{"id":{"repo_id":"uiuc","oai_identifier":"oai:www.ideals.illinois.edu:2142/129271"},"canonical_url":"https://search.dev.ndltd.org/etd/uiuc/oai:www.ideals.illinois.edu:2142/129271","repository":{"repo_id":"uiuc","name":"University of Illinois - Urbana-Champaign","base_url":"https://www.ideals.illinois.edu/oai-pmh"},"display":{"title":"Inferring communication pairs in end-to-end encrypted messaging applications","abstract":"Submission original under an indefinite embargo labeled 'Open Access'. The submission was exported from vireo on 2025-10-19 without embargo terms","abstract_html":"Submission original under an indefinite embargo labeled 'Open Access'. The submission was exported from vireo on 2025-10-19 without embargo terms","abstract_has_math":false,"creators":["Aoun, Tala"],"institution":"University of Illinois Urbana-Champaign","degree_name":"M.S.","degree_level":"Thesis","degree_discipline":"Electrical & Computer Engr","degree_department":null,"school":null,"contributors":["Levchenko, Kirill"],"advisors":[],"committee_chairs":[],"committee_members":[],"year":2025,"date_issued":"2025-04-29","date_published":"2025-04-29","updated_at":"2026-07-22T22:25:04Z","subjects":["network security","encrypted communication","timing correlation attacks"],"languages":["en","eng"],"rights":["Copyright 2025 Tala Aoun"],"rights_urls":[],"identifier_entries":[]},"links":{"outbound_url":"https://hdl.handle.net/2142/129271","outbound_label":"Handle","outbound_source":"dc:identifier"},"metadata_groups":[{"id":"people","label":"People","entries":[{"key":"dc:contributor","label":"Contributor","values":["Levchenko, Kirill"]},{"key":"dc:creator","label":"Author","values":["Aoun, Tala"]}]},{"id":"academic_context","label":"Academic Context","entries":[{"key":"dc:date","label":"Dc Date","values":["2025-04-29","2025-05"]},{"key":"dc:type","label":"Dc Type","values":["text","Thesis"]},{"key":"thesis:degree_discipline","label":"Discipline","values":["Electrical & Computer Engr"]},{"key":"thesis:degree_level","label":"Degree Level","values":["Thesis"]},{"key":"thesis:degree_name","label":"Degree Name","values":["M.S."]},{"key":"thesis:institution_name","label":"Thesis Institution Name","values":["University of Illinois Urbana-Champaign"]}]},{"id":"subjects_keywords","label":"Subjects and Keywords","entries":[{"key":"dc:subject","label":"Dc Subject","values":["network security","encrypted communication","timing correlation attacks"]}]},{"id":"language_rights","label":"Language and Rights","entries":[{"key":"dc:language","label":"Dc Language","values":["en","eng"]},{"key":"dc:rights","label":"Dc Rights","values":["Copyright 2025 Tala Aoun"]}]},{"id":"identifiers","label":"Identifiers","entries":[{"key":"dc:identifier","label":"Identifier","values":["https://hdl.handle.net/2142/129271"]}]},{"id":"additional","label":"Additional Metadata","entries":[{"key":"dc:description","label":"Description","values":["Submission original under an indefinite embargo labeled 'Open Access'. The submission was exported from vireo on 2025-10-19 without embargo terms","The student, Tala Aoun, accepted the attached license on 2025-04-29 at 01:11.","The student, Tala Aoun, submitted this Thesis for approval on 2025-04-29 at 01:14.","This Thesis was approved for publication on 2025-04-29 at 15:23.","DSpace SAF Submission Ingestion Package generated from Vireo submission #22059 on 2025-10-19 at 18:11:12","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."]},{"key":"dc:format","label":"Dc Format","values":["application/pdf"]},{"key":"dc:title","label":"Title","values":["Inferring communication pairs in end-to-end encrypted messaging applications"]}]}],"canonical_facts":{"dc:contributor":["Levchenko, Kirill"],"dc:creator":["Aoun, Tala"],"dc:date":["2025-04-29","2025-05"],"dc:description":["Submission original under an indefinite embargo labeled 'Open Access'. The submission was exported from vireo on 2025-10-19 without embargo terms","The student, Tala Aoun, accepted the attached license on 2025-04-29 at 01:11.","The student, Tala Aoun, submitted this Thesis for approval on 2025-04-29 at 01:14.","This Thesis was approved for publication on 2025-04-29 at 15:23.","DSpace SAF Submission Ingestion Package generated from Vireo submission #22059 on 2025-10-19 at 18:11:12","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."],"dc:format":["application/pdf"],"dc:identifier":["https://hdl.handle.net/2142/129271"],"dc:language":["en","eng"],"dc:rights":["Copyright 2025 Tala Aoun"],"dc:subject":["network security","encrypted communication","timing correlation attacks"],"dc:title":["Inferring communication pairs in end-to-end encrypted messaging applications"],"dc:type":["text","Thesis"],"thesis:degree_discipline":["Electrical & Computer Engr"],"thesis:degree_level":["Thesis"],"thesis:degree_name":["M.S."],"thesis:institution_name":["University of Illinois Urbana-Champaign"]},"updated_at":"2026-07-22T22:25:04Z"}