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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Zhenxiao Qi (UC Riverside), Qian Feng (Baidu USA), Yueqiang Cheng (NIO Security Research), Mengjia Yan (MIT), Peng Li (ByteDance), Heng Yin (UC Riverside), Tao Wei (Ant Group)

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POSEIDON: Privacy-Preserving Federated Neural Network Learning

Sinem Sav (EPFL), Apostolos Pyrgelis (EPFL), Juan Ramón Troncoso-Pastoriza (EPFL), David Froelicher (EPFL), Jean-Philippe Bossuat (EPFL), Joao Sa Sousa (EPFL), Jean-Pierre Hubaux (EPFL)

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Trust the Crowd: Wireless Witnessing to Detect Attacks on...

Kai Jansen (Ruhr University Bochum), Liang Niu (New York University), Nian Xue (New York University), Ivan Martinovic (University of Oxford), Christina Pöpper (New York University Abu Dhabi)

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Understanding and Detecting International Revenue Share Fraud

Merve Sahin (SAP Security Research), Aurélien Francillon (EURECOM)

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