BAN-trust: An attack-resilient malicious node detection scheme for body area networks

Wenjia Li, Xianshu Zhu
{"title":"BAN-trust: An attack-resilient malicious node detection scheme for body area networks","authors":"Wenjia Li, Xianshu Zhu","doi":"10.1109/ICCNC.2016.7440651","DOIUrl":null,"url":null,"abstract":"Body area networks (BAN) has recently emerged as an important enabling technology to support various telehealth applications. Because of its unique application domain, it is critical to ensure the secure and reliable gathering of patient's physiological signs. However, most of the existing security solutions for BANs focus on using encryption techniques to secure the data transmission or provide authentication. On the other hand, it is well understood that BANs are also extremely vulnerable to various malicious attacks, which have not attracted abundant research attention so far. In this paper, an attack-resilient malicious node detection scheme (BAN-Trust) is proposed for wireless body area networks that is able to detect and cope with malicious attacks in BANs. The effectiveness and efficiency of the proposed BAN-Trust scheme is validated through extensive experiments.","PeriodicalId":308458,"journal":{"name":"2016 International Conference on Computing, Networking and Communications (ICNC)","volume":"27 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2016-03-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"9","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2016 International Conference on Computing, Networking and Communications (ICNC)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICCNC.2016.7440651","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 9

Abstract

Body area networks (BAN) has recently emerged as an important enabling technology to support various telehealth applications. Because of its unique application domain, it is critical to ensure the secure and reliable gathering of patient's physiological signs. However, most of the existing security solutions for BANs focus on using encryption techniques to secure the data transmission or provide authentication. On the other hand, it is well understood that BANs are also extremely vulnerable to various malicious attacks, which have not attracted abundant research attention so far. In this paper, an attack-resilient malicious node detection scheme (BAN-Trust) is proposed for wireless body area networks that is able to detect and cope with malicious attacks in BANs. The effectiveness and efficiency of the proposed BAN-Trust scheme is validated through extensive experiments.
查看原文
分享 分享
微信好友 朋友圈 QQ好友 复制链接
本刊更多论文
BAN-trust:一种抗攻击的体域网络恶意节点检测方案
体域网络(BAN)最近成为支持各种远程医疗应用的重要使能技术。由于其独特的应用领域,确保患者生理体征的安全可靠采集至关重要。然而,现有的ban安全解决方案大多侧重于使用加密技术来保护数据传输或提供身份验证。另一方面,众所周知,ban也极易受到各种恶意攻击,迄今为止还没有引起足够的研究关注。本文提出了一种针对无线体域网络的抗攻击恶意节点检测方案(BAN-Trust),该方案能够检测和应对ban中的恶意攻击。通过大量实验验证了所提出的BAN-Trust方案的有效性和高效性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
求助全文
约1分钟内获得全文 去求助
来源期刊
自引率
0.00%
发文量
0
期刊最新文献
Public scene recognition using mobile phone sensors Mixed signal detection and carrier frequency estimation based on spectral coherent features A queue-length based distributed scheduling for CSMA-driven Wireless Mesh Networks GreenTCAM: A memory- and energy-efficient TCAM-based packet classification Hierarchical traffic engineering based on model predictive control
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
现在去查看 取消
×
提示
确定
0
微信
客服QQ
Book学术公众号 扫码关注我们
反馈
×
意见反馈
请填写您的意见或建议
请填写您的手机或邮箱
已复制链接
已复制链接
快去分享给好友吧!
我知道了
×
扫码分享
扫码分享
Book学术官方微信
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术
文献互助 智能选刊 最新文献 互助须知 联系我们:info@booksci.cn
Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。
Copyright © 2023 Book学术 All rights reserved.
ghs 京公网安备 11010802042870号 京ICP备2023020795号-1