野外VPN生态系统的特征

Aniss Maghsoudlou, Lukas Vermeulen, Ingmar Poese, Oliver Gasser
{"title":"野外VPN生态系统的特征","authors":"Aniss Maghsoudlou, Lukas Vermeulen, Ingmar Poese, Oliver Gasser","doi":"10.48550/arXiv.2302.06566","DOIUrl":null,"url":null,"abstract":"With the shift to working remotely after the COVID-19 pandemic, the use of Virtual Private Networks (VPNs) around the world has nearly doubled. Therefore, measuring the traffic and security aspects of the VPN ecosystem is more important now than ever. It is, however, challenging to detect and characterize VPN traffic since some VPN protocols use the same port number as web traffic and port-based traffic classification will not help. VPN users are also concerned about the vulnerabilities of their VPN connections due to privacy issues. In this paper, we aim at detecting and characterizing VPN servers in the wild, which facilitates detecting the VPN traffic. To this end, we perform Internet-wide active measurements to find VPN servers in the wild, and characterize them based on their vulnerabilities, certificates, locations, and fingerprinting. We find 9.8M VPN servers distributed around the world using OpenVPN, SSTP, PPTP, and IPsec, and analyze their vulnerability. We find SSTP to be the most vulnerable protocol with more than 90% of detected servers being vulnerable to TLS downgrade attacks. Of all the servers that respond to our VPN probes, 2% also respond to HTTP probes and therefore are classified as Web servers. We apply our list of VPN servers to the traffic from a large European ISP and observe that 2.6% of all traffic is related to these VPN servers.","PeriodicalId":103587,"journal":{"name":"Passive and Active Network Measurement Conference","volume":"18 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2023-02-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":"{\"title\":\"Characterizing the VPN Ecosystem in the Wild\",\"authors\":\"Aniss Maghsoudlou, Lukas Vermeulen, Ingmar Poese, Oliver Gasser\",\"doi\":\"10.48550/arXiv.2302.06566\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"With the shift to working remotely after the COVID-19 pandemic, the use of Virtual Private Networks (VPNs) around the world has nearly doubled. Therefore, measuring the traffic and security aspects of the VPN ecosystem is more important now than ever. It is, however, challenging to detect and characterize VPN traffic since some VPN protocols use the same port number as web traffic and port-based traffic classification will not help. VPN users are also concerned about the vulnerabilities of their VPN connections due to privacy issues. In this paper, we aim at detecting and characterizing VPN servers in the wild, which facilitates detecting the VPN traffic. To this end, we perform Internet-wide active measurements to find VPN servers in the wild, and characterize them based on their vulnerabilities, certificates, locations, and fingerprinting. We find 9.8M VPN servers distributed around the world using OpenVPN, SSTP, PPTP, and IPsec, and analyze their vulnerability. We find SSTP to be the most vulnerable protocol with more than 90% of detected servers being vulnerable to TLS downgrade attacks. Of all the servers that respond to our VPN probes, 2% also respond to HTTP probes and therefore are classified as Web servers. We apply our list of VPN servers to the traffic from a large European ISP and observe that 2.6% of all traffic is related to these VPN servers.\",\"PeriodicalId\":103587,\"journal\":{\"name\":\"Passive and Active Network Measurement Conference\",\"volume\":\"18 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2023-02-13\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"1\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Passive and Active Network Measurement Conference\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.48550/arXiv.2302.06566\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Passive and Active Network Measurement Conference","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.48550/arXiv.2302.06566","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 1

摘要

随着COVID-19大流行后人们转向远程工作,全球虚拟专用网络(vpn)的使用量几乎翻了一番。因此,衡量VPN生态系统的流量和安全方面比以往任何时候都更加重要。然而,检测和描述VPN流量是具有挑战性的,因为一些VPN协议使用与web流量相同的端口号,基于端口的流量分类将没有帮助。由于隐私问题,VPN用户也担心VPN连接的漏洞。在本文中,我们的目的是在野外检测和表征VPN服务器,以便于检测VPN流量。为此,我们执行互联网范围内的主动测量,以在野外找到VPN服务器,并根据它们的漏洞、证书、位置和指纹特征来描述它们。我们发现了分布在世界各地的980万台使用OpenVPN、SSTP、PPTP和IPsec的VPN服务器,并分析了它们的漏洞。我们发现SSTP是最脆弱的协议,超过90%的检测到的服务器容易受到TLS降级攻击。在所有响应我们的VPN探测的服务器中,2%也响应HTTP探测,因此被归类为Web服务器。我们将VPN服务器列表应用于来自大型欧洲ISP的流量,并观察到所有流量的2.6%与这些VPN服务器有关。
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
Characterizing the VPN Ecosystem in the Wild
With the shift to working remotely after the COVID-19 pandemic, the use of Virtual Private Networks (VPNs) around the world has nearly doubled. Therefore, measuring the traffic and security aspects of the VPN ecosystem is more important now than ever. It is, however, challenging to detect and characterize VPN traffic since some VPN protocols use the same port number as web traffic and port-based traffic classification will not help. VPN users are also concerned about the vulnerabilities of their VPN connections due to privacy issues. In this paper, we aim at detecting and characterizing VPN servers in the wild, which facilitates detecting the VPN traffic. To this end, we perform Internet-wide active measurements to find VPN servers in the wild, and characterize them based on their vulnerabilities, certificates, locations, and fingerprinting. We find 9.8M VPN servers distributed around the world using OpenVPN, SSTP, PPTP, and IPsec, and analyze their vulnerability. We find SSTP to be the most vulnerable protocol with more than 90% of detected servers being vulnerable to TLS downgrade attacks. Of all the servers that respond to our VPN probes, 2% also respond to HTTP probes and therefore are classified as Web servers. We apply our list of VPN servers to the traffic from a large European ISP and observe that 2.6% of all traffic is related to these VPN servers.
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
WHOIS Right? An Analysis of WHOIS and RDAP Consistency SunBlock: Cloudless Protection for IoT Systems Data Augmentation for Traffic Classification How Ready Is DNS for an IPv6-Only World? Characterizing the VPN Ecosystem in the Wild
×
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