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PRIVEE: Privacy-Preserving Extensions of Epidemiological Apps with Sensitive Sensory Data

Grant number: unknown

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Key facts

  • Disease

    COVID-19

  • start year

    2020

  • Funder

    Volkswagen Stiftung

  • Principal Investigator

    Prof Dr and Prof Dr and Prof Dr Esfandiar Mohammadi, Stefan Fischer, Thomas Martinetz

  • Research Location

    Germany

  • Lead Research Institution

    Universität zu Lübeck

  • Research Priority Alignment

    N/A

  • Research Category

    Epidemiological studies

  • Research Subcategory

    Impact/ effectiveness of control measures

  • Special Interest Tags

    Innovation

  • Study Type

    Non-Clinical

  • Clinical Trial Details

    N/A

  • Broad Policy Alignment

    Pending

  • Age Group

    Not Applicable

  • Vulnerable Population

    Not applicable

  • Occupations of Interest

    Not applicable

Abstract

This project aims to extend contact-tracing with privacy-preserving functionality that utilize a richer set of sensory information (Wi-Fi, ambient noise, and ultrasound) together with a jointly trained classifier (via federated learning) to reduce the number of false positives and to develop privacy preserving regularly estimated statistics about crowd sizes that inform epidemiologists (e.g., in regulatory bodies) about the effectiveness of current restrictions or recent relaxation of restrictions.