poster

Rosetta: Enabling Robust TLS Encrypted Traffic Classification in Diverse Network Environments with TCP-Aware Traffic Augmentation

Authors:

Kun Sun,

Qi Li,

Licheng Shen,

Menghao ZhangAuthors Info & Claims

ACM TURC '23: Proceedings of the ACM Turing Award Celebration Conference - China 2023

Pages 131 - 132

https://doi.org/10.1145/3603165.3607437

Published: 25 September 2023 Publication History

Get Access

Abstract

As the majority of Internet traffic is encrypted by the Transport Layer Security (TLS) protocol, recent advances leverage Deep Learning (DL) models to conduct encrypted traffic classification. We propose Rosetta to enable robust TLS encrypted traffic classification for existing DL models. It leverages TCP-aware traffic augmentation mechanisms and self-supervised learning to understand implicit TCP semantics, and hence extracts robust features of TLS flows. Extensive experiments show that Rosetta can significantly improve the classification performance of existing DL models on TLS traffic in diverse network environments.

References

[1]

Jiahao Cao, Zijie Yang, Kun Sun, Qi Li, Mingwei Xu, and Peiyi Han. [n. d.]. Fingerprinting { SDN} applications via encrypted control traffic. In RAID 2019.

Google Scholar

[2]

Chang Liu, Longtao He, Gang Xiong, Zigang Cao, and Zhen Li. 2019. Fs-net: A flow sequence network for encrypted traffic classification. In IEEE INFOCOM 2019-IEEE Conference On Computer Communications. IEEE, 1171–1179.

Digital Library

Google Scholar

[3]

Meng Shen, Yiting Liu, Liehuang Zhu, Xiaojiang Du, and Jiankun Hu. 2020. Fine-grained webpage fingerprinting using only packet length information of encrypted traffic. IEEE Transactions on Information Forensics and Security 16 (2020), 2046–2059.

Crossref

Google Scholar

[4]

Payap Sirinam, Mohsen Imani, Marc Juarez, and Matthew Wright. [n. d.]. Deep fingerprinting: Undermining website fingerprinting defenses with deep learning. In CCS 18.

Google Scholar

[5]

Ashish Vaswani, Noam Shazeer, Niki Parmar, Jakob Uszkoreit, Llion Jones, Aidan N Gomez, Łukasz Kaiser, and Illia Polosukhin. 2017. Attention is all you need. Advances in neural information processing systems 30 (2017).

Google Scholar

Cited By

View all

Chen YHou BWu BHu H(2025)CD-Net: Robust mobile traffic classification against apps updatingComputers & Security10.1016/j.cose.2024.104214150(104214)Online publication date: Mar-2025
https://doi.org/10.1016/j.cose.2024.104214
Sharma ALashkari A(2025)A survey on encrypted network traffic: A comprehensive survey of identification/classification techniques, challenges, and future directionsComputer Networks10.1016/j.comnet.2024.110984257(110984)Online publication date: Feb-2025
https://doi.org/10.1016/j.comnet.2024.110984
Suo YXue JGuo WDu WHan WXu C(2025)Certificate-Based Transport Layer Security Encrypted Malicious Traffic Detection in Real-Time Network EnvironmentsAlgorithms and Architectures for Parallel Processing10.1007/978-981-96-1525-4_20(341-350)Online publication date: 17-Feb-2025
https://doi.org/10.1007/978-981-96-1525-4_20
Show More Cited By

Recommendations

Observing real Multipath TCP traffic

We analyse a Multipath TCP dataset collected from multipath-tcp.org consecutively in 5 months.Multipath TCP correctly passes through a wide range of Internet paths.Current implementations of Multipath TCP try to utilise additional paths as quickly as ...
Encrypted TLS Traffic Classification on Cloud Platforms
Nowadays, encryption technology has been widely used to protect user privacy. With the explosive growth of mobile Internet, encrypted TLS traffic rises sharply and occupies a great share of current Internet traffic. In reality, the classification of ...
Achieving bounded fairness for multicast and TCP traffic in the Internet

There is an urgent need for effective multicast congestion control algorithms which enable reasonably fair share of network resources between multicast and unicast TCP traffic under the current Internet infrastructure. In this paper, we propose a ...

Comments

Information & Contributors

Information

Published In

ACM TURC '23: Proceedings of the ACM Turing Award Celebration Conference - China 2023

July 2023

173 pages

ISBN:9798400702334

DOI:10.1145/3603165

Permission to make digital or hard copies of part or all of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for third-party components of this work must be honored. For all other uses, contact the Owner/Author.

