Douglas Leith and Stephen Farrell (Trinity College Dublin)

We report on an independent assessment of the Android implementation of the Google/Apple Exposure Notification (GAEN) system. While many health authorities have committed to making the code for their contact tracing apps open source, these apps depend upon the GAEN API for their operation and this is not open source. Public documentation of the GAEN API is also limited. We find that the GAEN API uses a filtered Bluetooth LE signal strength measurement that can be potentially misleading with regard to the proximity between two handsets. We also find that the exposure duration values reported by the API are coarse grained and can somewhat overestimate the time that two handsets are in proximity. Updates to the GAEN API that can affect contact tracing performance, and so public health, are silently installed on user handsets. While facilitating rapid rollout of changes, the lack of transparency around this raises obvious concerns.

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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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EarArray: Defending against DolphinAttack via Acoustic Attenuation

Guoming Zhang (Zhejiang University), Xiaoyu Ji (Zhejiang University), Xinfeng Li (Zhejiang University), Gang Qu (University of Maryland), Wenyuan Xu (Zhejing University)

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FARE: Enabling Fine-grained Attack Categorization under Low-quality Labeled Data

Junjie Liang (The Pennsylvania State University), Wenbo Guo (The Pennsylvania State University), Tongbo Luo (Robinhood), Vasant Honavar (The Pennsylvania State University), Gang Wang (University of Illinois at Urbana-Champaign), Xinyu Xing (The Pennsylvania State University)

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