{"id":452256,"date":"2022-01-17T16:56:48","date_gmt":"2022-01-18T00:56:48","guid":{"rendered":"https:\/\/www.microsoft.com\/en-us\/research\/?post_type=msr-research-item&p=452256"},"modified":"2022-01-17T16:56:48","modified_gmt":"2022-01-18T00:56:48","slug":"security-of-homomorphic-encryption","status":"publish","type":"msr-research-item","link":"https:\/\/www.microsoft.com\/en-us\/research\/publication\/security-of-homomorphic-encryption\/","title":{"rendered":"SECURITY OF HOMOMORPHIC ENCRYPTION"},"content":{"rendered":"
We met as a group during the Homomorphic Encryption Standardization Workshop on July 13-
\n14, 2017, hosted at Microsoft Research in Redmond. Researchers from around the world
\nrepresented a number of different communities: government, industry, and academia. There are
\nat least 6 research groups around the world who have made libraries for general-purpose
\nhomomorphic encryption available ([SEAL], [HElib], [Palisade], [cuHE], [NFLLib], [HEAAN]) for
\napplications and general-purpose use, and demos were shown of all 6 libraries. All 6 of these
\ngeneral-purpose libraries for homomorphic encryption were based on RLWE-based systems
\n(Ring Learning With Errors), and all libraries implemented one of two encryption schemes (BGV
\nor B\/FV) and also displayed common choices for the underlying ring, error distribution, and
\nparameter selection.
\nHomomorphic Encryption is a breakthrough new technology which can enable private cloud
\nstorage and computation solutions. Demos shown at the workshop included a SEAL demo of
\nCryptoNets, which performs efficient computation of image processing tasks such as handwriting recognition on encrypted data using neural nets. Many other applications are described
\nin detail in the white paper by the Applications group. In order for Homomorphic Encryption to
\nbe adopted in medical, health, and financial sectors to protect data and patient and consumer
\nprivacy, it will have to be standardized, most likely by multiple standardization bodies and
\ngovernment agencies. An important part of standardization is broad agreement on security
\nlevels for varying parameter sets. Although extensive research and benchmarking has been
\ndone in the research community to establish the foundations for this effort, it is hard to find all
\nthe information in one place, along with concrete parameter recommendations for applications
\nand deployment.
\nThis document is an attempt to capture the collective knowledge at the workshop regarding the
\ncurrently known state of security of these schemes, to specify the schemes, and to recommend
\na wide selection of parameters to be used for homomorphic encryption at various security
\nlevels. We describe known attacks and their estimated running times in order to make these
\nparameter recommendations. We also describe additional features of these encryption schemes
\nwhich make them useful in different applications and scenarios. Many sections of this document
\nare intended for direct use as a first draft of parts of the standard to be prepared by the Working
\nGroup formed at this workshop.<\/p>\n","protected":false},"excerpt":{"rendered":"
We met as a group during the Homomorphic Encryption Standardization Workshop on July 13- 14, 2017, hosted at Microsoft Research in Redmond. Researchers from around the world represented a number of different communities: government, industry, and academia. There are at least 6 research groups around the world who have made libraries for general-purpose homomorphic encryption 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