2026-09-21T06:41:47Z https://www.ideals.illinois.edu/oai-pmh

oai:www.ideals.illinois.edu:2142/120452 2023-09-05 col_2142_5131 col_2142_10761 com_2142_5130 com_2142_10755 com_2142_234

Kumar, Ranjitha 2023-05 application/pdf en text Submission published under a 24 month embargo labeled 'U of I Access', the embargo will last until 2025-05-01 The student, Carl Guo, accepted the attached license on 2023-05-02 at 12:07. The student, Carl Guo, submitted this Thesis for approval on 2023-05-02 at 12:24. This Thesis was approved for publication on 2023-05-03 at 12:29. DSpace SAF Submission Ingestion Package generated from Vireo submission #19297 on 2023-09-01 at 17:15:52 Exploring user data privacy interfaces for mobile UIS Guo, Carl 2023-05-03 Mobile Privacy Interaction Mining Personally Identifiable Informaiton Many applications view user privacy protection through the perspective of securing users’ personally identifiable information (PII) such as email addresses, full names, and government identification. However, findings indicate certain types of data in mobile applications exist that are not covered by current PII definitions and tools. In this thesis, we will introduce new tools we built to facilitate the exploration of new understandings of user privacy for mobile UIs. Specifically, we created a privacy redaction probe that enables users to easily redact UI regions on a mobile screen they consider “too sensitive to share”. We also disclose some initial design principles we considered when building these interfaces. Next, we implemented two differing versions of our UI redaction tool and integrate them into two mobile interaction mining systems to test our privacy probe’s usefulness in redacting sensitive UI data inside interaction traces. Finally, to evaluate our implementation and demonstrate an example use case for our redaction interface, we conduct a user study where we asked users record interaction traces on their personal accounts and redact UI regions they consider ”too sensitive to share.” By analyzing these redactions through open iterative coding, we identified some trends in user attitudes in regards to sensitive UI content. Text eng https://hdl.handle.net/2142/120452 Copyright 2023 Carl Guo M.S. Thesis Computer Science University of Illinois at Urbana-Champaign Computer Science