Tanisha Afnan and Yixin Zou, University of Michigan School of Information; Maryam Mustafa, Lahore University of Management Sciences; Mustafa Naseem and Florian Schaub, University of Michigan School of Information
Women who identify with Islam in the United States come from many different race, class, and cultural communities. They are also more likely to be first or second-generation immigrants. This combination of different marginal identities (religious affiliation, gender, immigration status, and race) exposes Muslim-American women to unique online privacy risks and consequences. We conducted 21 semi-structured interviews to understand how Muslim-American women perceive digital privacy risks related to three contexts: government surveillance, Islamophobia, and social surveillance. We find that privacy concerns held by Muslim-American women unfolded with respect to three dimensions of identity: as a result of their identity as Muslim-Americans broadly (e.g., Islamophobic online harassment), as Muslim-American women more specifically (e.g., reputational harms within one's cultural community for posting taboo content), and as a product of their own individual practices of Islam (e.g., constructing female-only spaces to share photos of oneself without a hijab). We discuss how these intersectional privacy concerns add to and expand on existing pro-privacy design principles, and lessons learned from our participants' privacy-protective strategies for improving the digital experiences of this community.
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author = {Tanisha Afnan and Yixin Zou and Maryam Mustafa and Mustafa Naseem and Florian Schaub},
title = {Aunties, Strangers, and the {FBI}: Online Privacy Concerns and Experiences of {Muslim-American} Women},
booktitle = {Eighteenth Symposium on Usable Privacy and Security (SOUPS 2022)},
year = {2022},
isbn = {978-1-939133-30-4},
address = {Boston, MA},
pages = {387--406},
url = {https://www.usenix.org/conference/soups2022/presentation/afnan},
publisher = {USENIX Association},
month = aug
}