Inferring communication pairs in end-to-end encrypted messaging applications
Aoun, Tala
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https://hdl.handle.net/2142/129271
Description
Title
Inferring communication pairs in end-to-end encrypted messaging applications
Author(s)
Aoun, Tala
Issue Date
2025-04-29
Director of Research (if dissertation) or Advisor (if thesis)
Levchenko, Kirill
Department of Study
Electrical & Computer Eng
Discipline
Electrical & Computer Engr
Degree Granting Institution
University of Illinois Urbana-Champaign
Degree Name
M.S.
Degree Level
Thesis
Keyword(s)
network security
encrypted communication
timing correlation attacks
Language
eng
Abstract
Modern messaging platforms have widely adopted end-to-end encryption to secure user communications. However, encryption alone does not prevent adversaries from leveraging traffic analysis techniques to leak information and communication patterns. This poses significant risks, particularly in environments where metadata surveillance is used to suppress dissent, track activists, or monitor sensitive exchanges, such as those between journalists and whistleblowers. In this study, we analyze the extent to which an attacker monitoring network traffic can accurately determine the identity of a target user’s communication partner based solely on the encrypted traffic. We construct a model of user behavior based on real-world messaging data from WhatsApp, simulating communication scenarios and mapping them to observable network traffic patterns. Our approach identifies key metadata features such as message timing, packet sizes, and delivery notifications that enable traffic correlation. Our findings provide actionable insights for enhancing privacy in encrypted messaging applications and highlight the need for stronger defenses against metadata-based surveillance.
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