TLS在审查规避中的使用

Sergey Frolov, Eric Wustrow
{"title":"TLS在审查规避中的使用","authors":"Sergey Frolov, Eric Wustrow","doi":"10.14722/ndss.2019.23511","DOIUrl":null,"url":null,"abstract":"TLS, the Transport Layer Security protocol, has quickly become the most popular protocol on the Internet, already used to load over 70% of web pages in Mozilla Firefox. Due to its ubiquity, TLS is also a popular protocol for censorship circumvention tools, including Tor and Signal, among others. However, the wide range of features supported in TLS makes it possible to distinguish implementations from one another by what set of cipher suites, elliptic curves, signature algorithms, and other extensions they support. Already, censors have used deep packet inspection (DPI) to identify and block popular circumvention tools based on the fingerprint of their TLS implementation. In response, many circumvention tools have attempted to mimic popular TLS implementations such as browsers, but this technique has several challenges. First, it is burdensome to keep up with the rapidly-changing browser TLS implementations, and know what fingerprints would be good candidates to mimic. Second, TLS implementations can be difficult to mimic correctly, as they offer many features that may not be supported by the relatively lightweight libraries used in typical circumvention tools. Finally, dependency changes and updates to the underlying libraries can silently impact what an application’s TLS fingerprint looks like, making it difficult for tool maintainers to keep up. In this paper, we collect and analyze real-world TLS traffic from over 11.8 billion TLS connections over 9 months to identify a wide range of TLS client implementations actually used on the Internet. We use our data to analyze TLS implementations of several popular censorship circumvention tools, including Lantern, Psiphon, Signal, Outline, TapDance, and Tor (Snowflake and meek pluggable transports). We find that the many of these tools use TLS configurations that are easily distinguishable from the real-world traffic they attempt to mimic, even when these tools have put effort into parroting popular TLS implementations. To address this problem, we have developed a library, uTLS, that enables tool maintainers to automatically mimic other popular TLS implementations. Using our real-world traffic dataset, we observe many popular TLS implementations we are able to correctly mimic with uTLS, and we describe ways our tool can more flexibly adapt to the dynamic TLS ecosystem with minimal manual effort.","PeriodicalId":20444,"journal":{"name":"Proceedings 2019 Network and Distributed System Security Symposium","volume":null,"pages":null},"PeriodicalIF":0.0000,"publicationDate":"2019-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"64","resultStr":"{\"title\":\"The use of TLS in Censorship Circumvention\",\"authors\":\"Sergey Frolov, Eric Wustrow\",\"doi\":\"10.14722/ndss.2019.23511\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"TLS, the Transport Layer Security protocol, has quickly become the most popular protocol on the Internet, already used to load over 70% of web pages in Mozilla Firefox. Due to its ubiquity, TLS is also a popular protocol for censorship circumvention tools, including Tor and Signal, among others. However, the wide range of features supported in TLS makes it possible to distinguish implementations from one another by what set of cipher suites, elliptic curves, signature algorithms, and other extensions they support. Already, censors have used deep packet inspection (DPI) to identify and block popular circumvention tools based on the fingerprint of their TLS implementation. In response, many circumvention tools have attempted to mimic popular TLS implementations such as browsers, but this technique has several challenges. First, it is burdensome to keep up with the rapidly-changing browser TLS implementations, and know what fingerprints would be good candidates to mimic. Second, TLS implementations can be difficult to mimic correctly, as they offer many features that may not be supported by the relatively lightweight libraries used in typical circumvention tools. Finally, dependency changes and updates to the underlying libraries can silently impact what an application’s TLS fingerprint looks like, making it difficult for tool maintainers to keep up. In this paper, we collect and analyze real-world TLS traffic from over 11.8 billion TLS connections over 9 months to identify a wide range of TLS client implementations actually used on the Internet. We use our data to analyze TLS implementations of several popular censorship circumvention tools, including Lantern, Psiphon, Signal, Outline, TapDance, and Tor (Snowflake and meek pluggable transports). We find that the many of these tools use TLS configurations that are easily distinguishable from the real-world traffic they attempt to mimic, even when these tools have put effort into parroting popular TLS implementations. To address this problem, we have developed a library, uTLS, that enables tool maintainers to automatically mimic other popular TLS implementations. Using our real-world traffic dataset, we observe many popular TLS implementations we are able to correctly mimic with uTLS, and we describe ways our tool can more flexibly adapt to the dynamic TLS ecosystem with minimal manual effort.\",\"PeriodicalId\":20444,\"journal\":{\"name\":\"Proceedings 2019 Network and Distributed System Security Symposium\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2019-01-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"64\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Proceedings 2019 Network and Distributed System Security Symposium\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.14722/ndss.2019.23511\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Proceedings 2019 Network and Distributed System Security Symposium","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.14722/ndss.2019.23511","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 64

