Research Information Security and Reliability Critical Infrastructure Control Systems

Abstract:

The effectiveness of the functioning communication management systems with the information security system is analyzed on the example critical information infrastructure objects. Based on the study, a new approach is proposed to obtain analytical estimates security and reliability indicators hardware and software complexes critical information infrastructure management systems. The given formulas for calculating the intensities of the states telecommunication systems allow to expand the number indicators information security and reliability functioning, if necessary.

• Periodical: Engineering Headway (Volume 7)
• Pages: 127-133
• DOI: https://doi.org/10.4028/p-S0qXYI
• Online since: April 2024
• Authors: Iltimas Mammadov, Ulfat Sadigov*
• Keywords: Control, Dangerous, Failure Rate, Information Security, Network Attacks, Probability Uptime, Safe Failures

References

[1] S.D. Erokhin, A.N. Petukhov, P.L. Pilyugin, Security management critical information infrastructures. M.: Hotline - Telecom, 2021.

[2] B.G. Ibrahimov, T. G. Mamedov, Study of the characteristics information protection of a telecommunication system and control of an important object in critical infrastructures. All- Russian Scientific and Technical Corporation "Telecommunication and Computing Systems". MTUSI, Moscow, 2021. p.170–173.

[3] R.Chaudhary, A.Jindal, G.S. Aujla, S.Aggarwal, N.Kumar, Blockchain-based secure energy trading in SDN-enabled intelligent transportation system. Computers & Security. 2019. p.288 –299.

DOI: 10.1016/j.cose.2019.05.006

[4] Huang X., Xu C., Wang P., Liu H, LNSC: A Security Model for Electric Vehicle and Charging Pile Management Based on Blockchain Ecosystem. IEEE Access, Vol.6, 2018. p.13565–3574.

DOI: 10.1109/access.2018.2812176

[5] Mikhailov V.S., Yurkov N.K. Integral estimates in reliability theory. Introduction and main results M.: Tekhnosphere, 2020.

[6] M.Aljabri, S.S. Aljameel, R.M.A. Mohammad, S.H. Almotiri, S.Mirza, F.M. Anis, M.Aboulnour, D.M. Alomari, D.H. Alhamed, H.S. Altamimi, Intelligent Techniques for Detecting Network Attacks: Review and Research Di rections. Sensors 2021, 21, 7070, URL:.

DOI: 10.3390/s21217070

[7] D.Gumuşbaş, T.Yıldırım, A.Genovese, F. Scotti, A Comprehensive Survey of Databases and Deep Learning Methods for Cybersecurity and Intrusion Detection Systems, in IEEE Systems Journal, vol. 15, no. 2, 2021, pp.1717-1731, URL: https://doi.org/10.1109/JSYST. 2020.2992966

DOI: 10.1109/jsyst.2020.2992966

[8] P.Mishra, V.Varadharajan, U.Tupakula, E. S. Pilli, A detailed investigation and analysis of using machine learning techniques for intrusion detection, IEEE Commun. Surveys Tuts., vol. 21, no. 1, 2019, p.686–728.

DOI: 10.1109/comst.2018.2847722

[9] S.Erokhin, B.Borisenko, A.Fadeev, Reducing the dimension of input data for ids by using match analysis, 28th Conference of Open Innovations Association (FRUCT), Moscow, Russia, 2021, pp.96-102, URL:.

DOI: 10.23919/FRUCT50888.2021.9347629

[10] I.Sharafaldin, A.Gharib, A.H. Lashkari, A.A. Ghorbani, Towards a reliable intrusion detection benchmark dataset. Software Networking, 2018(1), p.177–200, URL:

DOI: 10.13052/jsn2445-9739.2017.009