Research Article
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Random Number Generator Based on Discrete Cosine Transform Based Lossy Picture Compression

Year 2021, Volume: 2 Issue: 2, 76 - 85, 18.12.2021

Selman Yakut

https://doi.org/10.46572/naturengs.1009013
Cited By: 2

Abstract

The The widespread use of digital data makes the security of this data important. Various cryptographic systems are used to ensure the security of this data. The most important part of these systems is random numbers. In this article, a random number generator based on the discrete cosine transform, which is the basis of image compression algorithms, is proposed. In this generator, the difference between the original image and the compressed image produced using the discrete cosine transform is used. The original picture is transferred to the frequency plane using the discrete cosine transform. It is then converted back to the space plane using the inverse discrete cosine transform. These transformations cause some losses as certain coefficients are taken into account. Raw random numbers were generated using the differences between the original image and the compressed image. Then, the possible weaknesses in the random numbers generated by passing these raw data through the hash function were fixed. The SHA-512 algorithm was used as the hash function. An important advantage of the developed system is that it can be easily produced using any digital data source. It has been shown by the analysis that the generated random numbers are safe.

Keywords

Discrete cosine transform Image compression Random numbers Hash functions.

References

  • [1] Flores-Vergara, A., Garcia-Guerrero, E. E., Inzunza-González, E., López-Bonilla, O. R., Rodríguez-Orozco, E., Cardenas-Valdez, J. R., Tlelo-Cuautle, E. (2019). Implementing a chaotic cryptosystem in a 64-bit embedded system by using multiple-precision arithmetic, Nonlinear Dynamics, 96(1): 497-516.
  • [2] Yu, J.-Y.; Lee, E.; Oh, S.-R.; Seo, Y.-D.; Kim, Y.-G. (2020). A Survey on Security Requirements for WSNs: Focusing on the Characteristics Related to Security. IEEE Access, 8:45304–45324.
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  • [5] Paar, C., Pelzl, J. (2009). Understanding cryptography: a textbook for students and practitioners, Universitat Bochum, Springer Publishing Company, Bochum, Germany.
  • [6] Yakut, S. (2019). Design and Analysis of Real Random Number Generators, Ph.D. Thesis, Fırat University Institute of Science and Technology, Elazığ, Turkey.
  • [7]-Bakiri, M., Guyeux, C., Couchot, J. F., Oudjida, A. K. (2018). Survey on hardware implementation of random number generators on FPGA: Theory and experimental analyses, Computer Science Review, 27: 135-153.
  • [8] Aljohani, M.; Ahmad, I.; Basheri, M.; Alassafi, M.O. (2019). Performance Analysis of Cryptographic Pseudorandom Number Generators. IEEE Access, 7: 39794–39805.
  • [9] García-Martínez, M., Campos-Cantón, E. (2015). Pseudo-random bit generator based on multi-modal maps, Nonlinear Dynamics, 82(4): 2119–2131.
  • [10] Avaroğlu E, Koyuncu İ, Özer AB, Türk M. (2017). A Hybrid pseudo-random number generator for cryptographic systems Nonlinear Dyn, 82:239–248.
