Top

Automatic Control and Computer Sciences

Published in:

01-12-2022

Adaptive Control System for Detecting Computer Attacks on Objects of Critical Information Infrastructure

Authors: V. M. Krundyshev, M. O. Kalinin

Published in: Automatic Control and Computer Sciences | Issue 8/2022

Activate our intelligent search to find suitable subject content or patents.

search-config

AI-assisted search

Off

Abstract

This paper presents an adaptive control system for detecting computer attacks in CII based on a neuro-fuzzy analysis of variant cyber-threat spaces and parameters of the protected object using an adaptive neuro-fuzzy inference system (ANFIS) and the Takagi–Sugeno–Kang fuzzy basis. The results of experimental studies have shown that the developed system provides high accuracy and speed of detecting computer attacks in changing decision-making conditions.

previous article Noise-Immune Marking of Digital Audio Signals in Audio Stegosystems with Multiple Inputs and Multiple Outputs

Popov, V.O. and Chechulin, A.A., Investigation of the vulnerabilities distribution in the management systems of critical infrastructure, Inf. Svyaz’, 2021, no. 7, pp. 7–13. https://doi.org/10.34219/2078-8320-2021-12-7-7-13

Petrenko, S.A., Petrenko, A.A., and Kostyukov, A.D., Cyber resilience of digital ecosystems, Zashchita Inf. Insaid, 2021, no. 4, pp. 17–23.

Zima, V.M. and Kryukov, R.O., An approach to controlling the actions of privileged users in critical automated systems, Vopr. Oboronnoi Tekh. Ser. 16: Tekh. Sredstva Protivodeistviya Terrorizmu, 2021, nos. 9–10, pp. 72–82.

Tatarnikova, T.M., Sikarev, I.A., Bogdanov, P.Yu., and Timochkina, T.V., Botnet attack detection approach in IoT networks, Autom. Control Comput. Sci., 2022, vol. 56, no. 8, pp. 838–846.https://doi.org/10.3103/S0146411622080259

Ovasapyan, T.D., Using fuzzy logic to block attacks of internal intruders in WSN, Probl. Inf. Bezop. Komp’yut. Sist., 2019, no. 2, pp. 65–72.

Katasev, A.S., Methods and algorithms of generating the fuzzy models of assessing the objects under condition of uncertainty, Vestn. Tekhnol. Univ., 2019, vol. 22, no. 3, pp. 138–147.

Katasev, A.S., Models and methods of generating fuzzy rules in intelligent systems of state diagnostics of complex objects, Doctoral (Eng.) Dissertation, Kazan, 2014.

Andrievskaya, N.V., Reznikov, A.S., and Cheranev, A.A., Features of application of neuro fuzzy systems in systems of automatic control, Fundam. Issled., 2014, no. 11-7, pp. 1445–1449.

Alekseev, A.S., Methodology of modeling neuro-fuzzy systems, Vestn. Sovrem. Issled., 2019, no. 1.13, pp. 35–40.

10.

Sechenov, M.D. and Shcheglov, S.N., The analysis of informal models of representation of knowledge in decision-making systems, Izv. Yuzhnogo Fed. Univ. Tekh. Nauki, 2010, no. 7, pp. 135–140.

11.

Ivanov, A.S., Mathematical models and algorithms of operation of production knowledge bases, Cand. Sci. (Phys.–Math.) Dissertation, Saratove, 2007.

12.

Avdeenko, T.V. Bakaev, M.A., Hybrid model of knowledge representation for inference realization in frame-based ontology, Nauchn. Vestn. Novosib. Gos. Tekh. Univ., 2013, no. 3, pp. 84–90.

13.

Bolotova, L.S., Sistemy iskusstvennogo intellekta. Modeli i tekhnologii, osnovannye na znaniyakh. Uchebnik (Artificial Intelligence Systems: Knowledge-Based Models and Technologies: Textbook), Moscow: Finansy i Statistika, 2012.

14.

Kotov, E.M., Models of knowledge representation and text representation in form of semantic network, Izv. Taganrogskogo Tekhnol. Univ., 2005, no. 6, pp. 145–147.

15.

Jang, J.-S.R., ANFIS: Adaptive-network-based fuzzy inference system, IEEE Trans. Syst., Man, Cybern., 1993, vol. 23, no. 3, pp. 665–685. https://doi.org/10.1109/21.256541CrossRef

16.

Belenko, V., Krundyshev, V., and Kalinin, M., Synthetic datasets generation for intrusion detection in VANET, SIN ’18: Proc. 11th Int. Conf. on Security of Information and Networks, 2018, p. 9. https://doi.org/10.1145/3264437.3264479

Title: Adaptive Control System for Detecting Computer Attacks on Objects of Critical Information Infrastructure
Authors: V. M. Krundyshev
M. O. Kalinin
Publication date: 01-12-2022
Publisher: Pleiades Publishing
Published in: Automatic Control and Computer Sciences / Issue 8/2022
Print ISSN: 0146-4116
Electronic ISSN: 1558-108X
DOI: https://doi.org/10.3103/S0146411622080090

Springer Professional

Abstract

Please log in to get access to your license.

Other articles of this Issue 8/2022

Counteracting Information Threats Using Honeypot Systems Based on a Graph of Potential Attacks

Detecting Malicious Executable Files Based on Static–Dynamic Analysis Using Machine Learning

Immunization of Complex Networks: Topology and Methods

Methods of Multidimensional Aggregation of Time Series of Streaming Data for Cyber-Physical System Monitoring

Authentication and Key Establishment in WSN Based on Key Predistribution

Botnet Attack Detection Approach in IoT Networks