Please use this identifier to cite or link to this item: https://dspace.ncfu.ru/handle/123456789/29210
Title: Toward Understanding Uncertainty in Fog-Cloud Computing for Big Data Storage and Processing
Authors: Kucherov, N. N.
Кучеров, Н. Н.
Gladkov, A. V.
Гладков, А. В.
Vershkov, N. A.
Вершков, Н. А.
Nazarov, A. S.
Назаров, А. С.
Keywords: Fog computing;Modular arithmetic;Uncertainty
Issue Date: 2024
Publisher: Springer Science and Business Media Deutschland GmbH
Citation: Kucherov N., Gladkov A., Vershkov N., Nazarov A. Toward Understanding Uncertainty in Fog-Cloud Computing for Big Data Storage and Processing // Lecture Notes in Networks and Systems. - 2024. - 1044 LNNS. - pp. 115 - 133. - DOI: 10.1007/978-3-031-64010-0_12
Series/Report no.: Lecture Notes in Networks and Systems
Abstract: Fog computing is currently getting more and more development. But researchers face the challenges of uncertainty, security, and data management in the fog. To solve these problems, re-searchers use various methods. For example, methods of machine learning, orchestration, cryptography, etc. are used. In this paper, we propose a method for solving the confidentiality problem based on modular arithmetic, secret sharing schemes, and homomorphic ciphers. An overview and nature of the arising uncertainties in fog computing is given. Approaches to its reduction are proposed.
URI: https://dspace.ncfu.ru/handle/123456789/29210
Appears in Collections:Статьи, проиндексированные в SCOPUS, WOS

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