  • [11] Yakut, S., Tuncer, T., & Özer, A. B. (2020). A New Secure and Efficient Approach for TRNG and Its Post-Processing Algorithms. Journal of Circuits, Systems and Computers.
  • [12] Avaroğlu, E. & Tuncer, T. (2020). A novel S-box-based postprocessing method for true random number generation. Turk. J. Elec. Eng. & Comp. Sci., 28: 288–301.
  • [13] Garipcan, A. M. ve Erdem, E. (2020). A GRSÜ using chaotic entropy pool as a post-processing technique: analysis, design and FPGA implementation, Analog Integrated Circuits and Signal Processing, 103(3): 391-410.
  • [14] Łoza Sz., Matuszewski Ł., Jessa M., (2015). A Random Number Generator Using Ring Oscillators and SHA-256 as Post-Processing. Int. Journal of Electronics and Telecommunications, 61(2): 199-204.
  • [15] Aljohani, M., Ahmad, I., Basheri, M., Alassafi, M. O. (2019). Performance analysis of cryptographic pseudorandom number generators, IEEE Access, 7: 39794-39805.
  • [16] Fuad M., Ernawan F., (2020) Video steganography based on DCT psychovisual and object motion, Bulletin of Electrical Engineering and Informatics, ISSN: 2302-9285, 9(3): 1015-1023., doi: 10.11591/eei.v9i3.1859
  • [17] Starosolski R., (2020). Hybrid Adaptive Lossless Image Compression Based on Discrete Wavelet Transform, Entropy, 22(7): 751, doi:10.3390/e22070751.
  • [[8] Hudson G., Yasuda H. and Sebestyen I., (1988). The international standardization of a still picture compression technique, IEEE Global Telecommunications Conference and Exhibition. Communications for the Information Age, 1988, pp. 1016-1021 vol.2, doi: 10.1109/GLOCOM.1988.25989.
  • [19] Wedaj F. T., Kim S., Kim H. J., et al. (2017). Improved reversible data hiding in JPEG images based on new coefficient selection strategy[J]. Eurasip Journal on Image & Video Processing, 2017(1):63.
  • [20] Ajmera A., Divecha M., Ghosh S. S., Raval I. and Chaturvedi R., (2019). Video Steganography: Using Scrambling- AES Encryption and DCT, DST Steganography, 2019 IEEE Pune Section International Conference (PuneCon), pp. 1-7, Pune, India. doi: 10.1109/PuneCon46936.2019.9105666.
  • [21] Mao B H, Wang Z C, Zhang X P., (2019) Asymmetric JPEG Steganography Based on Correlation in DCT Domain. Computer Science, , 46(01):203-207.
  • [22] Ahmed N., Natarajan T. and Rao K. R., (1974). Discrete Cosine Transform, in IEEE Transactions on Computers, vol. C-23, no. 1, pp. 90-93, Jan., doi: 10.1109/T-C.1974.223784.
  • [23] Al-Roithy, B.O., Gutub, A., (2021).Remodeling randomness prioritization to boost-up security of RGB image encryption. Multimed Tools Appl., 80: 28521–28581 https://doi.org/10.1007/s11042-021-11051-3.
  • [24] Sumagita M., Riadi I., Soepomo J.P., Warungboto U., (2018) Analysis of secure hash algorithm (SHA) 512 for encryption process on web based application. Int J Cyber-Secur Digital for (IJCSDF) 7(4):373–381.
  • [25] Rukhin, A., Soto, J., Nechvatal, J., Smid, M., Barker, E., Leigh, S., Levenson, M., Vangel, M., Banks, D., Heckert, A., Dray, J., Vo, S., (2010).A statistical test suite for random and pseudorandom number generators for cryptographic applications. NIST Special Publication 800–22rev1a, Gaithersburg, MD, USA.

