Numerically-analytical solution of problem gaming confrontation hardware-redundant dynamic system with the enemy operating in conditions of incomplete information about the behavior of participants in the game

Potapov, V. I.; Shafeeva, O. P.; Doroshenko, M. S.; Chervenchuk, I. V.; Gritsay, A. S.

doi:10.1088/1742-6596/1050/1/012062

Cited by 7 publications

(2 citation statements)

References 4 publications

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“…Requests are initiated by the client, and responses are generated by the server. There is an important need for developing models of distributed information systems in stationary conditions and under the influence of external factors that increase the failure rate of component systems [ 43 , 44 ].…”

Section: System Modelmentioning

confidence: 99%

Hash and Physical Unclonable Function (PUF)-Based Mutual Authentication Mechanism

Bhatia

Pandey

Singh

et al. 2023

Sensors

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The security of web applications in an enterprise is of paramount importance. To strengthen the security of applications, the identification and mitigation of vulnerabilities through appropriate countermeasures becomes imperative. The Open Web Application Security Project (OWASP) Top 10 API Security Risks, 2023 Edition, indicates the prominent vulnerabilities of API security risks. Broken authentication, however, is placed in second position with level-3 exploitability, level-2 prevalence, level-3 detectability, and level-3 technical impact. To mitigate this vulnerability, many mitigation strategies have been proposed by using the cryptographic primitives wherein two techniques, namely hashing and PUF, are used. Some of the proposals have integrated the concepts of hashing and PUF. However, the unnecessarily lengthy and complex mathematics used in these proposals makes them unsuitable for current API-based application scenarios. Therefore, in this paper, the authors propose a privacy-preserving authentication protocol that incorporates the capability of both mechanisms in an easy and low-complexity manner. In addition to overcoming existing limitations, the proposed protocol is tested to provide more security properties over existing schemes. Analysis of their performance has demonstrated that the proposed solutions are secure, efficient, practical, and effective for API-based web applications in an enterprise environment.

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Section: System Modelmentioning

confidence: 99%

Hash and Physical Unclonable Function (PUF)-Based Mutual Authentication Mechanism

Bhatia

Pandey

Singh

et al. 2023

Sensors

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“…In this context, the ability to predict and preemptively address LAN failures is a paramount concern for network administrators and IT professionals. Studies conducted by Positive Technologies, as cited in references [1,2], indicate an 11% rise in incidents (encompassing attacks and network equipment failures) in the first half of 2019 compared to the same period in 2018 [3]. This suggests that the information systems of organizations from 2019 did not witness a reduction in their susceptibility to failures.…”

Section: Introductionmentioning

confidence: 99%

Enhancing LAN Failure Predictions with Decision Trees and SVMs: Methodology and Implementation

Rzayeva,

Myrzatay,

Abitova

et al. 2023

Electronics

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Predicting Local Area Network (LAN) equipment failure is of utmost importance to ensure the uninterrupted operation of modern communication networks. This study explores the use of machine learning algorithms to enhance the accuracy of equipment failure prediction in LAN environments. Using these algorithms to enhance LAN failure predictions involves collecting and analyzing network data, such as packet loss rates and latency, to identify patterns and anomalies. These algorithms can then predict potential LAN failures by recognizing early warning signs and deviations from normal network behavior. By leveraging machine learning, network administrators can proactively address issues, reduce downtime, and improve overall network reliability. In our study, two powerful machine learning algorithms—decision tree and support vector machine (SVM)—are used. To evaluate the effectiveness of the proposed models, a comprehensive dataset comprising various LAN equipment parameters and corresponding failure instances is utilized. The dataset is pre-processed to handle missing values and normalize features, ensuring the algorithms’ optimal performance. Performance metrics, such as accuracy, precision, recall, and F1-score, are employed to assess the predictive capabilities of the models. The excremental results of our study lead to more reliable and stable network operations by allowing early detection of potential issues and preventive maintenance. This leads to reduced downtime, improved network performance, and enhanced overall user satisfaction. They demonstrate the efficacy of both decision tree and SVM algorithms in accurately predicting LAN equipment failure.

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Fault-tolerance model of the information systems

Potapov

Goleva

Storozhenko

et al. 2019

J. Phys.: Conf. Ser.

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Numerically-analytical solution of problem gaming confrontation hardware-redundant dynamic system with the enemy operating in conditions of incomplete information about the behavior of participants in the game

Cited by 7 publications

References 4 publications

Hash and Physical Unclonable Function (PUF)-Based Mutual Authentication Mechanism

Hash and Physical Unclonable Function (PUF)-Based Mutual Authentication Mechanism

Enhancing LAN Failure Predictions with Decision Trees and SVMs: Methodology and Implementation

Fault-tolerance model of the information systems

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