THE DATA ENCODING IN DENIABLE ENCRYPTION ALGORITHMS

Authors

  • A.V. HALCHENKO
  • S.V. CHOPOROV

DOI:

https://doi.org/10.32782/KNTU2618-0340/2020.3.2-1.6

Keywords:

denied encryption; information protection; confidential data; divide and rule method; unauthorized access; coercion; productivity; data compression; code

Abstract

The hypothesis of the deniable encryption algorithms productivity increasing without the original algorithms transformation possibility has been investigated in this article. The algorithms of deniable encryption is relevant because of effective protection schemes of information and its users. These algorithms have the complex and concentrated structure. It makes impossible their practical applying. Its productivity is affected by them. That’s why deniable encryption algorithms are not applied for practical using. The encoding information algorithms reviewing and its investigation are main objectives of the article. They allow to transform the information, not its value. The deniable encryption algorithms input data is reduced by the encoding algorithms. The deniable encryption algorithms proportional productivity increasing and their practical applying are provided. The effective encoding algorithms and their applications are overviewed and applied to deniable encryption algorithms in this manuscript. Two algorithms have been investigated. The first scheme is based on the deniable encryption mechanisms. Its security bugs have been identified and investigated. Another algorithm is based on the efficient encoding algorithms. They are implemented to the basic data processing subsystem. Both of the algorithms’ efficiency has been investigated by the real public and secret information files using. The proposed data processing schemes are investigated by the user's workplace simulating. The original deniable encryption algorithm productivity increasing has been reached by the reduced data size. Also, the encryption keys difference and its dependence have been tested and compared with the other authors’ investigations. Finally, the general authors' hypothesis has been confirmed. The tested deniable encryption algorithms productivity has been increased.

References

Гальченко А. В., Чопоров С. В. Заперечуване шифрування на основі застосування підходу гібридних криптографічних систем. Радіоелектроніка, інформатика, управління. 2019. № 1. С. 178−191.

Молдовян Н. А., Вайчикаускас М. А. Расширение криптосхемы Рабина: алгоритм отрицаемого шифрования по открытому ключу. Вопросы защиты информации. 2014. № 2. С. 12−16.

Молдовян Н. А., Биричевский А. Р., Мондикова Я. А. Отрицаемое шифрование на основе блочных шифров. Информационно-управляющие системы. 2014. № 5. С. 80−86.

Буза М. К. Механизм повышения надежности сжатия данных. Штучний інтелект. 2016. № 2. С. 96−102.

Goldwasser S., Micali C. Probabilistic Encryptionю. Journal of Computer and System Sciences. 1984. Vol. 28. Р. 277−299.

Canetti R., Dwork C., Naor M. Ostrovsky R. Deniable Encryption. Advances in Cryptology – CRYPTO: 30th Annual International Conference on the Theory and Applications of Cryptographic Techniques. (Estonia, Tallinn, May 15-19, 2011). Berlin: Springer, 1997. P. 90−104.

Ibrahim H. Receiver-Deniable Public-Key Encryption. International Journal of Network Security. 2009. Vol. 8. № 2. Р. 159−165.

Klonowski M., Kubiak P., Kutyłowsk M. Practical Deniable Encryption. SOFSEM 2008: 34th Conference on Current Trends in Theory and Practice of Computer Science. (Slovakia, Nový Smokovec, January 19-25, 2008). Berlin: Springer, 2008. P. 599−609.

Лидовский В. В. Теория информации: М.: Компания Спутник+, 2004. 111 с.

Grasemann U., Miikkulainen R. Effective Image Compression Using Evolved Wavelets. Genetic and Evolutionary Computation Conference, GECCO 2005: International Conference. (USA, Washington, June 25-29, 2005). New York: Association for Computing Machinery, 2005. P. 1961−1968.

Zhihua G., Xiuli C., Zhang J., Zhang Y. An Effective Image Compression–Encryption Scheme Based on Compressive Sensing (CS) and Game of Life (GOL). Neural Computing and Applications. 2020. Vol. 32. Issue 17. P. 4961–4988.

Kedarnath J. B., Nur A. T. Relationship Between Entropy and Test Data Compression. IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems. 2007. Vol. 26. №. 2. Р. 386−395.

Published

2023-08-28