Distributed Reputation System for Tracking Applications in Sensor Networks

T. Roosta, M. Meingast, S. Sastry
{"title":"Distributed Reputation System for Tracking Applications in Sensor Networks","authors":"T. Roosta, M. Meingast, S. Sastry","doi":"10.1109/mobiq.2006.340449","DOIUrl":null,"url":null,"abstract":"Ad-hoc sensor networks are becoming more common, yet security of these networks is still an issue. Node misbehavior due to malicious attacks can impair the overall functioning of the system. Existing approaches mainly rely on cryptography to ensure data authentication and integrity. These approaches only address part of the problem of security in sensor networks. However, cryptography is not sufficient to prevent the attacks in which some of the nodes are overtaken and compromised by a malicious user. Recently, the use of reputation systems has shown positive results as a self-policing mechanism in ad-hoc networks. This scheme can aid in decreasing vulnerabilities which are not solved by cryptography. We look at how a distributed reputation scheme can benefit the object tracking application in sensor networks. Tracking multiple objects is one of the most important applications of the sensor network. In our setup, nodes detect misbehavior locally from observations, and assign a reputation to each of their neighbors. These reputations are used to weight node readings appropriately when performing object tracking. Over time, data from malicious nodes will not be included in the track formation process. We evaluate the reputation system experimentally and demonstrate how it improves object tracking in the presence of malicious nodes","PeriodicalId":440604,"journal":{"name":"2006 Third Annual International Conference on Mobile and Ubiquitous Systems: Networking & Services","volume":"347 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2006 Third Annual International Conference on Mobile and Ubiquitous Systems: Networking & Services","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/mobiq.2006.340449","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 1

Abstract

Ad-hoc sensor networks are becoming more common, yet security of these networks is still an issue. Node misbehavior due to malicious attacks can impair the overall functioning of the system. Existing approaches mainly rely on cryptography to ensure data authentication and integrity. These approaches only address part of the problem of security in sensor networks. However, cryptography is not sufficient to prevent the attacks in which some of the nodes are overtaken and compromised by a malicious user. Recently, the use of reputation systems has shown positive results as a self-policing mechanism in ad-hoc networks. This scheme can aid in decreasing vulnerabilities which are not solved by cryptography. We look at how a distributed reputation scheme can benefit the object tracking application in sensor networks. Tracking multiple objects is one of the most important applications of the sensor network. In our setup, nodes detect misbehavior locally from observations, and assign a reputation to each of their neighbors. These reputations are used to weight node readings appropriately when performing object tracking. Over time, data from malicious nodes will not be included in the track formation process. We evaluate the reputation system experimentally and demonstrate how it improves object tracking in the presence of malicious nodes
分布式信誉系统在传感器网络中的跟踪应用
Ad-hoc传感器网络正变得越来越普遍,但这些网络的安全性仍然是一个问题。由于恶意攻击导致的节点行为异常会损害系统的整体功能。现有的方法主要依靠密码学来确保数据的身份验证和完整性。这些方法只解决了传感器网络安全问题的一部分。然而,加密不足以防止某些节点被恶意用户超越和破坏的攻击。最近,声誉系统作为自组织网络中的自我监管机制的使用已经显示出积极的结果。该方案可以减少加密技术无法解决的漏洞。我们将研究分布式信誉方案如何使传感器网络中的目标跟踪应用受益。多目标跟踪是传感器网络最重要的应用之一。在我们的设置中,节点从观察中检测本地的不当行为,并为每个邻居分配声誉。这些声誉用于在执行对象跟踪时适当地加权节点读数。随着时间的推移,来自恶意节点的数据将不包含在航迹形成过程中。我们通过实验评估了信誉系统,并演示了它如何在存在恶意节点的情况下改善目标跟踪
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 求助全文
来源期刊
自引率
0.00%
发文量
0
×
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
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
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 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术官方微信