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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FLTrust: Byzantine-robust Federated Learning via Trust Bootstrapping

Xiaoyu Cao (Duke University), Minghong Fang (The Ohio State University), Jia Liu (The Ohio State University), Neil Zhenqiang Gong (Duke University)

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Rosita: Towards Automatic Elimination of Power-Analysis Leakage in Ciphers

Madura A. Shelton (University of Adelaide), Niels Samwel (Radboud University), Lejla Batina (Radboud University), Francesco Regazzoni (University of Amsterdam and ALaRI – USI), Markus Wagner (University of Adelaide), Yuval Yarom (University of Adelaide and Data61)

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Analyzing and Creating Malicious URLs: A Comparative Study on...

Vincent Drury (IT-Security Research Group, RWTH Aachen University), Rene Roepke (Learning Technologies Research Group, RWTH Aachen University), Ulrik Schroeder (Learning Technologies Research Group, RWTH Aachen University), Ulrike Meyer (IT-Security Research Group, RWTH Aachen University)

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When DNS Goes Dark: Understanding Privacy and Shaping Policy...

Vijay k. Gurbani and Cynthia Hood ( Illinois Institute of Technology), Anita Nikolich (University of Illinois), Henning Schulzrinne (Columbia University) and Radu State (University of Luxembourg)

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