN
title_short Secrecy Capacity of a Class of Erasure Wiretap Channels in WBAN
title_sort secrecy capacity of a class of erasure wiretap channels in wban
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6308839/
https://www.ncbi.nlm.nih.gov/pubmed/30486250
http://dx.doi.org/10.3390/s18124135
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