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  1. How private is your period?: A systematic analysis of menstrual app ...

    Volume: 2020 Issue: 4 Pages: 491–510 DOI: https://doi.org/10.2478/popets-2020-0083 Download PDF Abstract: Menstruapps are mobile applications that can track a user’s reproductive cycle, sex life and …

  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 Symposium …

  3. Proceedings on Privacy Enhancing Technologies ; 2020 (4):414–433 Payman Mohassel, Mike Rosulek, and Ni Trieu*

  4. Practical Privacy-Preserving K-means Clustering

    Volume: 2020 Issue: 4 Pages: 414–433 DOI: https://doi.org/10.2478/popets-2020-0080 Download PDF Abstract: Clustering is a common technique for data analysis, which aims to partition data into similar …

  5. PoPETs Proceedings — When Speakers Are All Ears: Characterizing ...

    Volume: 2020 Issue: 4 Pages: 255–276 DOI: Download PDF Abstract: Internet-connected voice-controlled speakers, also known as smart speakers, are increasingly popular due to their …

  6. Tik-Tok: The Utility of Packet Timing in Website Fingerprinting Attacks

    Volume: 2020 Issue: 3 Pages: 5–24 DOI: Download PDF Abstract: A passive local eavesdropper can leverage Website Fingerprinting (WF) to deanonymize the web browsing activity of Tor users. The …

  7. PoPETs Proceedings — Secure k-ish Nearest Neighbors Classifier

    Authors: Hayim Shaul (MIT), Dan Feldman (University of Haifa), Daniela Rus (MIT) Volume: 2020 Issue: 3 Pages: 42–61 DOI: https://doi.org/10.2478/popets-2020-0045 Download PDF Abstract: The k …

  8. Pets without PETs: on pet owners’ under-estimation of privacy …

    Volume: 2020 Issue: 1 Pages: 143–164 DOI: Download PDF Abstract: We report on a mixed-method, comparative study investigating whether there is a difference between privacy concerns expressed …

  9. Illuminating the Dark or how to recover what should not be seen in FE ...

    Volume: 2020 Issue: 2 Pages: 5–23 DOI: Download PDF Abstract: Classification algorithms/tools become more and more powerful and pervasive. Yet, for some use cases, it is necessary to be able …

  10. PoPETs Proceedings — SoK: Differential privacies

    Volume: 2020 Issue: 2 Pages: 288–313 DOI: https://doi.org/10.2478/popets-2020-0028 Download PDF Abstract: Shortly after it was first introduced in 2006, differential privacy became the flagship data …