Document Type
Conference Proceeding
Publication Date
8-27-2025
Publication Title
2025 Silicon Valley Cybersecurity Conference (SVCC)
Pages
1-10
Publisher Name
IEEE
Abstract
Maintaining ones privacy online is often thought of as using strong passwords and using encrypted network communications. However, website fingerprinting has in the past been proven to expose even highly encrypted, salted, and padded communications. Using just packet size, direction, and a known IP address an adversary can observe and accurately predict websites a user visits online. In this paper we go beyond just website fingerprinting and show an adversary is able to identify specific articles a user visits, specific Google searches they conduct, and specific actions they take in Virtual Reality. We analyzed network traffic by developing a set of features that yields better performance than previous work, and predicted user behavior using a RandomForest classifier. Ultimately we show that it is possible for an adversary to predict user’s online activity for various applications.
Recommended Citation
Moran, Madeline; Honig, Joshua; Ferrell, Nathan; Soni, Shreena; Homan, Sophia; Chan-Tin, Eric; and Abuhamad, Mohammed. Encrypted Network Traffic Analysis: To Website Fingerprinting and Beyond. 2025 Silicon Valley Cybersecurity Conference (SVCC), , : 1-10, 2025. Retrieved from Loyola eCommons, Computer Science: Faculty Publications and Other Works, http://dx.doi.org/10.1109/SVCC65277.2025.11133612
Creative Commons License
This work is licensed under a Creative Commons Attribution-NonCommercial-No Derivative Works 4.0 International License.
Copyright Statement
© IEEE, 2025.
Author Manuscript
This is a pre-publication author manuscript of the final, published article.
Comments
Author Posting © IEEE, 2025. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works. The definitive version of this work was published in 2025 Silicon Valley Cybersecurity Conference (SVCC), https://doi.org/10.1109/SVCC65277.2025.11133612.