Improving IP Prefix Hijacking Detection by Tracing Hijack Fingerprints and Verifying Them through RIR Databases

Hussain Alshamrani, B. Ghita
{"title":"Improving IP Prefix Hijacking Detection by Tracing Hijack Fingerprints and Verifying Them through RIR Databases","authors":"Hussain Alshamrani, B. Ghita","doi":"10.5220/0005934200570063","DOIUrl":null,"url":null,"abstract":"In spite of significant on-going research, the Border Gateway Protocol (BGP) still encompasses conceptual vulnerability issues regarding impersonating the ownership of IP prefixes for ASes (Autonomous Systems). In this context, a number of research studies focused on securing BGP through historical-based and statistical-based behavioural models. This paper improves the earlier IP prefix hijack detection method presented in (Alshamrani et al. 2015) by identifying false positives showing up due to the organisations that may use multiple ASNs (Autonomous System Numbers) to advertise their routes. To solve this issue, we link a Verification Database to the previously proposed detection method to improve the accuracy. The method extracts the organisation names (unique code) and associated ASNs from different ASN delegators and RIRs (Regional Internet Registries), more specifically the RIPE (Reseaux IP Europeans) dump database (John Stamatakis 2014) in order to evaluate the method. Since the organisation name is not available in the BGP updates, the data are extracted and processed to produce a structured database (Verification DB). The algorithm excludes false positive IP prefix hijack detection events in the SFL (Suspicious Findings List) introduced in (Alshamrani et al. 2015). Finally, the algorithm is validated using the 2008 YouTube Pakistan hijack event and the Con-Edison hijack (2006); the analysis demonstrates that the improved algorithm qualitatively increases the accuracy of detecting the IP prefix hijacks, specifically reducing the false positives.","PeriodicalId":172337,"journal":{"name":"International Conference on Data Communication Networking","volume":"70 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2016-07-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"International Conference on Data Communication Networking","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.5220/0005934200570063","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

In spite of significant on-going research, the Border Gateway Protocol (BGP) still encompasses conceptual vulnerability issues regarding impersonating the ownership of IP prefixes for ASes (Autonomous Systems). In this context, a number of research studies focused on securing BGP through historical-based and statistical-based behavioural models. This paper improves the earlier IP prefix hijack detection method presented in (Alshamrani et al. 2015) by identifying false positives showing up due to the organisations that may use multiple ASNs (Autonomous System Numbers) to advertise their routes. To solve this issue, we link a Verification Database to the previously proposed detection method to improve the accuracy. The method extracts the organisation names (unique code) and associated ASNs from different ASN delegators and RIRs (Regional Internet Registries), more specifically the RIPE (Reseaux IP Europeans) dump database (John Stamatakis 2014) in order to evaluate the method. Since the organisation name is not available in the BGP updates, the data are extracted and processed to produce a structured database (Verification DB). The algorithm excludes false positive IP prefix hijack detection events in the SFL (Suspicious Findings List) introduced in (Alshamrani et al. 2015). Finally, the algorithm is validated using the 2008 YouTube Pakistan hijack event and the Con-Edison hijack (2006); the analysis demonstrates that the improved algorithm qualitatively increases the accuracy of detecting the IP prefix hijacks, specifically reducing the false positives.
利用RIR数据库跟踪并验证劫持指纹,改进IP前缀劫持检测
尽管有大量正在进行的研究,边界网关协议(BGP)仍然包含关于模拟as(自治系统)的IP前缀所有权的概念性漏洞问题。在此背景下,许多研究集中于通过基于历史和基于统计的行为模型来保护BGP。本文改进了(Alshamrani et al. 2015)中提出的早期IP前缀劫持检测方法,通过识别由于可能使用多个asn(自治系统号)来发布其路由的组织而出现的假阳性。为了解决这个问题,我们将一个验证数据库与之前提出的检测方法联系起来,以提高准确性。该方法从不同的ASN代理和RIRs(区域互联网注册管理机构)中提取组织名称(唯一代码)和相关的ASN,更具体地说,是RIPE (Reseaux IP europe)转储数据库(John Stamatakis 2014),以便评估该方法。由于组织名称在BGP更新中不可用,因此提取并处理数据以生成结构化数据库(Verification DB)。该算法排除了(Alshamrani et al. 2015)中引入的SFL(可疑发现列表)中的假阳性IP前缀劫持检测事件。最后,使用2008年YouTube巴基斯坦劫持事件和Con-Edison劫持事件(2006年)验证了该算法;分析表明,改进后的算法定性地提高了IP前缀劫持检测的准确性,特别是减少了误报。
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:604180095
Book学术官方微信