A Method for Restructuring Video Data in Compressed Coding Systems to Increase Reliability

Authors

DOI:

https://doi.org/10.20535/RADAP.2022.88.50-59

Keywords:

video information resource, restructuring, quantitative feature, coding, reliability, communication channel

Abstract

The subject of research in the article is the processing of video images using orthogonal transformation for data exchange in information and communication networks. The analysis of known algorithms for encoding video information with the active use of a statistical approach in data cod\-ing has been presented. The aim of the study is to develop a method for restructuring video information resource data in the compression coding systems for increasing information reliability. This will allow you to ensure the neutralizaon of the errors and avoid the destruction of video data during its reconstruction while maintaining the structural-statistical regularity and controlled loss of quality. The task of the article is to develop a method for restructuring information resource data using structural regularity in a binary sequence that specifies video information resource data; to analyze the effectiveness of the application of the developed method for restructuring video data by a quantitative attribute from the standpoint of creating conditions for additional reduction of the structural redundancy of code representation as well as to analyze the effectiveness of the application of the developed method of restructuring the information space from the standpoint of increasing reliability. The article presents a solution to the scientific problem that is aimed to develop methods for increasing reliability of compact video images in information and telecommunication networks of aero segment systems. As a result, the use of the developed method of restructuring video data based on the number of series of units makes it possible to create conditions for additional reduction in the structural redundancy of the code representation of information due to significant reduction of the power of the information space within which the data is encoded; the conditions are provided for localizing the effect of errors in the process of reconstructing video information resources; the conditions are created for reducing the time of data processing due to the fact that the developed method of data restructuring does not require transformations on message elements.

References

References

JPEG Privacy & Security Abstract and Executive Summary, 2015. JPEG.org, accessed 7.04.2021.

Barannik, V., Sidchenko, S., Barannik, D. (2020). Technology for Protecting Video Information Resources in the Info-Communication Space. IEEE 2nd International Conference on Advanced Trends in Information Theory (IEEE ATIT 2020), pp. 29-33. DOI: 10.1109/ATIT50783.2020.9349324.

Barannik, V., Sidchenko S., Barannik N., Barannik V. (2021). Development of the method for encoding service data in cryptocompression image representation systems. Eastern-European Journal of Enterprise Technologies, Vol. 3, No. 9(111), pp. 103-115. doi: 10.15587/1729-4061.2021.235521.

DSTU 7624:2014: Informatsiini tekhnolohii. Kryptohrafichnyi zakhyst informatsii. Alhorytm symetrychnoho blokovoho peretvorennia [Information Technology. Cryptographic protection of information. Symmetric block transformation algorithm]. Ministry of Economic Development of Ukraine, 2015. 39 p. [In Ukrainian].

Data Encryption Standard (DES), Federal Information Processing Standards Publication 46-3, 1999. 26 p.

DSTU GOST 28147:2009: Systema obrobky informatsii. Zakhyst kryptohrafichnyi. Alhorytm kryptohrafichnoho peretvorennia (HOST 28147-89) [Information processing system. Cryptographic protection. Cryptographic transformation algorithm (GOST 28147-89)], State Committee for Technical Regulation and Consumer Policy (Derzhspozhivstandart) of Ukraine, 2008. 20 p. [In Ukrainian].

Rivest, R., Shamir, A., Adleman, L. (1978). A method for obtaining digital signatures and public-key cryptosystems. Communications of the ACM, Vol. 21, Iss. 2, pp. 120-126. DOI: 10.1145/359340.359342.

Barannik, V., Babenko, Yu., Kulitsa, O., Barannik, V., Khimenko, A., Matviichuk-Yudina, O. (2020). Significant Microsegment Transformants Encoding Method to Increase the Availability of Video Information Resource. IEEE 2nd International Conference on Advanced Trends in Information Theory (IEEE ATIT 2020), pp. 52-56. DOI: 10.1109/ATIT50783.2020.9349256.

