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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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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Short Paper: Declarative Demand-Driven Reverse Engineering

Yihao Sun, Jeffrey Ching, Kristopher Micinski (Department of Electical Engineering and Computer Science, Syracuse University)

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ALchemist: Fusing Application and Audit Logs for Precise Attack...

Le Yu (Purdue University), Shiqing Ma (Rutgers University), Zhuo Zhang (Purdue University), Guanhong Tao (Purdue University), Xiangyu Zhang (Purdue University), Dongyan Xu (Purdue University), Vincent E. Urias (Sandia National Laboratories), Han Wei Lin (Sandia National Laboratories), Gabriela Ciocarlie (SRI International), Vinod Yegneswaran (SRI International), Ashish Gehani (SRI International)

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