Encrypted computing in Python using OpenFHE
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| Title | Encrypted computing in Python using OpenFHE |
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| Number of Parts | 131 |
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| License | CC Attribution - NonCommercial - ShareAlike 3.0 Unported: You are free to use, adapt and copy, distribute and transmit the work or content in adapted or unchanged form for any legal and non-commercial purpose as long as the work is attributed to the author in the manner specified by the author or licensor and the work or content is shared also in adapted form only under the conditions of this license. |
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| Abstract | Fully Homomorphic Encryption (FHE) is a privacy-enhancing technology that enables performing computations over encrypted data. FHE has recently seen a lot of progress, and commercial applications of FHE are now available. One of the main application domains for FHE is privacy-preserving machine learning. We introduce a Python interface for OpenFHE, a popular open-source FHE C++ software library that supports all common FHE schemes. OpenFHE is a NumFocus-sponsored open-source project that has been authored by a community of well-known FHE cryptographers and software engineers.The talk provides a high-level introduction to FHE and its applications, and then provides an overview of the Python API. Several examples are presented to both illustrate FHE concepts and show the practicality of the technology.
More information about the OpenFHE project:
* Main website: openfhe.org/ ;
* OpenFHE discourse forum: openfhe.discourse.group/ ;
* Main OpenFHE repository: GitHub: openfheorg/openfhe-development ;
* OpenFHE organization: GitHub: openfheorg ;
* Main OpenFHE design paper: eprint.iacr.org/2022/915 |
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