Microsoft SEAL
| Microsoft SEAL example of homomorphic encryption | |
| Developer(s) | Microsoft Research |
|---|---|
| Initial release | December 3, 2018; 6 years ago (2018年12月03日) |
| Stable release | 4.0.0
/ March 17, 2022; 2 years ago (2022年03月17日) |
| Repository | github |
| Written in | C++ |
| Operating system | Microsoft Windows, macOS, Linux, Android |
| Platform | IA-32, x86-64, ARM64 |
| Type | Homomorphic encryption library |
| License | MIT License |
| Website | www |
Simple Encrypted Arithmetic Library or SEAL is a free and open-source cross platform software library developed by Microsoft Research that implements various forms of homomorphic encryption.[1] [2]
History
[edit ]Development originally came out of the Cryptonets paper,[3] demonstrating that artificial intelligence algorithms could be run on homomorphically encrypted data.[4]
It is open-source (under the MIT License) and written in standard C++ without external dependencies and so it can be compiled cross platform. An official .NET wrapper written in C# is available and makes it easier for .NET applications to interact with SEAL.
Features
[edit ]Algorithms
[edit ]Microsoft SEAL supports both asymmetric and symmetric (added in version 3.4) encryption algorithms.
Scheme types
[edit ]Microsoft SEAL comes with two different homomorphic encryption schemes with very different properties:
- BFV:[5] The BFV scheme allows modular arithmetic to be performed on encrypted integers. For applications where exact values are necessary, the BFV scheme is the only choice.
- CKKS:[6] The CKKS scheme allows additions and multiplications on encrypted real or complex numbers, but yields only approximate results. In applications such as summing up encrypted real numbers, evaluating machine learning models on encrypted data, or computing distances of encrypted locations CKKS is going to be by far the best choice.
Compression
[edit ]Data compression can be achieved by building SEAL with Zlib support. By default, data is compressed using the DEFLATE algorithm which achieves significant memory footprint savings when serializing objects such as encryption parameters, ciphertexts, plaintexts, and all available keys: Public, Secret, Relin (relinearization), and Galois. Compression can always be disabled.
Availability
[edit ]There are several known ports of SEAL to other languages in active development:
C++
[edit ]- Microsoft SEAL (Microsoft's source)
C#/F#
[edit ]- NuGet (Microsoft's official package)
Python
[edit ]JavaScript
[edit ]TypeScript
[edit ]References
[edit ]- ^ Microsoft SEAL is an easy-to-use and powerful homomorphic encryption library.: microsoft/SEAL, Microsoft, 2019年11月20日, archived from the original on 2019年05月31日, retrieved 2019年11月20日
- ^ Coron, Jean-Sébastien; Nielsen, Jesper Buus (2017年04月10日). Advances in Cryptology – EUROCRYPT 2017: 36th Annual International Conference on the Theory and Applications of Cryptographic Techniques, Paris, France, April 30 – May 4, 2017, Proceedings. Springer. p. 104. ISBN 9783319566146.
- ^ Downlin, Nathan; Gilad-Bachrach, Ran; Laine, Kim; Lauter, Kirstin; Naehrig, Michael; Wernsing, John (2016年05月25日). "CryptoNets: Applying Neural Networks to Encrypted Data with High Throughput and Accuracy" (PDF). Proceedings of the 33rd International Conference on Machine Learning. Archived from the original (PDF) on 2018年08月26日.
- ^ "The Microsoft Simple Encrypted Arithmetic Library goes open source". Microsoft Research. 2018年12月03日. Archived from the original on 2019年11月12日. Retrieved 2019年11月20日.
- ^ Fan, Junfeng; Vercauteren, Frederik (2012). "Somewhat Practical Fully Homomorphic Encryption".
{{cite journal}}: Cite journal requires|journal=(help) - ^ Cheon, Jung Hee; Kim, Andrey; Kim, Miran; Song, Yongsoo (2017). "Homomorphic Encryption for Arithmetic of Approximate Numbers". In Takagi, Tsuyoshi; Peyrin, Thomas (eds.). Advances in Cryptology – ASIACRYPT 2017. Lecture Notes in Computer Science. Vol. 10624. Cham: Springer International Publishing. pp. 409–437. doi:10.1007/978-3-319-70694-8_15. ISBN 978-3-319-70694-8. S2CID 3164123.