摘要

TLS,即传输层安全协议,已经迅速成为互联网上最流行的协议,已经用于加载Mozilla Firefox中超过70%的网页。由于其无处不在,TLS也是审查规避工具的流行协议,包括Tor和Signal等。然而,TLS所支持的广泛特性使得通过它们所支持的密码套件、椭圆曲线、签名算法和其他扩展集来区分实现成为可能。审查者已经使用深度包检测(DPI)来识别和阻止基于其TLS实现指纹的流行翻墙工具。作为回应,许多翻墙工具试图模仿流行的TLS实现(如浏览器),但是这种技术有几个挑战。首先,要跟上快速变化的浏览器TLS实现,并知道哪些指纹是很好的模仿对象,这是一项繁重的工作。其次,TLS实现很难正确模拟,因为它们提供的许多特性可能不被典型规避工具中使用的相对轻量级库所支持。最后,对底层库的依赖项更改和更新可能会悄悄地影响应用程序的TLS指纹,使工具维护人员难以跟上。在本文中,我们在9个月的时间里收集和分析了118亿TLS连接的真实TLS流量,以确定在互联网上实际使用的广泛的TLS客户端实现。我们使用我们的数据来分析几种流行的审查规避工具的TLS实现,包括Lantern, Psiphon, Signal, Outline, TapDance和Tor (Snowflake和meek可插拔传输)。我们发现,这些工具中的许多都使用TLS配置,这些配置很容易与它们试图模仿的真实流量区分开来,即使这些工具已经努力模仿流行的TLS实现。为了解决这个问题,我们开发了一个库uTLS,它使工具维护者能够自动模拟其他流行的TLS实现。使用我们的真实世界流量数据集,我们观察了许多流行的TLS实现,我们能够用uTLS正确地模拟,并且我们描述了我们的工具可以更灵活地适应动态TLS生态系统的方法,只需最少的手工工作。
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
The use of TLS in Censorship Circumvention
TLS, the Transport Layer Security protocol, has quickly become the most popular protocol on the Internet, already used to load over 70% of web pages in Mozilla Firefox. Due to its ubiquity, TLS is also a popular protocol for censorship circumvention tools, including Tor and Signal, among others. However, the wide range of features supported in TLS makes it possible to distinguish implementations from one another by what set of cipher suites, elliptic curves, signature algorithms, and other extensions they support. Already, censors have used deep packet inspection (DPI) to identify and block popular circumvention tools based on the fingerprint of their TLS implementation. In response, many circumvention tools have attempted to mimic popular TLS implementations such as browsers, but this technique has several challenges. First, it is burdensome to keep up with the rapidly-changing browser TLS implementations, and know what fingerprints would be good candidates to mimic. Second, TLS implementations can be difficult to mimic correctly, as they offer many features that may not be supported by the relatively lightweight libraries used in typical circumvention tools. Finally, dependency changes and updates to the underlying libraries can silently impact what an application’s TLS fingerprint looks like, making it difficult for tool maintainers to keep up. In this paper, we collect and analyze real-world TLS traffic from over 11.8 billion TLS connections over 9 months to identify a wide range of TLS client implementations actually used on the Internet. We use our data to analyze TLS implementations of several popular censorship circumvention tools, including Lantern, Psiphon, Signal, Outline, TapDance, and Tor (Snowflake and meek pluggable transports). We find that the many of these tools use TLS configurations that are easily distinguishable from the real-world traffic they attempt to mimic, even when these tools have put effort into parroting popular TLS implementations. To address this problem, we have developed a library, uTLS, that enables tool maintainers to automatically mimic other popular TLS implementations. Using our real-world traffic dataset, we observe many popular TLS implementations we are able to correctly mimic with uTLS, and we describe ways our tool can more flexibly adapt to the dynamic TLS ecosystem with minimal manual effort.
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
Network and System Security: 17th International Conference, NSS 2023, Canterbury, UK, August 14–16, 2023, Proceedings Network and System Security: 16th International Conference, NSS 2022, Denarau Island, Fiji, December 9–12, 2022, Proceedings Network and System Security: 15th International Conference, NSS 2021, Tianjin, China, October 23, 2021, Proceedings Network and System Security: 14th International Conference, NSS 2020, Melbourne, VIC, Australia, November 25–27, 2020, Proceedings Neuro-Symbolic Execution: Augmenting Symbolic Execution with Neural Constraints
×
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