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  1. Privacy Enhancing Technologies Symposium 2021

    PETS 2021 The 21st Privacy Enhancing Technologies Symposium July 12–16, 2021 On the Internet The annual Privacy Enhancing Technologies Symposium (PETS) brings ...

  2. Privacy Enhancing Technologies Symposium 2021

    Monday, July 12 Tuesday, July 13 Wednesday, July 14 Thursday, July 15 Friday, July 16 (HotPETs)

  3. Privacy Enhancing Technologies Symposium 2021

    SGX-MR: Regulating Dataflows for Protecting Access Patterns of Data-Intensive SGX Applications A K M Mubashwir Alam (Marquette University), Sagar Sharma (HP Inc), and …

  4. Privacy Enhancing Technologies Symposium 2021

    Links to Sites of Interest Past Symposiums/Workshops PETS 2025 — 25th Symposium PETS 2024 — 24th Symposium PETS 2023 — 23rd Symposium PETS 2022 — 22nd Symposium …

  5. With this shift to the digital, on-demand distribu-tion of media comes increased convenience and cost sav-ings for consumers—and an unprecedented capacity for content distributors to …

  6. 1 Introduction the adoption of digitalization. According to Gandorfer et al. [18], privacy is a factor that tends to slow the pro-cess of digitalization. The processing and exchange of data is a key …

  7. Privacy Enhancing Technologies Symposium 2021

    Registration Info Register for PETS 2021: https://pets21.ticketspice.com/privacy-enhancing-technologies-2021 Registration for PETS 2021, a virtual event held in the ...

  8. Privacy Enhancing Technologies Symposium 2021

    The organizers expect that anyone participating in PETS will—at minimum—treat others with respect for their dignity and autonomy. Correspondingly, behavior that violates these principles …

  9. The CNAME of the Game: Large-scale Analysis of DNS-based Tracking Evasion Abstract: Online tracking is a whack-a-mole game between trackers who build and monetize behavioral user …

  10. Falcon: Honest-Majority Maliciously Secure Framework for Private Deep Learning Abstract: We propose Falcon, an end-to-end 3-party protocol for efficient private training and inference of …