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A new trust management framework based on the experience of users in industrial cloud computing using multi-criteria decision making

Liudmila Ivanovna Khoruzhy (Russian State Agrarian University - Moscow Timiryazev Agricultural Academy, Moscow, Russian Federation)
Roman Petrovich Bulyga (Financial University under the Government of the Russian Federation, Moscow, Russian Federation)
Olga Yuryevna Voronkova (Altai State University, Barnaul, Russian Federation)
Lidia Vladimirovna Vasyutkina (Bauman Moscow State Technical University, Moscow, Russian Federation)
Natalya Ryafikovna Saenko (Moscow Polytechnic University, Moscow, Russian Federation)
Andrey Leonidovich Poltarykhin (Plekhanov Russian University of Economics, Moscow, Russian Federation)
Surendar Aravindhan (Department of Pharmacology, Saveetha Dental College and Hospital, Saveetha Institute of Medical and Technical Sciences, Chennai, India)

Kybernetes

ISSN: 0368-492X

Article publication date: 1 December 2021

Issue publication date: 17 May 2022

247

Abstract

Purpose

Nowadays, cloud platforms are used in many fields, including e-commerce, web applications, data storage, healthcare, gaming, mobile social networks, etc. However, security and privacy are still two significant concerns in this area. The target of this paper is to present a system for trust management in industrial cloud computing using the multi-criteria decision making (MCDM) approach. MCDM techniques have been developed to accommodate a wide range of applications. As a result, hundreds of approaches have been generated with even minor variations on current approaches spawning new study fields.

Design/methodology/approach

Cloud computing provides a fully scalable, accessible and flexible computing platform for various applications. Due to the multiple applications that cloud computing has found in numerous life features, users and providers have considered providing security in cloud communications. Due to its distributive nature, dynamic space and lack of transparency in performing cloud computing, it faces many challenges in providing security. For security improvement, trust management can play a very influential role. This paper proposes a generic analytical methodology that uses a series of assessment criteria to evaluate current trust management testing prototypes in industrial cloud computing and related fields. The authors utilize a MCDM approach in the present article. Due to the multi-dimensionality of the sustainability objective and the complexities of socio-economic and biophysical processes, MCDM approaches have become progressively common in decision-making for sustainable energy.

Findings

The results of comparing and evaluating the performance of this model show its ability to manage trust and the ability to adapt to changes in the behavior of service providers quickly. Using a simulation, all results are confirmed. The results of simulations and evaluation of the present paper indicate that the proposed model provides a more accurate evaluation of the credibility of cloud service providers than other models.

Practical implications

The number of cloud services and customers is vast and extremely competitive in cloud environments, where novel cloud services and customers can join at any time, while others can withdraw whenever they want. Because of cloud services' highly dynamic and dispersed design, trust management mechanisms must be highly flexible to obtain feedback and update trust outcomes as quickly as possible. The model presented in this article tries to improve users' trust in the cloud industry.

Originality/value

Using a method (MCDM) to find the best trust management solution based on user experience in industrial cloud computing is the novelty of this paper.

Keywords

Citation

Khoruzhy, L.I., Petrovich Bulyga, R., Yuryevna Voronkova, O., Vasyutkina, L.V., Ryafikovna Saenko, N., Leonidovich Poltarykhin, A. and Aravindhan, S. (2022), "A new trust management framework based on the experience of users in industrial cloud computing using multi-criteria decision making", Kybernetes, Vol. 51 No. 6, pp. 1949-1966. https://doi.org/10.1108/K-05-2021-0378

Publisher

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Emerald Publishing Limited

Copyright © 2021, Emerald Publishing Limited

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