Publisher

Association for Computing Machinery

New York, NY, United States

Publication History

Published: 25 September 2023

Check for updates

Qualifiers

Poster
Research
Refereed limited

Conference

ACM TURC '23

ACM TURC '23: ACM Turing Award Celebration Conference 2023

July 28 - 30, 2023

Wuhan, China

Contributors

Other Metrics

View Article Metrics

Bibliometrics & Citations

Bibliometrics

Article Metrics

17
Total Citations
View Citations
393
Total Downloads

Downloads (Last 12 months)250
Downloads (Last 6 weeks)18

Reflects downloads up to 02 Mar 2025

Other Metrics

View Author Metrics

Citations

Cited By

View all

Chen YHou BWu BHu H(2025)CD-Net: Robust mobile traffic classification against apps updatingComputers & Security10.1016/j.cose.2024.104214150(104214)Online publication date: Mar-2025
https://doi.org/10.1016/j.cose.2024.104214
Sharma ALashkari A(2025)A survey on encrypted network traffic: A comprehensive survey of identification/classification techniques, challenges, and future directionsComputer Networks10.1016/j.comnet.2024.110984257(110984)Online publication date: Feb-2025
https://doi.org/10.1016/j.comnet.2024.110984
Suo YXue JGuo WDu WHan WXu C(2025)Certificate-Based Transport Layer Security Encrypted Malicious Traffic Detection in Real-Time Network EnvironmentsAlgorithms and Architectures for Parallel Processing10.1007/978-981-96-1525-4_20(341-350)Online publication date: 17-Feb-2025
https://doi.org/10.1007/978-981-96-1525-4_20
Liu TMa XLiu LLiu XZhao YHu NGhafoor K(2024)LAMBERT: Leveraging Attention Mechanisms to Improve the BERT Fine-Tuning Model for Encrypted Traffic ClassificationMathematics10.3390/math1211162412:11(1624)Online publication date: 22-May-2024
https://doi.org/10.3390/math12111624
Zhou JFu WHu WSun ZHe TZhang Z(2024)Challenges and Advances in Analyzing TLS 1.3-Encrypted Traffic: A Comprehensive SurveyElectronics10.3390/electronics1320400013:20(4000)Online publication date: 11-Oct-2024
https://doi.org/10.3390/electronics13204000
Jansen RWails RJohnson AAyday EVaidya J(2024)Repositioning Real-World Website Fingerprinting on TorProceedings of the 23rd Workshop on Privacy in the Electronic Society10.1145/3689943.3695047(124-140)Online publication date: 20-Nov-2024
https://dl.acm.org/doi/10.1145/3689943.3695047
Cebere BRossow C(2024)Understanding Web Fingerprinting with a Protocol-Centric ApproachProceedings of the 27th International Symposium on Research in Attacks, Intrusions and Defenses10.1145/3678890.3678910(17-34)Online publication date: 30-Sep-2024
https://dl.acm.org/doi/10.1145/3678890.3678910
Wang CYin JLi ZXu HZhang ZLiu QChua TNgo CKa-Wei Lee RKumar RLauw H(2024)Identifying VPN Servers through Graph-Represented BehaviorsProceedings of the ACM Web Conference 202410.1145/3589334.3645552(1790-1799)Online publication date: 13-May-2024
https://dl.acm.org/doi/10.1145/3589334.3645552
Han XCui SQin JLiu SJiang BDong CLu ZLiu BChua TNgo CKa-Wei Lee RKumar RLauw H(2024)ContraMTD: An Unsupervised Malicious Network Traffic Detection Method based on Contrastive LearningProceedings of the ACM Web Conference 202410.1145/3589334.3645479(1680-1689)Online publication date: 13-May-2024
https://dl.acm.org/doi/10.1145/3589334.3645479
Li JLin ZQu JWu SZhou HLiu YMa XWang TLuo XGuan X(2024)Robust App Fingerprinting Over the AirIEEE/ACM Transactions on Networking10.1109/TNET.2024.344862132:6(5065-5080)Online publication date: Dec-2024
https://doi.org/10.1109/TNET.2024.3448621
Show More Cited By

View Options

Login options

Check if you have access through your login credentials or your institution to get full access on this article.

Full Access

Get this Publication

View options

PDF

View or Download as a PDF file.

PDF

eReader

View online with eReader.

eReader

HTML Format

View this article in HTML Format.

HTML Format

Abstract

References

Cited By

Recommendations

Observing real Multipath TCP traffic

Encrypted TLS Traffic Classification on Cloud Platforms

Achieving bounded fairness for multicast and TCP traffic in the Internet

Comments

Information

Published In

Publisher

Publication History

Check for updates

Qualifiers

Conference

Contributors

Other Metrics

Bibliometrics

Article Metrics

Other Metrics

Citations

Cited By

Login options

Full Access

View options

PDF

eReader

HTML Format

Share

Share this Publication link

Share on social media

Affiliations