Abdulmajeed Alqhatani, Heather R. Lipford (University of North Carolina at Charlotte)

Users of wearable fitness devices share different pieces of information with a variety of recipients to support their health and fitness goals. Device platforms could ease this sharing and empower users to protect their information by providing controls and features centered around these common sharing goals. However, there is little research that examines existing mechanisms for sharing and privacy management, and what needs users have beyond their current controls. In this paper, we analyze five popular wearable device platforms to develop taxonomies of mechanisms based on common sharing patterns and boundaries, as well as data collection awareness. With this analysis, we identify design opportunities for supporting users’ sharing and privacy needs.

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PrivacyFlash Pro: Automating Privacy Policy Generation for Mobile Apps

Sebastian Zimmeck (Wesleyan University), Rafael Goldstein (Wesleyan University), David Baraka (Wesleyan University)

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Practical Blind Membership Inference Attack via Differential Comparisons

Bo Hui (The Johns Hopkins University), Yuchen Yang (The Johns Hopkins University), Haolin Yuan (The Johns Hopkins University), Philippe Burlina (The Johns Hopkins University Applied Physics Laboratory), Neil Zhenqiang Gong (Duke University), Yinzhi Cao (The Johns Hopkins University)

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