网站指纹攻击综述
A Review of Website Fingerprinting Attacks
DOI: 10.12677/csa.2024.1411213, PDF,   
作者: 冯雨思：中国科学院信息工程研究所，北京；中国科学院大学网络空间安全学院，北京
关键词: 网站指纹攻击；侧信道；机器学习；Website Fingerprinting Attacks； Side Channel； Machine Learning
摘要: 网站指纹攻击利用统计方法来确定用户正在访问的网站，侵犯用户隐私，给互联网的安全和隐私带来了巨大挑战。网站指纹攻击首先收集用户访问不同网站时的数据，然后使用机器学习等方法处理数据，识别网站。之前的研究主要集中于传统的基于网络流量的网站指纹攻击，本文重点介绍了较新出现的基于主机侧信道的网站指纹攻击，并讨论了这两类攻击的流程、指纹特征、威胁模型、分类方法、评价指标和防御研究。文章最后展望了网站指纹攻击的未来研究方向，尤其是新式的基于主机侧信道数据的网站指纹攻击当前存在的问题及未来发展方向。
Abstract: Website fingerprinting attacks utilize statistical methods to identify which websites a user is visiting, thereby infringing on user privacy and posing significant challenges to internet security and privacy. These attacks first collect data generated when a user visits different websites and then use methods such as machine learning to process the data and identify the websites. Previous research has mainly focused on traditional network traffic-based website fingerprinting attacks. This paper highlights the more recently emerged host-side channel-based website fingerprinting attacks and discusses the process, fingerprinting characteristics, threat models, classification methods, evaluation metrics, and defense measures of these two types of attacks. Finally, this paper provides an outlook on the future research directions of website fingerprinting attacks, particularly addressing the current issues and future development of host-side channel-based website fingerprinting attacks.
文章引用：冯雨思. 网站指纹攻击综述[J]. 计算机科学与应用, 2024, 14(11): 28-38. https://doi.org/10.12677/csa.2024.1411213

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