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Homomorphic Encryption Standard

In: Protecting Privacy through Homomorphic Encryption

Author

Listed:
  • Martin Albrecht

    (Facebook)

  • Melissa Chase

    (Microsoft Research, Cryptography and Privacy Research Group)

  • Hao Chen

    (Facebook)

  • Jintai Ding

    (Facebook)

  • Shafi Goldwasser

    (Facebook)

  • Sergey Gorbunov

    (Facebook)

  • Shai Halevi

    (Facebook)

  • Jeffrey Hoffstein

    (Facebook)

  • Kim Laine

    (Microsoft Research, Cryptography and Privacy Research Group)

  • Kristin Lauter

    (Microsoft Research, Cryptography and Privacy Research Group)

  • Satya Lokam

    (Facebook)

  • Daniele Micciancio

    (Facebook)

  • Dustin Moody

    (National Institute of Standards and Technology, Computer Security Division)

  • Travis Morrison

    (Virginia Tech University, Mathematics)

  • Amit Sahai

    (UCLA, Computer Science)

  • Vinod Vaikuntanathan

    (Massachusetts Institute of Technology, Electrical Engineering and Computer Science)

Abstract

We met as a group during the Homomorphic Encryption Standardization Workshop on July 13–14, 2017, hosted at Microsoft Research in Redmond, and again during the second workshop on March 15–16, 2018 in MIT. Researchers from around the world represented government, industry, and academia. There are several research groups around the world who have made libraries for general-purpose homomorphic encryption available for applications and general-purpose use. Some examples include [40–46,47]. Most general-purpose libraries for homomorphic encryption implement schemes that are based on the ring learning-with-error (RLWE) problem, and many of them displayed common choices for the underlying rings, error distributions, and other parameters.

Suggested Citation

  • Martin Albrecht & Melissa Chase & Hao Chen & Jintai Ding & Shafi Goldwasser & Sergey Gorbunov & Shai Halevi & Jeffrey Hoffstein & Kim Laine & Kristin Lauter & Satya Lokam & Daniele Micciancio & Dustin, 2021. "Homomorphic Encryption Standard," Springer Books, in: Kristin Lauter & Wei Dai & Kim Laine (ed.), Protecting Privacy through Homomorphic Encryption, pages 31-62, Springer.
    • Handle: RePEc:spr:sprchp:978-3-030-77287-1_2
    DOI: 10.1007/978-3-030-77287-1_2
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