Improvement of the method for assessing the level of speech information security

Authors

DOI:

https://doi.org/10.15587/1729-4061.2019.185585

Keywords:

digital phonogram, speech intelligibility index, destructive changes of phonemic structure, wavelet transformation

Abstract

Assessment of the level of speech information protection from leakage through acoustic and vibration channels is carried out according to international and national standards and in compliance with regulatory documents. To assess its security level, regulatory documents in many countries imply the use of signal/noise ratio. However, the method has a series of significant shortcomings, which do not make it possible to determine the real state of security level.

The improved objective evaluation method, which is based on determining the coefficient of residual intelligibility for a test-signal after its recovery by the methods of mathematical analysis (adaptive filtration, correlation and spectral analyses, wavelet transformation, etc.) was proposed. The coefficient of residual intelligibility is determined for each word included in a short phrase, a test signal.

The analysis of frequency of using the phonemes in the Ukrainian speech was performed. It was shown that given the definition of the term "allophone" and the number of native speakers, it is possible to assume that the total number of allophones tends to infinity. To reduce the calculation complexity, we proposed the formalized approach based on the simplified linguistic model – a phoneme (a letter), a diphone (two letters), and a triphone (three letters). As a source of information, it is possible to use text documents.

We proposed analytical dependences for calculating the coefficient of residual speech intelligibility and its components – coefficients of frequency of using allophones in the words of the Ukrainian language and the importance of allophone recognition for the word recognition.

The interrelations of the SPC (speech privacy class) and word intelligibility W were shown. On their base, the scale of objective estimation of the degree of speech information privacy on the boundary of the controlled zone by the criterion of residual speech intelligibility was proposed

Author Biographies

Volodymyr Blintsov, Admiral Makarov National University of Shipbuilding Heroiv Ukrainy ave., 9, Mykolayiv, Ukraine, 54025

Doctor of Technical Sciences, Professor

Department of Electronic Engineering of Ship and Robotic Complexes

Sergey Nuzhniy, Admiral Makarov National University of Shipbuilding Heroiv Ukrainy ave., 9, Mykolayiv, Ukraine, 54025

