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  1. MAPS: Scaling Privacy Compliance Analysis to a Million Apps

    Volume: 2019 Issue: 3 Pages: 66–86 DOI: Download PDF Abstract: The app economy is largely reliant on data collection as its primary revenue model. To comply with legal requirements, app …

  2. PoPETs Proceedings

    Volume 2025 Volume 2024 Volume 2023 Volume 2022 Volume 2021 Volume 2020 Volume 2019 Volume 2018 Volume 2017 Volume 2016 Volume 2015 Privacy Enhancing Technologies …

  3. Keywords: machine learning; privacy; inference attacks DOI 10.2478/popets-2019-0008 Received 2018-05-31; revised 2018-09-15; accepted 2018-09-16.

  4. Proceedings on Privacy Enhancing Technologies ; 2019 (4):34–53 Jeremy Martin*, Douglas Alpuche, Kristina Bodeman, Lamont Brown, Ellis Fenske*, Lucas Foppe, Travis Mayberry*, …

  5. PoPETs Proceedings — Tracking Anonymized Bluetooth Devices

    Authors: Johannes K Becker (Boston University), David Li (Boston University), David Starobinski (Boston University) Volume: 2019 Issue: 3 Pages: 50–65 DOI: https://doi.org/10.2478/popets …

  6. Investigating People’s Privacy Risk Perception

    Volume: 2019 Issue: 3 Pages: 267–288 DOI: Download PDF Abstract: Although media reports often warn about risks associated with using privacy-threatening technologies, most lay users …

  7. StealthDB: a Scalable Encrypted Database with Full SQL Query …

    Volume: 2019 Issue: 3 Pages: 370–388 DOI: https://doi.org/10.2478/popets-2019-0052 Download PDF Abstract: Encrypted database systems provide a great method for protecting sensitive …

  8. PoPETs Proceedings — ConsenSGX: Scaling Anonymous …

    Volume: 2019 Issue: 3 Pages: 331–349 DOI: Download PDF Abstract: Anonymous communications networks enable individuals to maintain their privacy online. The most popular …

  9. SecureNN: 3-Party Secure Computation for Neural Network Training

    Volume: 2019 Issue: 3 Pages: 26–49 DOI: Download PDF Abstract: Neural Networks (NN) provide a powerful method for machine learning training and inference. To effectively train, it is …

  10. Proceedings on Privacy Enhancing Technologies ; 2019 (3):409–429 Benjamin Kuykendall*, Hugo Krawczyk, and Tal Rabin