Research Article
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Examination of Post Processing Algorithms

Year 2020, Volume: 1 Issue: 2, 66 - 73, 15.12.2020

Abstract

Random numbers can be defined as numbers that are defined for a certain range, their probability of occurrence is equal to each other, and there is no specific relationship between these numbers. Random number generators are tools used to generate random numbers. Some of the bit sequences obtained from these random number generators show poor statistical properties. For this reason, various post-processing algorithms are applied to the produced sequences in order to eliminate this weakness. In this article, major post-processing algorithms proposed so far have been examined and compared.

References

  • Yadav, A. (2013). Design and Analysis of Digital True Random Number Generator, M.Sc. Thesis Virginia Commonwealth University, Virginia.
  • Anikin, I. V. & Alnajjar, K. (2016). Psseudo-Random Number Generator Based on Fuzzy Logic. In 2016 International Siberian Conference on Control and Communications (SIBCON), 2016 International Siberian Conference, 1-4.
  • Avaroğlu, E. & Türk, M. (2013) Son İşlemin Gerçek Rasgele Sayı Üreteçleri Üzerindeki Etkisinin İncelenmesi. In 6th International Information Security and Cryptology Conference, ISCTURKEY 2013, 290–294.
  • Tehranipoor, F., Yan, W. & Chandy, J. A. (2016). Robust Hardware True Random Number Generators using DRAM Remanence Effects. In 2016 IEEE International Symposium on Hardware Oriented Security and Trust (HOST), 79–84.
  • Tsuneda, A., Mitsuishi, S. & Inoue, T. (2008). A Study on Generation of Random Bit Sequences with Post-Processing by Linear Feedback Shift Registers. International Journal of Innovative Computing, Information & Control, 4(10), 2631–2638.
  • Tsuneda, A. & Morikawa, K. (2013). A Study on Random Bit Sequences with Prescribed Auto-Correlations by Post-Processing Using Linear Feedback Shift Registers. In 2013 European Conference on Circuit Theory and Design (ECCTD).
  • Avaroğlu, E., Tuncer, T., Özer, A.B., Ergen, B., Türk, M. (2015). A novel chaos-based post-processing for TRNG. Nonlinear Dynamics, 81, 189–199.
  • Loza, S. & Matuszewski, L. (2014). A True Random Number Generator Using Ring Oscillators and SHA-256 as Post-Processings. In International Conference on Signals and Electronic Systems (ICSES) 2014, 1–4.
  • Nikolic, S. & Veinovic, M. D. (2016). Advancement of True Random Number Generators Based on Sound Cards Through Utilization of a New Post-processing Method. Wireless Personal Communications, 91(2), 603–622.
  • Von Neumann, J. (1951). Various Techniques Used in Connection With Random Digits. National Bureau of Standards Applied Math Series 12, 36–38.
  • Peres, Y. (1992). Iterating Von Neumann’s Procedure for Extracting Random Bits. Annals Statistics, 20(1), 590–597.
  • Elias, P. (1972). The efficient construction of an unbiased random sequence. Ann. Math. Statist, 43(3), 864–870.
  • Zhang, R., Chen, S., Wan, C. & Shinohara, H. (2018). High-Throughput Von Neumann Post-Processing for Random Number Generator. In 2018 International Symposium on VLSI Design, Automation and Test (VLSI-DAT), 1-4.
  • Yakut, S., Tuncer, T., & Özer, A. B. (2019). Secure and Efficient Hybrid Random Number Generator Based on Sponge Constructions for Cryptographic Applications. Elektronika Ir Elektrotechnika, 25(4), 40–46.
  • 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
  • Avaroğlu, E. & Tuncer, T. (2020). A novel S-box-based postprocessing method for true random number generation. Turk. J. Elec. Eng. & Comp. Sci. (2020) 28, 288–301.
  • Suresh, V. B., & Burleson, W. P. (2010). Entropy extraction in metastability-based TRNG. In Proceedings of the IEEE International Symposium on Hardware-Oriented Security and Trust (HOST), 135–140.
  • Davies, R. B. (2002). Exclusive OR (XOR) and hardware random number generators. 1-11. http://www.robertnz.net/pdf/xor2.pdf
  • Dichtl, M. (2007). Bad and Good Ways of Post-processing Biased Physical Random Numbers. In Proceedings of International Workshop on Fast Software Encryption (Luxembourg, Luxembourg, Mar. 26-28, 2007). FSE '07. Lecture Notes in Computer Science, 4593, Springer, Berlin, Germany, 137–152.
  • Sunar, B., Martin, W. J. & Stinson, D. R. (2007). A Provably Secure True Random Number Generator with Built-in Tolerance to Active Attacks. IEEE Transactions on Computers 2007, 56 (1), 109–119.

Son İşlem Algoritmalarının İncelenmesi

Year 2020, Volume: 1 Issue: 2, 66 - 73, 15.12.2020

Abstract

Rasgele sayılar, belirli bir aralık için tanımlanmış, oluşma olasılıkları birbirine eşit ve bu sayılar arasında belirli bir ilişki olmayan sayılar olarak tanımlanabilir. Rasgele sayı üreteçleri de rasgele sayıları üretmek için kullanılan araçlardır. Bu rasgele sayı üreteçlerinden elde edilen bit dizilerinin bazıları zayıf istatistiki özellikler göstermektedir. Bu nedenle üretilen dizilere bu zayıflığın giderilmesi amacıyla çeşitli son işlem algoritmaları uygulanmaktadır. Bu makalede şimdiye dek önerilen belli başlı son işlem algoritmaları incelenerek, karşılaştırılmaları yapılmıştır.

