Quality Analysis of Matrix Masking of Digital Audio Data
https://doi.org/10.31854/1813-324X-2023-9-3-6-13
Abstract
This article considered the guarantee of confidentiality task of audio information transmitted over a packet communication channel. Domain analysis showed, that in most cases cryptographical method used for guarantee of confidentiality of audio information, however, along with them, matrix methods of protective coding used, with implementation on FPGA or DSP processors. These methods, using random matrices, impose additional instrumental errors during decoding. The purpose of the study: is to assess the quality of protective coding ‒ masking of audio data by quasi-orthogonal structured matrices. The proposed method of masking digital audio information by quasi-orthogonal matrices differs from the known ones in predictable results and simplity of implementation. An alternative approach to the classical use of metrics is proposed for evaluating the result of masking. It is based on the analysis of the spectral component of the signal. It is shown that masking with a square Mersenne ‒ Walsh matrix brings digital audio information, presented in the form of a matrix, to a form close in spectrum to white noise. This reliably protects it in the communication channel from unauthorized access. The obtained results showed that the proposed method is promising and suggests the study of the influence of the choice of orthogonal matrix structures and their sizes on the results of masking.
Supporting agencies: The paper was prepared with the financial support of the Ministry of Science and Higher Education of the Russian Federation, grant agreement No. FSRF-2023-0003, “Fundamental principles of building of noise-immune systems for space and satellite communications, relative navigation, technical vision and aerospace monitoring”
About the Authors
E. Grigoriev
Saint-Petersburg State University of Aerospace Instrumentation
Russian Federation
Russian Federation
A. Sergeev
Saint-Petersburg State University of Aerospace Instrumentation
Russian Federation
Russian Federation
References
1. Vladimirov S., Kognovitsky O. Dual Basis Based Processing of Wideband Gordon – Mills – Welch Sequences Based on Two Linear Registers. Proceed. of Telecom. Universities. 2019;5(2):49‒58. (in Russ.) DOI:10.31854/1813-324X-2019-5-2-49-58
2. FIPS 197. Advanced encryption standard (AES). URL: https://nvlpubs.nist.gov/nistpubs/FIPS/NIST.FIPS.197.pdf [Accessed 22d March 2023]
3. Rahman M., Saha K., Bhuiyan A. Implementation of RSA Algorithm for Speech Data Encryption and Decryption. International Journal of Computer Science and Network Security. 2012;(12)3:74‒82.
4. Gnanajeyaraman R., Prasadh K. Audio encryption using higher dimensional chaotic map. International Journal of Recent Trends in Engineering. 2009;1(2):103‒107.
5. Hassan N.A., Al-Mukhtar F.S., Ali E.H. Encrypt Audio File using Speech Audio File As a key. Proceedings of the 2nd International Scientific Conference of Al-Ayen University, ISCAU-2020, 15‒16 July 2020, Thi-Qar, Iraq. IOP Conference Series: Materials Science and Engineering. 2020;928 032066:79‒84. DOI:10.1088/1757-899X/928/3/032066
6. Farsana J., Devi R., Gopakumar K. An audio encryption scheme based on Fast Walsh Hadamard Transform and mixed chaotic keystreams. Applied Computing and Informatics. 2020;16(2). DOI:10.1016/j.aci.2019.10.001
7. Adhikari S., Karforma S. A novel audio encryption method using Henon–Tent chaotic pseudo random number sequence. International Journal of Information Technology. 2021;13:1463–1471. DOI:10.1007/s41870-021-00714-x
8. Cai C., Bai E., Jiang X.Q., Wu Y. Simultaneous Audio Encryption and Compression Using Parallel Compressive Sensing and Modified Toeplitz Measurement Matrix. Electronics. 2021;10(23):2902. DOI:10.3390/electronics10232902
9. Al-laham M.M. A Method for Encrypting and Decryptingwave Files. International Journal of Network Security & Its Applications. 2018;10(4):11‒21.
10. Abdallah H.A., Meshoul S.A. A Multilayered Audio Signal Encryption Approach for Secure Voice Communication. Electronics. 2023;12(1):2. DOI:10.3390/electronics12010002
11. Hameed Y.M., Ali N.H.M. An efficient audio encryption based on chaotic logistic map with 3D matrix. Journal of Theoretical and Applied Information Technology. 2018;96(16):5142‒5152.
12. Luis M., Daniel L., Isabel A., Deicy A. A new multimedia cryptosystem using chaos, quaternion theory and modular arithmetic. Multimedia Tools and Applications. 2023. DOI:10.1007/s11042-023-14475-1
13. Ge X., Sun G., Zheng B., Nan R. FPGA-Based Voice Encryption Equipment under the Analog Voice Communication Channel. Information. 2021;12(11):456. DOI:10.3390/info12110456
14. Donoho D.L. Compressed sensing. IEEE Transactions on Information Theory. 2006;52(4):1289‒1306. DOI:10.1109/TIT.2006.871582
15. Vostrikov A.A., Sergeev M.B., Litvinov M.Yu. Masking of Digital Visual Data: the Term and Basic Definitions. Information and Control Systems. 2015;5(78):116‒123. (in Russ.) DOI:10.15217/issn1684-8853.2015.5.116.
16. Vostrikov A., Sergeev M. Expansion of the Quasi-Orthogonal Basis to Mask Images. Proceedings of the 8th International KES Conference on Intelligent Interactive Multimedia Systems and Services, KES-IIMSS-15, 17‒19 June 2015, Sorrento, Italy. Smart Innovation, Systems and Technologies, vol.40. Cham: Springer; 2015. p.161‒168. DOI:10.1007/978-3-319-19830-9_15
17. Sergeev A. M., Grigoriev E. K. Quasi-orthogonal Structured Mersenne Matrices for Masking Digital Video and Audio Data in Distributed Systems. Proceedings of the International Conference on Information Processes and Systems Development and Quality Assurance, IPSQDA-2023. 2023. p.57–59.
18. Sergeev A. Interrelation of Symmetry and Antisymmetry of Quasi-Orthogonal Cyclic Matrices with Prime Numbers. Proc. of Telecom. Universities. 2022;8(4):14‒19. (in Russ.) DOI:10.31854/1813-324X-2022-8-4-14-19
19. Balonin A., Balonin U., Vostrikov A., Sergeev M. Computation of Mersenne ‒ Walsh Matrices. Herald of computer and information technologies. 2014;11:51–55. (in Russ.)
20. UrbanSound8K dataset. URL: https://urbansounddataset.weebly.com/urbansound8k.html [Accessed 04th April 2023]
21. Grigoriev E.K., Sergeev M.B., Sergeev A.M. The program for masking and demasking sound digital information. Masking module. Patent RF, no. 2023614623, 03.03.2023. (in Russ.)
22. Grigoriev E.K. Sergeev M.B. Sergeev A.M. The program for masking and demasking sound digital information. Demasking module. Patent RF, no. 2023614622, 03.03.2023. (in Russ.)
Review
For citations:
Grigoriev E., Sergeev A. Quality Analysis of Matrix Masking of Digital Audio Data. Proceedings of Telecommunication Universities. 2023;9(3):6-13. (In Russ.) https://doi.org/10.31854/1813-324X-2023-9-3-6-13
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