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https://dspace.ncfu.ru/handle/123456789/28755| Title: | Analytical Review of Confidential Artificial Intelligence: Methods and Algorithms for Deployment in Cloud Computing |
| Authors: | Shiriaev, E. M. Ширяев, Е. М. Nazarov, A. S. Назаров, А. С. Kucherov, N. N. Кучеров, Н. Н. Babenko, M. G. Бабенко, М. Г. |
| Keywords: | Artificial intelligence;Secret sharing scheme;Cloud computing;Homomorphic encryption;Neural network;Residue number system (RNS) |
| Issue Date: | 2024 |
| Publisher: | Pleiades Publishing |
| Citation: | Shiriaev, E.M., Nazarov, A.S., Kucherov, N.N., Babenko, M.G. Analytical Review of Confidential Artificial Intelligence: Methods and Algorithms for Deployment in Cloud Computing // Programming and Computer Software. - 2024. - 50 (4). - pp. 304-314. - DOI: 10.1134/S0361768824700117 |
| Series/Report no.: | Programming and Computer Software |
| Abstract: | The technologies of artificial intelligence and cloud computing systems have recently been actively developed and implemented. In this regard, the issue of their joint use, which has been topical for several years, has become more acute. The problem of data privacy preservation in cloud computing acquired the status of critical long before the necessity of their joint use with artificial intelligence, which made it even more complicated. This paper presents an overview of both the artificial intelligence and cloud computing techniques themselves, as well as methods to ensure data privacy. The review considers methods that utilize differentiated privacy; secret sharing schemes; homomorphic encryption; and hybrid methods. The conducted research has shown that each considered method has its pros and cons outlined in the paper, but there is no universal solution. It was found that theoretical models of hybrid methods based on secret sharing schemes and fully homomorphic encryption can significantly improve the confidentiality of data processing using artificial intelligence. |
| URI: | https://dspace.ncfu.ru/handle/123456789/28755 |
| Appears in Collections: | Статьи, проиндексированные в SCOPUS, WOS |
Files in This Item:
| File | Description | Size | Format | |
|---|---|---|---|---|
| scopusresults 3149 .pdf Restricted Access | 132.07 kB | Adobe PDF | View/Open | |
| WoS 1922 .pdf Restricted Access | 122.88 kB | Adobe PDF | View/Open |
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