Chen, T.-H., Wu, Ch.-S. (2011). Efficient multi-secret image sharing based on Boolean operation. Signal Processing, Vol. 91, Iss. 1, pp. 90-97. DOI: 10.1016/j.sigpro.2010.06.012.

Barannik, V., Shulgin, S., Krasnorutsky, A., Slobodyanyuk, O., Gurzhii, P., Korolyova, N. (2020). Methodological Fundamentals of Deciphering Coding of Aerophotography Segments on Special Equipment of Unmanned Complex. IEEE 2 nd International Conference on Advanced Trends in Information Theory (IEEE ATIT 2020), pp. 38-43. DOI: 10.1109/ATIT50783.2020.9349257.

Li, F., Krivenko, S., Lukin, V. (2020). Two-step providing of desired quality in lossy image compression by SPIHT. Radioelectronic and computer systems, No. 2(94), pp. 22-32. DOI: 10.32620/reks.2020.2.02.

Ji, Sh., Tong, X., Zhang, M. (2012). Image encryption schemes for JPEG and GIF formats based on 3D baker with compound chaotic sequence generator. Cornell University arXiv. doi: 10.48550/arXiv.1208.0999.

Belikova N., Lekakh A., Dovbenko O., Dodukh O. (2019). Method of Increasing the Capacity of Information Threat Detection Filters in Modern Information and Communication Systems. 3rd International Conference on Advanced Information and Communications Technologies (AICT), pp 426-429. DОІ: 10.1109/AIACT.2019.8847754.

Naor, M., Shamir, A. (1994). Visual Cryptography. Proceedings of the Advances in Cryptology. EUROCRYPT’94. Lecture Notes in Computer Science, Vol. 950, pp. 1–12. DOI: 10.1007/bfb0053419.

Wu, Yu., Agaian, S., Noonan, J. (2012). Sudoku Associated Two Dimensional Bijections for Image Scrambling. IEEE Transactions on multimedia, available at: Cornell University arXiv, 30 p. doi: 10.48550/arXiv.1207.5856.

Tsai, Ch.-L., Chen, Ch.-J., Hsu, W.-L. (2012). Multi-morphological image data hiding based on the application of Rubik's cubic algorithm. IEEE International Carnahan Conference on Security Technology (ICCST), pp. 135-139. DOI: 10.1109/CCST.2012.6393548.

Wong K. W. (2009). Image encryption using chaotic maps. In: Kocarev, L., Galias, Z., Lian, S. (eds) Intelligent Computing Based on Chaos, Studies in Computational Intelligence, Vol. 184, pp. 333–354, Springer. DOI: 10.1007/978-3-540-95972-4_16.

Cheng, P., Yang, H., Wei, P., Zhang, W. (2015). A fast image encryption algorithm based on chaotic map and lookup table. Nonlinear Dynamics, Vol. 79, Iss. 3, pp. 2121-2131. DOI: 10.1007/s11071-014-1798-y.

Guesmi, R., Farah, M. A. B., Kachouri, A., Samet, M. (2016). A novel chaos-based image encryption using DNA sequence operation and Secure Hash Algorithm SHA-2. Nonlinear Dynamics, Vol. 83, Iss. 3, pp. 1123-1136. DOI: 10.1007/s11071-015-2392-7.

Barannik, V., Barannik, V. (2020). Binomial-Polyadic Binary Data Encoding by Quantity of Series of Ones. 15th IEEE International Conference on Modern Problems of Radio Engineering, Telecommunications and Computer Science (TCSET’2020), pp. 775-780. DOI: 10.1109/TCSET49122.2020.235540.

Kurihara, K., Watanabe O., Kiya, H. (2016). An encryption-then-compression system for JPEG XR standard. IEEE International Symposium on Broadband Multimedia Systems and Broadcasting (BMSB), pp. 1-5. DOI: 10.1109/BMSB.2016.7521997.