Year 2021, Volume: 2 Issue: 2, 76 - 85, 18.12.2021

Selman Yakut

https://doi.org/10.46572/naturengs.1009013
Cited By: 2

Abstract

References

  • [1] Flores-Vergara, A., Garcia-Guerrero, E. E., Inzunza-González, E., López-Bonilla, O. R., Rodríguez-Orozco, E., Cardenas-Valdez, J. R., Tlelo-Cuautle, E. (2019). Implementing a chaotic cryptosystem in a 64-bit embedded system by using multiple-precision arithmetic, Nonlinear Dynamics, 96(1): 497-516.
  • [2] Yu, J.-Y.; Lee, E.; Oh, S.-R.; Seo, Y.-D.; Kim, Y.-G. (2020). A Survey on Security Requirements for WSNs: Focusing on the Characteristics Related to Security. IEEE Access, 8:45304–45324.
  • [3] Koç, Ç. (2009) Cryptographic Engineering. Springer, New York.
  • [4] Menezes, A.J., van Oorschot, P.C., Vanstone, S.A. (1996). Handbook of Applied Cryptography, 1st edn. CRC Press, Boca Raton
  • [5] Paar, C., Pelzl, J. (2009). Understanding cryptography: a textbook for students and practitioners, Universitat Bochum, Springer Publishing Company, Bochum, Germany.
  • [6] Yakut, S. (2019). Design and Analysis of Real Random Number Generators, Ph.D. Thesis, Fırat University Institute of Science and Technology, Elazığ, Turkey.
  • [7]-Bakiri, M., Guyeux, C., Couchot, J. F., Oudjida, A. K. (2018). Survey on hardware implementation of random number generators on FPGA: Theory and experimental analyses, Computer Science Review, 27: 135-153.
  • [8] Aljohani, M.; Ahmad, I.; Basheri, M.; Alassafi, M.O. (2019). Performance Analysis of Cryptographic Pseudorandom Number Generators. IEEE Access, 7: 39794–39805.
  • [9] García-Martínez, M., Campos-Cantón, E. (2015). Pseudo-random bit generator based on multi-modal maps, Nonlinear Dynamics, 82(4): 2119–2131.
  • [10] Avaroğlu E, Koyuncu İ, Özer AB, Türk M. (2017). A Hybrid pseudo-random number generator for cryptographic systems Nonlinear Dyn, 82:239–248.
  • [11] Yakut, S., Tuncer, T., & Özer, A. B. (2020). A New Secure and Efficient Approach for TRNG and Its Post-Processing Algorithms. Journal of Circuits, Systems and Computers.
  • [12] Avaroğlu, E. & Tuncer, T. (2020). A novel S-box-based postprocessing method for true random number generation. Turk. J. Elec. Eng. & Comp. Sci., 28: 288–301.
  • [13] Garipcan, A. M. ve Erdem, E. (2020). A GRSÜ using chaotic entropy pool as a post-processing technique: analysis, design and FPGA implementation, Analog Integrated Circuits and Signal Processing, 103(3): 391-410.
  • [14] Łoza Sz., Matuszewski Ł., Jessa M., (2015). A Random Number Generator Using Ring Oscillators and SHA-256 as Post-Processing. Int. Journal of Electronics and Telecommunications, 61(2): 199-204.
  • [15] Aljohani, M., Ahmad, I., Basheri, M., Alassafi, M. O. (2019). Performance analysis of cryptographic pseudorandom number generators, IEEE Access, 7: 39794-39805.
  • [16] Fuad M., Ernawan F., (2020) Video steganography based on DCT psychovisual and object motion, Bulletin of Electrical Engineering and Informatics, ISSN: 2302-9285, 9(3): 1015-1023., doi: 10.11591/eei.v9i3.1859
  • [17] Starosolski R., (2020). Hybrid Adaptive Lossless Image Compression Based on Discrete Wavelet Transform, Entropy, 22(7): 751, doi:10.3390/e22070751.
  • [[8] Hudson G., Yasuda H. and Sebestyen I., (1988). The international standardization of a still picture compression technique, IEEE Global Telecommunications Conference and Exhibition. Communications for the Information Age, 1988, pp. 1016-1021 vol.2, doi: 10.1109/GLOCOM.1988.25989.
  • [19] Wedaj F. T., Kim S., Kim H. J., et al. (2017). Improved reversible data hiding in JPEG images based on new coefficient selection strategy[J]. Eurasip Journal on Image & Video Processing, 2017(1):63.
  • [20] Ajmera A., Divecha M., Ghosh S. S., Raval I. and Chaturvedi R., (2019). Video Steganography: Using Scrambling- AES Encryption and DCT, DST Steganography, 2019 IEEE Pune Section International Conference (PuneCon), pp. 1-7, Pune, India. doi: 10.1109/PuneCon46936.2019.9105666.
  • [21] Mao B H, Wang Z C, Zhang X P., (2019) Asymmetric JPEG Steganography Based on Correlation in DCT Domain. Computer Science, , 46(01):203-207.
  • [22] Ahmed N., Natarajan T. and Rao K. R., (1974). Discrete Cosine Transform, in IEEE Transactions on Computers, vol. C-23, no. 1, pp. 90-93, Jan., doi: 10.1109/T-C.1974.223784.
  • [23] Al-Roithy, B.O., Gutub, A., (2021).Remodeling randomness prioritization to boost-up security of RGB image encryption. Multimed Tools Appl., 80: 28521–28581 https://doi.org/10.1007/s11042-021-11051-3.
  • [24] Sumagita M., Riadi I., Soepomo J.P., Warungboto U., (2018) Analysis of secure hash algorithm (SHA) 512 for encryption process on web based application. Int J Cyber-Secur Digital for (IJCSDF) 7(4):373–381.
  • [25] Rukhin, A., Soto, J., Nechvatal, J., Smid, M., Barker, E., Leigh, S., Levenson, M., Vangel, M., Banks, D., Heckert, A., Dray, J., Vo, S., (2010).A statistical test suite for random and pseudorandom number generators for cryptographic applications. NIST Special Publication 800–22rev1a, Gaithersburg, MD, USA.
There are 25 citations in total.

Details

Primary Language English
Journal Section Research Articles
Authors

Selman Yakut 0000-0002-0649-1993

Publication Date December 18, 2021
Submission Date October 13, 2021
Acceptance Date November 30, 2021
Published in Issue Year 2021 Volume: 2 Issue: 2

Cite

APA Yakut, S. (2021). Random Number Generator Based on Discrete Cosine Transform Based Lossy Picture Compression. NATURENGS, 2(2), 76-85. https://doi.org/10.46572/naturengs.1009013

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