Is Encrypted ClientHello a Challenge for Traffic Classification?

Although the widely-used Transport Layer Security (TLS) protocol hides application data, an unencrypted part of the TLS handshake, specifically the server name indication (SNI), is a backdoor for encrypted traffic classification frameworks. The recently developed Encrypted ClientHello (ECH) amendmen...

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Main Authors: Danil Shamsimukhametov, Anton Kurapov, Mikhail Liubogoshchev, Evgeny Khorov
Format: Article
Language:English
Published: IEEE 2022-01-01
Series:IEEE Access
Subjects:
Online Access:https://ieeexplore.ieee.org/document/9830745/
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author Danil Shamsimukhametov
Anton Kurapov
Mikhail Liubogoshchev
Evgeny Khorov
author_facet Danil Shamsimukhametov
Anton Kurapov
Mikhail Liubogoshchev
Evgeny Khorov
author_sort Danil Shamsimukhametov
collection DOAJ
description Although the widely-used Transport Layer Security (TLS) protocol hides application data, an unencrypted part of the TLS handshake, specifically the server name indication (SNI), is a backdoor for encrypted traffic classification frameworks. The recently developed Encrypted ClientHello (ECH) amendment to the TLS protocol aims to protect the privacy-sensitive content of the ClientHello message, including SNI. Conversely, ECH can be a game-changer in the early detection of encrypted traffic. The paper shows that the performance of the state-of-the-art traffic classification algorithms degrades significantly with the introduction of the ECH. Hence, novel approaches to real-time traffic classification are required. The paper develops two novel traffic classification algorithms to address this challenge. The first one uses unencrypted bytes of the TLS Hello messages as independent features of the Random Forest algorithm. It is extremely lightweight and suits throughput-focused traffic classification. It is faster than state-of-the-art algorithms by three times and achieves higher classification quality. The second algorithm augments the approach of the first one by focusing on the particular metadata of the handshake. This way, it efficiently extracts data from the exchange and achieves the highest classification quality in all the considered scenarios. It has a three times lower error rate than state-of-the-art algorithms and provides a reliable classification of ECH traffic.
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spelling doaj.art-607f3719c5bb4599a2843892c9148c422022-12-22T00:58:05ZengIEEEIEEE Access2169-35362022-01-0110778837789710.1109/ACCESS.2022.31914319830745Is Encrypted ClientHello a Challenge for Traffic Classification?Danil Shamsimukhametov0Anton Kurapov1Mikhail Liubogoshchev2https://orcid.org/0000-0003-2674-7674Evgeny Khorov3https://orcid.org/0000-0001-5541-4671Wireless Networks Laboratory, Institute for Information Transmission Problems of the Russian Academy of Sciences, Moscow, RussiaWireless Networks Laboratory, Institute for Information Transmission Problems of the Russian Academy of Sciences, Moscow, RussiaWireless Networks Laboratory, Institute for Information Transmission Problems of the Russian Academy of Sciences, Moscow, RussiaWireless Networks Laboratory, Institute for Information Transmission Problems of the Russian Academy of Sciences, Moscow, RussiaAlthough the widely-used Transport Layer Security (TLS) protocol hides application data, an unencrypted part of the TLS handshake, specifically the server name indication (SNI), is a backdoor for encrypted traffic classification frameworks. The recently developed Encrypted ClientHello (ECH) amendment to the TLS protocol aims to protect the privacy-sensitive content of the ClientHello message, including SNI. Conversely, ECH can be a game-changer in the early detection of encrypted traffic. The paper shows that the performance of the state-of-the-art traffic classification algorithms degrades significantly with the introduction of the ECH. Hence, novel approaches to real-time traffic classification are required. The paper develops two novel traffic classification algorithms to address this challenge. The first one uses unencrypted bytes of the TLS Hello messages as independent features of the Random Forest algorithm. It is extremely lightweight and suits throughput-focused traffic classification. It is faster than state-of-the-art algorithms by three times and achieves higher classification quality. The second algorithm augments the approach of the first one by focusing on the particular metadata of the handshake. This way, it efficiently extracts data from the exchange and achieves the highest classification quality in all the considered scenarios. It has a three times lower error rate than state-of-the-art algorithms and provides a reliable classification of ECH traffic.https://ieeexplore.ieee.org/document/9830745/TLSencrypted ClientHelloencrypted SNIencrypted traffic classificationneural networksRandom Forest
spellingShingle Danil Shamsimukhametov
Anton Kurapov
Mikhail Liubogoshchev
Evgeny Khorov
Is Encrypted ClientHello a Challenge for Traffic Classification?
IEEE Access
TLS
encrypted ClientHello
encrypted SNI
encrypted traffic classification
neural networks
Random Forest
title Is Encrypted ClientHello a Challenge for Traffic Classification?
title_full Is Encrypted ClientHello a Challenge for Traffic Classification?
title_fullStr Is Encrypted ClientHello a Challenge for Traffic Classification?
title_full_unstemmed Is Encrypted ClientHello a Challenge for Traffic Classification?
title_short Is Encrypted ClientHello a Challenge for Traffic Classification?
title_sort is encrypted clienthello a challenge for traffic classification
topic TLS
encrypted ClientHello
encrypted SNI
encrypted traffic classification
neural networks
Random Forest
url https://ieeexplore.ieee.org/document/9830745/
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