Sharma, R., Bollavarapu, S. (2015). Data Security using Compression and Cryptography Techniques. International Journal of Computer Applications, Vol. 117, No. 14, pp. 15-18. DOI: 10.5120/20621-3342.

Zhou, J., Liu, X., Au, O. C., Tang, Y. Y. (2014). Designing an Efficient Image Encryption-Then-Compression System via Prediction Error Clustering and Random Permutation. IEEE Transactions on Information Forensics and Security, Vol. 9, No. 1, pp. 39-50. DOI: 10.1109/TIFS.2013.2291625.

Dufaux, F., Ebrahimi, T. (2006). Toward a Secure JPEG. Applications of Digital Image Processing XXIX, Vol. 6312, pp. 1–8. DOI: 10.1117/12.686963.

Information technology – JPEG 2000 image coding system: Secure JPEG 2000, International Standard ISO/IEC 15444-8, ITU-T Recommendation T.807, 2007. 108 p.

Wu, Y., Noonan, J., Agaian S. (2011). NPCR and UACI Randomness Tests for Image Encryption. Cyber Journals: Multidisciplinary Journals in Science and Technology, Journal of Selected Areas in Telecommunications (JSAT), April Edition, pp. 31–38.

Farajallah, M. (2015). Chaos-based crypto and joint crypto-compression systems for images and videos. HAL science ouverte.

Wong, K., Tanaka, K. (2010). DCT based scalable scrambling method with reversible data hiding functionality. 4th International Symposium on Communications, Control and Signal Processing (ISCCSP), pp. 1-4. DOI: 10.1109/ISCCSP.2010.5463307.

Yang, Y., Zhu, B., Li, S., Yu, N. (2008). Efficient and Syntax-Compliant JPEG 2000 Encryption Preserving Original Fine Granularity of Scalability. EURASIP Journal on Information Security, Vol. 2007, pp. 126-139. DOI: 10.1155/2007/56365.

Watanabe, O., Uchida, A., Fukuhara, T., Kiya, H. (2015). An Encryption-then-Compression system for JPEG 2000 standard. IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), pp. 1226-1230, DOI: 10.1109/ICASSP.2015.7178165.

Minemura, K., Moayed, Z., Wong, K., Qi, X., Tanaka, K. (2012). JPEG image scrambling without expansion in bitstream size. 19th IEEE International Conference on Image Processing, pp. 261-264. DOI: 10.1109/ICIP.2012.6466845.

Phatak, A. A. (2016). Non-format Compliant Scalable RSA-based JPEG Encryption Algorithm. International Journal of Image, Graphics and Signal Processing, Vol. 8, No. 6., pp. 64–71. DOI: 10.5815/ijigsp.2016.06.08.

Komolov, D., Zhurbynskyy, D., Kulitsa, O. (2015). Selective Method For Hiding Of Video Information Resource In Telecommunication Systems Based On Encryption Of Energy-Significant Blocks Of Reference I-Frame. 1st International Conference on Advanced Information and Communication Technologies (AICT'2015), pp. 80-83.

Rippel, O., Bourdev, L. (2017). Real-Time Adaptive Image Compression. 34th International Conference on Machine Learning, Vol. 70, pp. 2922-2930.

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Published

2022-06-30

How to Cite

Бараннік , В. В., Красноруцкий, А. О., Пасинчук , К. М., Бабенко , Ю. М., Степанко , О. С. and Тупица , І. М. (2022) “A Method for Restructuring Video Data in Compressed Coding Systems to Increase Reliability”, Visnyk NTUU KPI Seriia - Radiotekhnika Radioaparatobuduvannia, (88), pp. 50-59. doi: 10.20535/RADAP.2022.88.50-59.

Issue

No. 88 (2022)

Section

Telecommunication, navigation, radar systems, radiooptics and electroacoustics

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Copyright (c) 2022 Андрей Красноруцкий

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