High-Speed Convolution Core Architecture for Privacy-Preserving Neural Networks
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| Publicado en: | Programming and Computer Software vol. 50, no. 6 (Dec 2024), p. 417 |
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| Autor Principal: | |
| Outros autores: | , , |
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Springer Nature B.V.
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| Acceso en liña: | Citation/Abstract Full Text Full Text - PDF |
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| 022 | |a 0361-7688 | ||
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| 024 | 7 | |a 10.1134/S0361768824700282 |2 doi | |
| 035 | |a 3130548032 | ||
| 045 | 2 | |b d20241201 |b d20241231 | |
| 100 | 1 | |a Lapina, M. A. |u North Caucasian Center for Mathematical Research, North Caucasus Federal University, Stavropol, Russia (GRID:grid.440697.8) (ISNI:0000 0004 0646 0593) | |
| 245 | 1 | |a High-Speed Convolution Core Architecture for Privacy-Preserving Neural Networks | |
| 260 | |b Springer Nature B.V. |c Dec 2024 | ||
| 513 | |a Journal Article | ||
| 520 | 3 | |a Due to legal restrictions or restrictions related to companies' internal information policies, businesses often do not trust sensitive information to public cloud providers. One of the mechanisms to ensure the security of sensitive data in clouds is homomorphic encryption. Privacy-preserving neural networks are used to design solutions that utilize neural networks under these conditions. They exploit the homomorphic encryption mechanism, thus enabling the security of commercial information in the cloud. The main deterrent to the use of privacy-preserving neural networks is the large computational and spatial complexity of the scalar multiplication algorithm, which is the basic algorithm for computing mathematical convolution. In this paper, we propose a scalar multiplication algorithm that reduces the spatial complexity from quadratic to linear, and reduces the computation time of scalar multiplication by a factor of 1.38. | |
| 653 | |a Encryption | ||
| 653 | |a Big Data | ||
| 653 | |a Neurons | ||
| 653 | |a Personal information | ||
| 653 | |a Neural networks | ||
| 653 | |a Security | ||
| 653 | |a Artificial intelligence | ||
| 653 | |a Convolution | ||
| 653 | |a Privacy | ||
| 653 | |a Algorithms | ||
| 653 | |a Data encryption | ||
| 653 | |a Complexity | ||
| 653 | |a Cloud computing | ||
| 653 | |a Efficiency | ||
| 700 | 1 | |a Shiriaev, E. M. |u North Caucasian Center for Mathematical Research, North Caucasus Federal University, Stavropol, Russia (GRID:grid.440697.8) (ISNI:0000 0004 0646 0593) | |
| 700 | 1 | |a Babenko, M. G. |u North Caucasian Center for Mathematical Research, North Caucasus Federal University, Stavropol, Russia (GRID:grid.440697.8) (ISNI:0000 0004 0646 0593) | |
| 700 | 1 | |a Istamov, I. |u Samarkand State University Named after Sharof Rashidov, Samarkand, Uzbekistan (GRID:grid.77443.33) (ISNI:0000 0001 0942 5708) | |
| 773 | 0 | |t Programming and Computer Software |g vol. 50, no. 6 (Dec 2024), p. 417 | |
| 786 | 0 | |d ProQuest |t Advanced Technologies & Aerospace Database | |
| 856 | 4 | 1 | |3 Citation/Abstract |u https://www.proquest.com/docview/3130548032/abstract/embedded/6A8EOT78XXH2IG52?source=fedsrch |
| 856 | 4 | 0 | |3 Full Text |u https://www.proquest.com/docview/3130548032/fulltext/embedded/6A8EOT78XXH2IG52?source=fedsrch |
| 856 | 4 | 0 | |3 Full Text - PDF |u https://www.proquest.com/docview/3130548032/fulltextPDF/embedded/6A8EOT78XXH2IG52?source=fedsrch |