№1, 2023


Ramiz H. Shikhaliyev

The size and complexity of computer networks (CNs) are constantly increasing, which requires the intellectualization of network monitoring. Undoubtedly, intellectualization will increase the effectiveness of monitoring the CNs. To ensure the intellectualization of the CNs monitoring, it is necessary to use machine learning (ML) methods. The use of ML methods enables to create an intelligent monitoring system. This article proposes a conceptual model of a system for CNs intelligent monitoring. The model is based on the analysis of log files using ML methods. The proposed model will make it possible to monitor the CNs in a targeted manner, which can increase the efficiency of network monitoring and management in terms of the use of network resources (pp.23-28).

Keywords: Computer networks, intelligent monitoring, log file analysis, machine learning
  • Shikhaliyev R. H. (2022). A method for intelligent planning of computer networks monitoring  Problems of Information Technology, 13(1), 42-48. http://doi.org/10.25045/ jpit.v13.i1.05
  • Abdalla R. R. and Jumaa A.K. (2022). Log File Analysis Based on Machine Learning: A Survey. UHD Journal of Science and Technology, 6(2), 77-84. https://doi.org/10.21928/uhdjst.v6n2y2022.pp77-84
  • Brandao A. and Georgieva P. (2020). Log Files Analysis for Network Intrusion Detection, Proceedings of 2020 IEEE 10th International Conference on Intelligent Systems, pp. 328-333. https://doi.org/10.1109/IS48319.2020.9199976
  • Mandagondi L. G. (2021). Anomaly Detection in Log Files Using Machine Learning Techniques, Master of Science in Computer Science, Faculty of Computing, Blekinge Institute of Technology.
  • Kobayashi S., Fukuda K., Esaki H. (2017). Mining causes of network events in log data with causal inference, 2017 IFIP/IEEE International Symposium on Integrated Network Management (IM2017), pp. 45-53. https://doi.org/10.23919/INM.2017.7987263
  • Dasgupta D. and Gonzalez F. A. (2001). An Intelligent Decision Support System for Intrusion Detection and Response, Proceedings of the International Workshop on Information Assurance in Computer Networks: Methods, Models, and Architectures for Network Security, 2001, https://doi.org/10.1007/3-540-45116-1_1
  • Mohammed A. R., Mohammed S. A., Côté D., and Shirmohammad S. (2021). Machine Learning-Based Network Status Detection and Fault Localization, IEEE Transactions on instrumentation and measurement, 70,  3521710, https://doi.org/10.1109/TIM.2021.3094223
  • Kotenko I., Saenko I., and Skorik F. (2020). Intelligent support for network administrator decisions based on combined neural networks. In 13th International Conference on Security of Information and Networks (SIN 2020), November 04–07, 2020, Merkez, Turkey. ACM, New York, NY, USA, 8 pages. https://doi.org/10.1145/3433174.3433602
  • Mirzaraxmedova A.X. and Fozilova M.M. (2019). Analysis of Prospects of Technology of Intelligent Monitoring Systems, International Conference on Information Science and Communications Technologies (ICISCT). https://doi.org/ 10.1109/ICISCT47635.2019.9011845
  • He P., Zhu J., He S., Li J. and Lyu M.R. (2016). An Evaluation Study on Log Parsing and Its Use in Log Mining, 46th Annual IEEE/IFIP International Conference on Dependable Systems and Networks, pp. 654-661. https://doi.org/ 10.1109/DSN.2016.66