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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RandRunner: Distributed Randomness from Trapdoor VDFs with Strong Uniqueness

Philipp Schindler (SBA Research), Aljosha Judmayer (SBA Research), Markus Hittmeir (SBA Research), Nicholas Stifter (SBA Research, TU Wien), Edgar Weippl (Universität Wien)

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Impact Evaluation of Falsified Data Attacks on Connected Vehicle...

Shihong Huang (University of Michigan, Ann Arbor), Yiheng Feng (Purdue University), Wai Wong (University of Michigan, Ann Arbor), Qi Alfred Chen (UC Irvine), Z. Morley Mao and Henry X. Liu (University of Michigan, Ann Arbor) Best Paper Award Runner-up ($200 cash prize)!

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Panel – Experiment Artifact Sharing: Challenges and Solutions

Moderator: Laura Tinnel (SRI International) Panelists: Clémentine Maurice (CNRS, IRIS); Martin Rosso (Eindhoven University of Technology); Eric Eide (U. Utah)

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