PhD, Associate Professor

Department of Computer Technologies and Information Security

References

  1. Normatyvnyi dokument systemy tekhnichnoho zakhystu informatsiyi ND TZI 2.4-010-2015.
  2. Normatyvnyi dokument systemy tekhnichnoho zakhystu informatsiyi ND TZI 2.3-019-2015.
  3. Normatyvnyi dokument systemy tekhnichnoho zakhystu informatsiyi ND TZI 2.2-008-2015.
  4. ASTM E2638-10. ASTM Intl., West Conshohocken, PA.
  5. ANSI/ASA S3.37-1987 (R2017) American National Standard Preferred Earhook Nozzle Thread for Postauricular Hearing Aids. STANDARD by American National Standards of the Acoustical Society of America, 1987.01.01.
  6. ANSI/ASA S3.5-1997 (R2017) American National Standard Methods for Calculation of the Speech Intelligibility Index. STANDARD by American National Standards of the Acoustical Society of America, 1997.01.01.
  7. ISO 9921:2003. Ergonomics – Assessment of speech communication (2003). International Organization for Standardization, 28. Available at: https://www.iso.org/standard/33589.html
  8. IEC 60268-16:2011. Sound system equipment – Part 16: Objective rating of speech intelligibility by speech transmission index. Available at: https://webstore.iec.ch/publication/1214
  9. ISO 7240-24:2010. Fire detection and fire alarm systems – Part 24: Sound-system loudspeakers (2010). International Organization for Standardization, 39.
  10. UNE EN 60268-16:2011. Sound system equipment – Part 16: Objective rating of speech intelligibility by speech transmission index (Endorsed by AENOR in November of 2011).
  11. ISO 3382 (2012). Acoustics – Measurement of room acoustics parameters – Part 3: Open plan offices.
  12. Grigoriev, I. A., Kazanovski, A. I. (2010). Methodical approach to efficiency evaluation of voice data protection. Vestnik Voronezhskogo gosudarstvennogo tehnicheskogo universiteta, 5, 133–136.
  13. Nuzhnyy, S. M. (2018). Improved technology of evaluation of stage of protection of license information. Modern Information Security, 1 (33), 66–73. Available at: http://journals.dut.edu.ua/index.php/dataprotect/article/view/1796
  14. Blintsov, V., Nuzhniy, S., Parkhuts, L., Kasianov, Y. (2018). The objectified procedure and a technology for assessing the state of complex noise speech information protection. Eastern-European Journal of Enterprise Technologies, 5 (9 (95)), 26–34. doi: https://doi.org/10.15587/1729-4061.2018.144146
  15. Hornsby, B. W. Y. (2004). The Speech Intelligibility Index. The Hearing Journal, 57 (10), 10–17. doi: https://doi.org/10.1097/00025572-200410000-00003
  16. Allen, J. B. (2005). Consonant recognition and the articulation index. The Journal of the Acoustical Society of America, 117 (4), 2212–2223. doi: https://doi.org/10.1121/1.1856231
  17. Phatak, S. A., Lovitt, A., Allen, J. B. (2008). Consonant confusions in white noise. The Journal of the Acoustical Society of America, 124 (2), 1220–1233. doi: https://doi.org/10.1121/1.2913251
  18. Lee, P. J., Jeon, J. Y. (2011). Evaluation of speech transmission in open public spaces affected by combined noises. The Journal of the Acoustical Society of America, 130 (1), 219–227. doi: https://doi.org/10.1121/1.3598455
  19. Graetzer, S., Hopkins, C. (2018). Evaluation of STOI for speech at low signal-to-noise ratios after enhancement with Ideal Binary Masks. Conference: 25th International Congress on Sound and Vibration.
  20. Bradley, J. S., Gover, B. N. (2010). A new system of speech privacy criteria in terms of Speech Privacy Class (SPC) values. Proceedings of 20th International Congress on Acoustics. Sydney. Available at: https://nrc-publications.canada.ca/eng/view/accepted/?id=cf69d165-7fb1-46c9-b60f-e6c8020b0c11
  21. Bradley, J., Gover, B. (2008). Speech privacy class for rating the speech privacy of meeting rooms. Canadian Acoustics, 36 (3), 22–23. Available at: https://jcaa.caa-aca.ca/index.php/jcaa/article/view/2018
  22. Horev, A. A. (2009). Otsenka vozmozhnostey sredstv akusticheskoy (rechevoy) razvedki. Spetsial'naya tehnika, 4, 49–63.
  23. Rybal'skiy, O. V., Solov'ev, V. I., Zhuravel', V. V. (2017). Fraktal'niy podhod k viyavleniyu sledov tsifrovoy obrabotki v analogovyh fonogrammah. Suchasna spetsialna tekhnika, 1, 4–9. Available at: http://nbuv.gov.ua/UJRN/sstt_2017_1_4
  24. Solovyov, V., Rybalsky, O., Zheleznyak, V. (2014). Multifrаktal structure of whisper and recognition of speech structures. Vestnik Polotskogo gosudarstvennogo universiteta. Seriya C, Fundamental'nye nauki, 12, 16–20. Available at: http://elib.psu.by:8080/handle/123456789/11215
  25. Vakulenko, M. O. (2010). Akustychni invarianty ukrainskykh pryholosnykh. Naukovyi visnyk kafedry YuNESKO Kyivskoho natsionalnoho linhvistychnoho universytetu. Filolohiya, pedahohika, psykholohiia, 20, 4–16. Available at: http://nbuv.gov.ua/UJRN/Nvkyu_2010_20_3
  26. Dobrushkin, H. O., Danylov, V. Ya. (2010). Osnovni pidkhody do rozpiznavannia movlennievoi informatsiyi (Chastyna 1). Visnyk Vinnytskoho politekhnichnoho instytutu, 4, 50–64. Available at: https://visnyk.vntu.edu.ua/index.php/visnyk/article/view/1746
  27. Arkhypova, O. O., Zhuravlov, V. M., Kumeiko, V. M. (2009). Artykuliatsiyni tablytsi sliv ukrainskoi movy. Pravove, normatyvne ta metrolohichne zabezpechennia systemy zakhystu informatsiyi v Ukraini, 2 (19). 13–17. Available at: http://ela.kpi.ua/handle/123456789/9689
  28. Arkhypova, O. O., Zhuravlov, V. M. (2009). Chastotnyi analiz vykorystannia bukv ukrainskoi movy. Radio Electronics, Computer Science, Control, 2, 53–56. Available at: http://ric.zntu.edu.ua/issue/viewIssue/1582/pdf_11
  29. Sushko, S. O., Fomychova, L. Ya., Barsukov, Ye. S. (2010). Chastoty povtoriuvanosti bukv i bihram u vidkrytykh tekstakh ukrainskoiu movoiu. Ukrainian Information Security Research Journal, 12 (3 (48)). doi: https://doi.org/10.18372/2410-7840.12.1968
  30. Babenko, T. V., Sushko, S. O. (2012). About an entropy of Ukrainian language. Ukrainian Information Security Research Journal, 14 (3 (56)), 104–107. doi: https://doi.org/10.18372/2410-7840.14.3397
  31. Kulchytskyi, I. M., Shandruk, U. S. (2015). Vplyv orfohrafiyi na chastotu bukv u tekstakh. Visnyk Natsionalnoho universytetu "Lvivska politekhnika". Informatsiyni systemy ta merezhi, 814, 300–309. Available at: http://nbuv.gov.ua/ujrn/vnulpicm_2015_814_30
  32. Nuzhnyi, S. M., Zanoskina, P. V. (2018). General Approaches to the Formation of Articulation Tables of the Ukrainian Language to Assess the State of Protection of Excessive-Noise Speech Information. Suchasna spetsialna tekhnika, 4 (55), 66–75. Available at: http://suchasnaspetstehnika.com/journal/ukr/2018_4.pdf

Downloads

Published

2019-12-02

How to Cite

Blintsov, V., & Nuzhniy, S. (2019). Improvement of the method for assessing the level of speech information security. Eastern-European Journal of Enterprise Technologies, 6(9 (102), 28–38. https://doi.org/10.15587/1729-4061.2019.185585

Issue

Section

Information and controlling system