A METHOD FOR USER AUTHENTICATING TO CRITICAL INFRASTRUCTURE OBJECTS BASED ON VOICE MESSAGE IDENTIFICATION

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DOI: https://doi.org/10.20998/2522-9052.2020.3.02
Keywords:
biometric identification, identification by voice, authentication by voice message, information protection, unauthorized access, cyber security

Main Article Content

Vasyl Trysnyuk
Institute of Telecommunications and Global Information Space of the National Academy of Sciences of Ukraine, Kyiv
https://orcid.org/0000-0001-9920-4879
Yevhen Nagornyi
Institute of Telecommunications and Global Information Space of the National Academy of Sciences of Ukraine, Kyiv
https://orcid.org/0000-0001-5902-9295
Kirill Smetanin
Korolov Zhytomyr Military Institute, Zhytomyr
https://orcid.org/0000-0002-6062-550X
Igor Humeniuk
Korolov Zhytomyr Military Institute, Zhytomyr
https://orcid.org/0000-0001-5853-3238
Tetyana Uvarova
National University of Defense of Ukraine named after Ivan Chernyakhovsky, Kyiv
https://orcid.org/0000-0002-5807-2563

Abstract

The subject of the research is the protection of critical infrastructure objects from unauthorized access based on voice message identification. The purpose of the research is to consider the main methods and algorithms for identifying an individual by voice, as well as the development of a software implementation of the restricted zone access control system, which allows improving the security of the standard password system by introducing voice authorization technologies and improving the algorithm for selecting voice fragments in audio files. Therefore, the purpose determines following tasks: analysis of the advantages and disadvantages of existing methods of information protection to infrastructure objects; determination of the optimal method of identification by voice message; a description of the main features of the implementation and use of Mel-frequency kastelnik coefficients (MFKC). Are used such methods: system approach, system analysis, theory of algorithms. The following results were obtained: an algorithm was developed for storing users ' voice data for further use in authorization, the voice authorization subsystem; the corresponding software of the computer system has been developed. Conclusions: based on the example of applying the biometric method of user authentication to critical infrastructure objects based on voice message identification, this method of user authentication should be used as an additional method of multi-factor authentication by entering an additional password or another method of biometric user authentication.

Article Details

How to Cite
Trysnyuk, V., Nagornyi, Y., Smetanin, K., Humeniuk, I., & Uvarova, T. (2020). A METHOD FOR USER AUTHENTICATING TO CRITICAL INFRASTRUCTURE OBJECTS BASED ON VOICE MESSAGE IDENTIFICATION. Advanced Information Systems, 4(3), 11–16. https://doi.org/10.20998/2522-9052.2020.3.02
Issue
Vol. 4 No. 3 (2020): Advanced Information Systems
Section
Identification problems in information systems
Author Biographies

Vasyl Trysnyuk, Institute of Telecommunications and Global Information Space of the National Academy of Sciences of Ukraine, Kyiv

Doctor of Technical Sciences, Senior Researcher, Head of the environmental research department

Yevhen Nagornyi, Institute of Telecommunications and Global Information Space of the National Academy of Sciences of Ukraine, Kyiv

postgraduate student

Kirill Smetanin, Korolov Zhytomyr Military Institute, Zhytomyr

PhD (Technical), lecturer at the Department of Information Security and Cybersecurity

Igor Humeniuk, Korolov Zhytomyr Military Institute, Zhytomyr

PhD (Technical), Senior lecturer at the Department of Information Security and Cybersecurity

Tetyana Uvarova, National University of Defense of Ukraine named after Ivan Chernyakhovsky, Kyiv

Researcher

References

(2015), The concept of creating a national system of identification of citizens of Ukraine, foreigners and stateless persons, Order of the Cabinet of Ministers of Ukraine № 1428-2015-r dated 23.12.2015, available at:

https://zakon.rada.gov.ua/laws/main/1428-2015-%D1%80.

Bugaenko, H. and Gorbenko, I. (2012), “Analysis of three biometric methods of identity authentication”, Applied Radio Electronics, Vol. 11, No. 2, pp. 262-266.

Tsarev, R. and Lemekha, T. (2016), Biometric technologies, textbook, ONAZ, Odessa, 140 p.

Moroz, A. (2011), “Biometric technologies of human identification. System overview”, Mathematical machines and systems, No. 1, pp. 39-45.

(2020), Chalk-frequency keptral coefficients, available at: http://poisk-ru.ru/s62453t2.html.

Bidyuk, P. and Bondarchuk, V. (2009), “Modern methods of biometric identification”, Legal, regulatory and metrological support of information security in Ukraine, No. 1 (18), pp. 137-146.

Lalit R., Bahl, Peter F., Brown, Peter V., de Souza and Robert L., Mercer (1987), “Speech Recognition With Continuous Parameter Hidden Markov Models”, Proceedings of the International Conference on Acoustics. Speech and Signal Processing, Vol. 2, Issues 3-4, September–December 1987, IEEE, New York, pp. 219-234.

Viola, P. and Jones, M. (2001), “Rapid object detection using a boosted cascade of simple features”, IEEE Conf. on Computer Vision and Pattern Recognition, Vol. 1, pp. 511-518.

Smetanin, K., Humeniuk I. and Nekrylov A. (2020), “Protection from unauthorized access to information and telecommunication systems through biometric user identification”, Proceedings of the International Scientific and Technical Conference "PERSPECTIVES OF TELECOM, available at: http://conferenc.its.kpi.ua/proc/article/view/200915.

Campbell, J.P. (1997), “Speaker Recognition: A Tutorial”, Proceedings of the IEEE, Vol. 85, No. 9, pp. 1437-1462.

Ing-Jr, Ding, Chih-Ta, Yen and Yen-Ming, Hsu (2013), “Development so Machine Learning Schemes for 135 Dynamic Time-Wrapping-Based Speech Recognition”, Mathematical Problems in Engineering, Vol. 2, pp. 35-42.

Voronov A.A. (1983), Methods of automatic speech recognition, Vol. 1, MIR, Moscow, 328 p.

Trysnyuk, V., Demydenko, O., Smetanin, K. and Zozulia, A. (2020), “Improvement of the complex evaluation method of vital activity risks”, European Association of Geoscientists & Engineers, Geoinformatics: Theoretical and Applied Aspects 2020, May 2020, Vol. 2020, pp. 1-5, DOI: https://doi.org/10.3997/2214-4609.2020geo071.

Smetanin, K., Litvinenko, A. and Kostenko, D. (2019), “Biometric authentication of users based on voice signals in cyberspace”, Problems of theory and practice of information confrontation in the conditions of hybrid wars, scientific-practical. Conf., Oct. 24–25. 2019, ZhVI, Zhytomyr, pp. 205-207.