QUIC website fingerprinting based on automated machine learning

IF 4.1 3区计算机科学 Q1 COMPUTER SCIENCE, INFORMATION SYSTEMS

ICT Express Pub Date : 2024-06-01 DOI:10.1016/j.icte.2023.12.008

Joonseo Ha, Heejun Roh

引用次数: 0

Abstract

Recently, QUIC for the secure and faster connections has standardized but it is unclear that QUIC can cope with website fingerprinting (WF), a technique to infer visited websites from network traffic, since most existing efforts targeted TCP-induced traffic. To this end, we propose a novel QUIC WF technique based on Automated Machine Learning (AutoML). In our approach, we revisit traffic features appeared in literature, but relies on an AutoML framework to achieve best practice without manual intervention. Through experiments, we show that our technique outperforms state-of-the-art WF techniques with an F1-score of 99.79% and a 20-precision of 92.60%.

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基于自动机器学习的 QUIC 网站指纹识别技术

最近，用于安全和快速连接的 QUIC 已标准化，但 QUIC 是否能应对网站指纹（WF）（一种从网络流量推断访问过的网站的技术）还不清楚，因为现有的大多数工作都是针对 TCP 引起的流量。为此，我们提出了一种基于自动机器学习（AutoML）的新型 QUIC WF 技术。在我们的方法中，我们重新审视了文献中出现的流量特征，但依靠 AutoML 框架实现了无需人工干预的最佳实践。通过实验，我们发现我们的技术优于最先进的 WF 技术，F1 分数为 99.79%，20 精度为 92.60%。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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来源期刊

ICT Express Multiple-

CiteScore

10.20

自引率

1.90%

发文量

167

审稿时长

35 weeks

期刊介绍： The ICT Express journal published by the Korean Institute of Communications and Information Sciences (KICS) is an international, peer-reviewed research publication covering all aspects of information and communication technology. The journal aims to publish research that helps advance the theoretical and practical understanding of ICT convergence, platform technologies, communication networks, and device technologies. The technology advancement in information and communication technology (ICT) sector enables portable devices to be always connected while supporting high data rate, resulting in the recent popularity of smartphones that have a considerable impact in economic and social development.