1000 days of UDP amplification DDoS attacks

Daniel R. Thomas, R. Clayton, A. Beresford
{"title":"1000 days of UDP amplification DDoS attacks","authors":"Daniel R. Thomas, R. Clayton, A. Beresford","doi":"10.1109/ECRIME.2017.7945057","DOIUrl":null,"url":null,"abstract":"Distributed Denial of Service (DDoS) attacks employing reflected UDP amplification are regularly used to disrupt networks and systems. The amplification allows one rented server to generate significant volumes of data, while the reflection hides the identity of the attacker. Consequently this is an attractive, low risk, strategy for criminals bent on vandalism and extortion. To measure the uptake of this strategy we analyse the results of running a network of honeypot UDP reflectors (median size 65 nodes) from July 2014 onwards. We explore the life cycle of attacks that use our reflectors, from the scanning phase used to detect our honeypot machines, through to their use in attacks. We see a median of 1 450 malicious scanners per day across all UDP protocols, and have recorded details of 5.18 million subsequent attacks involving in excess of 3.31 trillion packets. Using a capture-recapture statistical technique, we estimate that our reflectors can see between 85.1% and 96.6% of UDP reflection attacks over our measurement period.","PeriodicalId":116819,"journal":{"name":"2017 APWG Symposium on Electronic Crime Research (eCrime)","volume":"69 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2017-04-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"44","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2017 APWG Symposium on Electronic Crime Research (eCrime)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ECRIME.2017.7945057","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 44

Abstract

Distributed Denial of Service (DDoS) attacks employing reflected UDP amplification are regularly used to disrupt networks and systems. The amplification allows one rented server to generate significant volumes of data, while the reflection hides the identity of the attacker. Consequently this is an attractive, low risk, strategy for criminals bent on vandalism and extortion. To measure the uptake of this strategy we analyse the results of running a network of honeypot UDP reflectors (median size 65 nodes) from July 2014 onwards. We explore the life cycle of attacks that use our reflectors, from the scanning phase used to detect our honeypot machines, through to their use in attacks. We see a median of 1 450 malicious scanners per day across all UDP protocols, and have recorded details of 5.18 million subsequent attacks involving in excess of 3.31 trillion packets. Using a capture-recapture statistical technique, we estimate that our reflectors can see between 85.1% and 96.6% of UDP reflection attacks over our measurement period.
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
1000天UDP放大DDoS攻击
分布式拒绝服务(DDoS)攻击利用反射UDP放大,经常被用来破坏网络和系统。这种放大允许租用的服务器生成大量数据,而反射隐藏了攻击者的身份。因此,这是一个有吸引力的,低风险的策略,罪犯一心想破坏和勒索。为了衡量这一策略的采用情况,我们分析了从2014年7月起运行蜜罐UDP反射器网络(中位数大小为65个节点)的结果。我们探索使用反射器的攻击的生命周期,从用于检测我们的蜜罐机器的扫描阶段,到它们在攻击中的使用。我们每天在所有UDP协议中看到1450个恶意扫描仪,并记录了518万次后续攻击的细节,涉及超过3.31万亿数据包。使用捕获-再捕获统计技术,我们估计在我们的测量期间,反射器可以看到85.1%到96.6%的UDP反射攻击。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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
Configuring Zeus: A case study of online crime target selection and knowledge transmission 1000 days of UDP amplification DDoS attacks “Hello. This is the IRS calling.”: A case study on scams, extortion, impersonation, and phone spoofing Classifying phishing URLs using recurrent neural networks Blockchain explorer: An analytical process and investigation environment for bitcoin
×
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