Development of a Software System to Ensure the Reliability and Fault Tolerance in Information Systems Based on Expert Estimates

Critical information infrastructure exists in different sectors of each country. Its loss or sustainability violation will lead to a negative impact on the supply of essential services, as well as on the social or economic well-being of the population. It also may even pose a threat to people’s health and lives. In the modern world, such infrastructure is more vulnerable and unstable than ever, due to rapid technological changes, and the emergence of a new type of threat—information threats. It is necessary to determine which infrastructure are of crucial importance when decision-makers aim to achieve the reliability of essential infrastructure. This article aims to solve the problem of ensuring the sustainable development of EU countries in terms of identifying critical information infrastructures. Integrated multi-criteria decision-making techniques based on fuzzy WASPAS and AHP methods are used to identify essential information infrastructures, which are related to a new type of potential threat to national security. The paper proposes a model for identifying critical information infrastructures, taking into account the sustainable development of countries.

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“…A new type of risk has appeared, such as terrorist attacks, cyber-attacks, cyber wars, etc. [56][57][58].…”

Section: Achieving the Sustainability Of CII And Potential Threats Tmentioning

confidence: 99%

A Fuzzy WASPAS-Based Approach to Determine Critical Information Infrastructures of EU Sustainable Development

et al. 2019

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“…The sensors, actuators, and internal components of the system can all fail, as can the network communication links between the system nodes. Once an accident occurs, it will cause huge losses and material losses, and even lead to catastrophic accidents [3][4].…”

Section: Introductionmentioning

confidence: 99%

Fault Tolerant Control of Distributed System Based on Neural Network

2020

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Neural networks are very promising in the design and control of distributed systems due to their powerful computing power, learning and adaptive capabilities, and distributed capabilities. The purpose of this work is to study fault-tolerant control of distributed systems based on neural networks. For nonlinear systems with actuator failures, fault-tolerant control based on a small portion of the network is required. By combining error tracking and forecasting methods to build performance metrics and reduced fault-tolerant systems, this translates into a control problem. The PSO algorithm is introduced to train the judgment neural network, which avoids the selection of the initial vector and improves the training success rate to a certain extent. To mitigate the effects of actuator errors, a neural network error observer is designed to estimate and compensate for errors. Finally, the effectiveness of the proposed fault-tolerant supervisory control method is proved by an example simulation.

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“…The rapid development of the IT sector leads to accelerated application and introduction of digital innovations, including blockchain technologies, open data, robotization and artificial intelligence, biometric authentication, crowdfunding, big data, etc. Digital technology development raises the need to increase the level of information security and reliability of implemented technologies (Boranbayev et al, 2018b). It is well known that modern society is becoming increasingly dependent on information technology, its continuous and trouble-free operation, respectively, on its reliability and security (Boranbayev et al, 2018a).…”

Section: Introduction and Problem Statementmentioning

confidence: 99%

Information Security Risk Assessment in Critical Infrastructure: A Hybrid MCDM Approach

et al. 2019

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The risk analysis has always been one of the essential procedures for any areas. The majority of security incidents occur because of ignoring risks or their inaccurate assessment. It is especially dangerous for critical infrastructures. Thus, the article is devoted to the description of the developed model of risk assessment for the essential infrastructures. The goal of the model is to provide a reliable method for multifaceted risk assessment of information infrastructure. The purpose of the article is to present a developed model based on integrated MCDM approaches that allow to correctly assess the risks of the critical information infrastructures.

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Development of a Software System to Ensure the Reliability and Fault Tolerance in Information Systems Based on Expert Estimates

Cited by 19 publications

References 8 publications

A Fuzzy WASPAS-Based Approach to Determine Critical Information Infrastructures of EU Sustainable Development

A Fuzzy WASPAS-Based Approach to Determine Critical Information Infrastructures of EU Sustainable Development

Fault Tolerant Control of Distributed System Based on Neural Network

Information Security Risk Assessment in Critical Infrastructure: A Hybrid MCDM Approach

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