水下无线传感器网络轻量级多因素认证

Ahmed Al Guqhaiman, Oluwatobi Akanbi, Amer Aljaedi, C. E. Chow
{"title":"水下无线传感器网络轻量级多因素认证","authors":"Ahmed Al Guqhaiman, Oluwatobi Akanbi, Amer Aljaedi, C. E. Chow","doi":"10.1109/CSCI51800.2020.00039","DOIUrl":null,"url":null,"abstract":"Underwater Wireless Sensor Networks (UWSNs) are liable to malicious attacks due to limited bandwidth, limited power, high propagation delay, path loss, and variable speed. The major differences between UWSNs and Terrestrial Wireless Sensor Networks (TWSNs) necessitate a new mechanism to secure UWSNs. The existing Media Access Control (MAC) and routing protocols have addressed the network performance of UWSNs, but are vulnerable to several attacks. The secure MAC and routing protocols must exist to detect Sybil, Blackhole, Wormhole, Hello Flooding, Acknowledgment Spoofing, Selective Forwarding, Sinkhole, and Exhaustion attacks. These attacks can disrupt or disable the network connection. Hence, these attacks can degrade the network performance and total loss can be catastrophic in some applications, like monitoring oil/gas spills. Several researchers have studied the security of UWSNs, but most of the works detect malicious attacks solely based on a certain predefined threshold. It is not optimal to detect malicious attacks after the threshold value is met. In this paper, we propose a multi-factor authentication model that is based on zero-knowledge proof to detect malicious activities and secure UWSNs from several attacks.","PeriodicalId":336929,"journal":{"name":"2020 International Conference on Computational Science and Computational Intelligence (CSCI)","volume":"85 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2020-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"2","resultStr":"{\"title\":\"Lightweight Multi-factor Authentication for Underwater Wireless Sensor Networks\",\"authors\":\"Ahmed Al Guqhaiman, Oluwatobi Akanbi, Amer Aljaedi, C. E. Chow\",\"doi\":\"10.1109/CSCI51800.2020.00039\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Underwater Wireless Sensor Networks (UWSNs) are liable to malicious attacks due to limited bandwidth, limited power, high propagation delay, path loss, and variable speed. The major differences between UWSNs and Terrestrial Wireless Sensor Networks (TWSNs) necessitate a new mechanism to secure UWSNs. The existing Media Access Control (MAC) and routing protocols have addressed the network performance of UWSNs, but are vulnerable to several attacks. The secure MAC and routing protocols must exist to detect Sybil, Blackhole, Wormhole, Hello Flooding, Acknowledgment Spoofing, Selective Forwarding, Sinkhole, and Exhaustion attacks. These attacks can disrupt or disable the network connection. Hence, these attacks can degrade the network performance and total loss can be catastrophic in some applications, like monitoring oil/gas spills. Several researchers have studied the security of UWSNs, but most of the works detect malicious attacks solely based on a certain predefined threshold. It is not optimal to detect malicious attacks after the threshold value is met. In this paper, we propose a multi-factor authentication model that is based on zero-knowledge proof to detect malicious activities and secure UWSNs from several attacks.\",\"PeriodicalId\":336929,\"journal\":{\"name\":\"2020 International Conference on Computational Science and Computational Intelligence (CSCI)\",\"volume\":\"85 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2020-12-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"2\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2020 International Conference on Computational Science and Computational Intelligence (CSCI)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/CSCI51800.2020.00039\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2020 International Conference on Computational Science and Computational Intelligence (CSCI)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/CSCI51800.2020.00039","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 2

摘要

水下无线传感器网络(UWSNs)由于带宽有限、功率有限、传播延迟大、路径丢失和速度可变等特点,容易受到恶意攻击。uwsn与地面无线传感器网络(TWSNs)之间的主要区别需要一种新的机制来保护uwsn。现有的媒体访问控制(MAC)和路由协议解决了uwsn的网络性能问题,但容易受到多种攻击。必须存在安全的MAC和路由协议才能检测Sybil、黑洞、虫洞、Hello flood、确认欺骗、选择性转发、天坑和耗尽攻击。这些攻击可以破坏或禁用网络连接。因此,这些攻击会降低网络性能,在某些应用程序(如监测石油/天然气泄漏)中,总损失可能是灾难性的。一些研究人员对UWSNs的安全性进行了研究,但大多数工作仅仅基于某个预定义的阈值来检测恶意攻击。在达到阈值后才检测恶意攻击并不是最优的。在本文中,我们提出了一种基于零知识证明的多因素认证模型来检测恶意活动并保护uwsn免受多种攻击。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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
Lightweight Multi-factor Authentication for Underwater Wireless Sensor Networks
Underwater Wireless Sensor Networks (UWSNs) are liable to malicious attacks due to limited bandwidth, limited power, high propagation delay, path loss, and variable speed. The major differences between UWSNs and Terrestrial Wireless Sensor Networks (TWSNs) necessitate a new mechanism to secure UWSNs. The existing Media Access Control (MAC) and routing protocols have addressed the network performance of UWSNs, but are vulnerable to several attacks. The secure MAC and routing protocols must exist to detect Sybil, Blackhole, Wormhole, Hello Flooding, Acknowledgment Spoofing, Selective Forwarding, Sinkhole, and Exhaustion attacks. These attacks can disrupt or disable the network connection. Hence, these attacks can degrade the network performance and total loss can be catastrophic in some applications, like monitoring oil/gas spills. Several researchers have studied the security of UWSNs, but most of the works detect malicious attacks solely based on a certain predefined threshold. It is not optimal to detect malicious attacks after the threshold value is met. In this paper, we propose a multi-factor authentication model that is based on zero-knowledge proof to detect malicious activities and secure UWSNs from several attacks.
求助全文
通过发布文献求助,成功后即可免费获取论文全文。 去求助
来源期刊
自引率
0.00%
发文量
0
期刊最新文献
First Success of Cancer Gene Data Analysis of 169 Microarrays for Medical Diagnosis Artificial Intelligence in Computerized Adaptive Testing Evidence for Monitoring the User and Computing the User’s trust Transfer of Hierarchical Reinforcement Learning Structures for Robotic Manipulation Tasks An open-source application built with R programming language for clinical laboratories to innovate process of excellence and overcome the uncertain outlook during the global healthcare crisis
×
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