Trends and Risks of Network Technologies

Syuntyurenko, O. V.; Gilyarevskii, R. S.

doi:10.3103/s0147688221020088

Cited by 6 publications

(4 citation statements)

References 5 publications

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“…An obvious outcome of this development is the proliferation of various risks and threats to people and societies, both in terms of quality and quantity which in turn would demonstrably bring about the growth and development of a range of threats pertaining to information integrity. There is a high degree of possibility that the creation of different kinds of risks and the growth in the number of threats pertaining to information security would continue to result in larger and many more challenges due to factors such as the development and expansion of telecommunications network across the globe, the embracing and implementation of various novel network technologies, and the growth and expansion of semantic Internet and popular media [2].…”

Section: Figure 1: Worldwide Market For Networking Hardwarementioning

confidence: 99%

Enhancing Supply Chain Efficiency to Build Next-Gen Artificial Intelligence (AI)/Machine Learning Network Through Al-Driven Forecasting

Krishnan,

Khastgir

2024

IJSCM

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The networking hardware industry is characterized by unique challenges when it comes to supply chain management. These include unpredictable demand patterns, complex logistics, besides disruptions caused by rapid technological advancements. This paper explores the integration of artificial intelligence (AI) into forecasting methodologies to enhance supply chain efficiency within the sector. Application of AI-driven forecasting models can help organizations improve demand predictions, refine inventory management, and streamline logistical operations. Drawing on recent research and industry practices, this article highlights the transformative impact of AI on supply chain efficiency and offers insights into best implementation practices. Furthermore, the research investigates the intersection of AI and networking hardware supply chain management, focusing on leveraging AI to analyze hardware failure patterns and interpret hardware-generated alarms and interrupts. By harnessing analytical capabilities of AI, modern organizations can extract actionable insights to reduce failure rates and enhance supply chain forecasting accuracy. This innovative approach enables more effective anticipation and preparation for hardware failures, optimizing spare part inventory management and minimizing the need for costly return merchandise authorizations (RMAs).

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Section: Figure 1: Worldwide Market For Networking Hardwarementioning

confidence: 99%

Enhancing Supply Chain Efficiency to Build Next-Gen Artificial Intelligence (AI)/Machine Learning Network Through Al-Driven Forecasting

Krishnan,

Khastgir

2024

IJSCM

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“…A fundamental uncertainty is associated with the processes of formation of a new technological order based on information technologies, since, first, society is simply not ready for such a large-scale expansion of the limits of the possible and, secondly, already obvious opportunities also entail dangerous consequences, most of which still belong to the realm of ignorance. We should note the increasing relevance of studies on the negative consequences of scientific, technical and industrial development, as the problem of minimizing the risks of introducing new technologies is part of a more general problem of social and scientific technological development [ 4 – 9 ]. Modern ideas on risk are diverse (especially in the financial and economic spheres) [ 10 ].…”

Section: Negative Trends In Information Technology Developmentmentioning

confidence: 99%

Predicting Potential Threats and Megarisks in Information Technology Development

Syuntyurenko

2022

Sci. Tech. Inf. Proc.

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This paper considers the methodological aspects of forecasting the emergence of threats and risks relating to the development of information technologies on the basis of a multicriterion analysis of human interaction with the information environment, as well as problems of information security of a person and society, taking into account the influence of factors such as the globalization of the world economy and the formation of a new technological structure. Informatization, convergence of computer, telecommunication technologies, and multimedia provide a fundamentally new level of civilizational development, increasingly influencing the life of a person and society. From the point of view of a systemic approach, the application of scientific metrics and multidimensional analysis methods, the causal relationships of the emergence of the most dangerous and significant threats and risks of the implementation of information technologies for the economy and society as a whole are investigated. Some conclusions, priorities, and the most urgent tasks of developing an interdisciplinary problem of forecasting the assessment and minimizing risks of information technology development are formulated.

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“…Network technologies (NTs) are being widely used in many applications. NTs mainly use data systems to manage and deliver digital resources through a computer network built specifically for a particular sector (Syuntyurenko and Gilyarevskii, 2021). Various industries currently use computer hardware and system software that maintain NTs.…”

Section: Introductionmentioning

confidence: 99%

“…Various industries currently use computer hardware and system software that maintain NTs. However, with the rapid development of information technology, the application scope of NTs has gradually expanded, especially for the emerging fields (cloud computing and big data) (Syuntyurenko and Gilyarevskii, 2021). The rise of NTs has greatly facilitated the stakeholders' engagement and brought solid support for enterprise development and national progress (Charwand and Gitizadeh, 2018;Rinalini and Prakash, 2018).…”

Section: Introductionmentioning

confidence: 99%

Performance Verification of Bayesian Network–Based Security Risk Management and Control System for Power Trading Institutions

Kong¹,

Lin²,

Sheng³

et al. 2022

Front. Energy Res.

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Risk in power trading is unavoidable for various reasons. The impact of this risk would vary based on the trading characteristics that mainly depend on the market design and power purchase agreements. So, a security risk management and control system for power trading institutions based on a Bayesian network is designed to reduce the risk of power trading projects. As a part of the network, we first provided the overall architecture of the risk management and control system, which includes a malicious network behaviour detection module, controller selection module, data transmission module, and management and control result visualisation module. Second, the hardware test design was implemented by analysing each module’s working principle and function. Based on the hardware design of the system, the regression analysis method is used to evaluate the risk of power transactions, followed by market fluctuation prediction to obtain the prediction result induced risks. The relationship between security risks and risk-influencing factors is analysed using the Bayesian network. The initial list of risks is established, the uncertain risk factors are reasoned, and the security risk management and control model of power trading institutions is tested to achieve the goal of risk management and control. The experimental results show that this method’s risk management and control efficiency are high. At the same time, this method effectively realised comprehensive risk identification by reducing the loss to power enterprises and has near-practical application value.

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Trends and Risks of Network Technologies

Cited by 6 publications

References 5 publications

Enhancing Supply Chain Efficiency to Build Next-Gen Artificial Intelligence (AI)/Machine Learning Network Through Al-Driven Forecasting

Enhancing Supply Chain Efficiency to Build Next-Gen Artificial Intelligence (AI)/Machine Learning Network Through Al-Driven Forecasting

Predicting Potential Threats and Megarisks in Information Technology Development

Performance Verification of Bayesian Network–Based Security Risk Management and Control System for Power Trading Institutions

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