References

  • Yadav, A. (2013). Design and Analysis of Digital True Random Number Generator, M.Sc. Thesis Virginia Commonwealth University, Virginia.
  • Anikin, I. V. & Alnajjar, K. (2016). Psseudo-Random Number Generator Based on Fuzzy Logic. In 2016 International Siberian Conference on Control and Communications (SIBCON), 2016 International Siberian Conference, 1-4.
  • Avaroğlu, E. & Türk, M. (2013) Son İşlemin Gerçek Rasgele Sayı Üreteçleri Üzerindeki Etkisinin İncelenmesi. In 6th International Information Security and Cryptology Conference, ISCTURKEY 2013, 290–294.
  • Tehranipoor, F., Yan, W. & Chandy, J. A. (2016). Robust Hardware True Random Number Generators using DRAM Remanence Effects. In 2016 IEEE International Symposium on Hardware Oriented Security and Trust (HOST), 79–84.
  • Tsuneda, A., Mitsuishi, S. & Inoue, T. (2008). A Study on Generation of Random Bit Sequences with Post-Processing by Linear Feedback Shift Registers. International Journal of Innovative Computing, Information & Control, 4(10), 2631–2638.
  • Tsuneda, A. & Morikawa, K. (2013). A Study on Random Bit Sequences with Prescribed Auto-Correlations by Post-Processing Using Linear Feedback Shift Registers. In 2013 European Conference on Circuit Theory and Design (ECCTD).
  • Avaroğlu, E., Tuncer, T., Özer, A.B., Ergen, B., Türk, M. (2015). A novel chaos-based post-processing for TRNG. Nonlinear Dynamics, 81, 189–199.
  • Loza, S. & Matuszewski, L. (2014). A True Random Number Generator Using Ring Oscillators and SHA-256 as Post-Processings. In International Conference on Signals and Electronic Systems (ICSES) 2014, 1–4.
  • Nikolic, S. & Veinovic, M. D. (2016). Advancement of True Random Number Generators Based on Sound Cards Through Utilization of a New Post-processing Method. Wireless Personal Communications, 91(2), 603–622.
  • Von Neumann, J. (1951). Various Techniques Used in Connection With Random Digits. National Bureau of Standards Applied Math Series 12, 36–38.
  • Peres, Y. (1992). Iterating Von Neumann’s Procedure for Extracting Random Bits. Annals Statistics, 20(1), 590–597.
  • Elias, P. (1972). The efficient construction of an unbiased random sequence. Ann. Math. Statist, 43(3), 864–870.
  • Zhang, R., Chen, S., Wan, C. & Shinohara, H. (2018). High-Throughput Von Neumann Post-Processing for Random Number Generator. In 2018 International Symposium on VLSI Design, Automation and Test (VLSI-DAT), 1-4.
  • Yakut, S., Tuncer, T., & Özer, A. B. (2019). Secure and Efficient Hybrid Random Number Generator Based on Sponge Constructions for Cryptographic Applications. Elektronika Ir Elektrotechnika, 25(4), 40–46.
  • 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
  • Avaroğlu, E. & Tuncer, T. (2020). A novel S-box-based postprocessing method for true random number generation. Turk. J. Elec. Eng. & Comp. Sci. (2020) 28, 288–301.
  • Suresh, V. B., & Burleson, W. P. (2010). Entropy extraction in metastability-based TRNG. In Proceedings of the IEEE International Symposium on Hardware-Oriented Security and Trust (HOST), 135–140.
  • Davies, R. B. (2002). Exclusive OR (XOR) and hardware random number generators. 1-11. http://www.robertnz.net/pdf/xor2.pdf
  • Dichtl, M. (2007). Bad and Good Ways of Post-processing Biased Physical Random Numbers. In Proceedings of International Workshop on Fast Software Encryption (Luxembourg, Luxembourg, Mar. 26-28, 2007). FSE '07. Lecture Notes in Computer Science, 4593, Springer, Berlin, Germany, 137–152.
  • Sunar, B., Martin, W. J. & Stinson, D. R. (2007). A Provably Secure True Random Number Generator with Built-in Tolerance to Active Attacks. IEEE Transactions on Computers 2007, 56 (1), 109–119.
There are 20 citations in total.

Details

Primary Language Turkish
Subjects Computer Software
Journal Section Research Articles
Authors

Didem Yosunlu 0000-0001-6917-4912

Erdinç Avaroğlu 0000-0003-1976-2526

Publication Date December 15, 2020
Submission Date November 4, 2020
Acceptance Date November 26, 2020
Published in Issue Year 2020 Volume: 1 Issue: 2

Cite

APA Yosunlu, D., & Avaroğlu, E. (2020). Son İşlem Algoritmalarının İncelenmesi. Bilgisayar Bilimleri Ve Teknolojileri Dergisi, 1(2), 66-73.