Öz
Son işlem algoritmaları üretilen rasgele sayıların istatistiksel özelliklerini geliştirmek amacıyla uygulanan ve birçok rasgele sayı üretecinin ihtiyaç duyduğu bir aşamadır. Rasgele sayılara ihtiyaç duyan kullanıcılar rasgele sayı üreteçlerine erişebilseler bile son işlem yöntemlerini uygulayabilmek için kullanabilecekleri hazır bir kaynak bulunmamaktadır. Uygulama geliştirme aşamalarını bilseler bile son işlem yönteminin yapısını incelemeleri ve sonrasında bu yöntemi koda dökerek geliştirmeleri hayli vakit alacaktır. Bu sıkıntıları gidermek ve ihtiyaç halinde kullanıcıların son işlem yöntemlerine hızlı erişimlerini sağlayabilmek adına seçili bazı algoritmaların bulunduğu, literatürde olmayan bir yazılım süiti geliştirilmiştir. Kolay bir arayüz ile kullanıcı dostu olarak geliştirilen web uygulaması C# ile yazılmış ve tüm kullanıcıların ulaşabileceği şekilde yayınlanmıştır. Bu nedenle gerçek rasgele sayı üzerine çalışanlar için önemli bir kaynak olacaktır. Geliştirilen web tabanlı bu yazılıma son kullanıcılar postprocess.mersin.edu.tr adresinden erişebilir. Son işlem yazılımının sonuçlarını görebilmek amacıyla örnek saf bit dizileri yazılımdan geçirilerek üretilen son işlem sonuçları NIST (National Institute of Standards and Technology) testlerine tabi tutulmuştur ve tasarlanan yazılımın başarılı bir şekilde çalıştığı doğrulanmıştır.
Anahtar Kelimeler
rasgele sayılar rasgele sayı üreteçleri Son işlem algoritmaları Web tabanlı uygulama
Kaynakça
- Avaroğlu E., Türk M., (2013). Son İşlemin Gerçek Rasgele Sayı Üreteçleri Üzerindeki Etkisinin İncelenmesi. 6th International Information Security and Cryptology Conference, ISCTURKEY 2013, 290–294.
- 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.
- Avaroğlu E., Tuncer T., Özer A.B., Türk M., (2014). A new method for hybrid pseudo random number generator. J. Microelectron. Electron. Compon. Mater, 4(4), 303–311.
- 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.
- 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. 2013 European Conference on Circuit Theory and Design (ECCTD).
- Kyaw T.N.N., Tsuneda A., (2017). Generation of chaos-based random bit sequences with prescribed auto-correlations by post-processing using linear feedback shift registers. NOLTA 2017, 8, 224–234.
- 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.
- Trevisan L., (2001). Extractors and pseudorandom generators. Journal of the ACM, 48(4), 860–879. Raz R., Reingold O., Vadhan S., (2002). Extracting all the Randomness and Reducing the Error in Trevisan’s Extractors. Journal of Computer and System Sciences, 65(1), 97–128.
- Wegman M. N., Carter, J. L., (1981). New hash functions and their use in authentication and set equality. Journal of Computer and System Sciences, 22(3), 265–279, 1981.
- Zhang X., Nie Y., Liang H., Zhang J., (2016). FPGA implementation of Toeplitz hashing extractor for real time post-processing of raw random numbers. 2016 IEEE-NPSS Real Time Conference (RT), Padua 2016, 1-5, doi: 10.1109/RTC.2016.7543094.
- 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, 29(15).
- Kaya T., (2020). Memristor and Trivium-based true random number generator. Phys. A Stat. Mech. its Appl., 124071.
- Davies R. B., (2002). Exclusive OR (XOR) and hardware random number generators. http://www.robertnz.net/pdf/xor2.pdf.
- Suresh V. B., Burleson W. P., (2010). Entropy extraction in metastability-based TRNG. Proceedings of the IEEE International Symposium on Hardware-Oriented Security and Trust (HOST), 135–140.
- Dichtl M., (2007) Bad and Good Ways of Post-processing Biased Physical Random Numbers. 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.
- 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.
- 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.
- Peres Y., (1992). Iterating Von Neumann’s Procedure for Extracting Random Bits. Annals Statistics, 20(1), 590–597.
Öz
Post-processing algorithms are a step that is applied to improve the statistical properties of the generated random numbers and is needed by many random number generators. Even if users who need random numbers have access to random number generators, there is no readily available resource they can use to apply post-processing methods. Even if they know the application development stages, it will take a lot of time to examine the structure of the post-processing method and then code this method and develop it. A software suite, which does not exist in the literature, has been developed with some selected algorithms in order to eliminate these problems and to provide users with fast access to finishing methods when needed. The web application developed in a user-friendly way with an easy
interface was written in C # and published in a way that all users can access. For this reason, it will be an important resource for those studying on true random numbers. The web-based software can be accessed by end users at postprocess.mersin.edu.tr. In order to see the results of the post-processing software, the results produced by passing the sample raw bit strings through the software were subjected to NIST (National Institute of Standards and technology) tests and it was confirmed that the designed software works successfully.
Anahtar Kelimeler
Random numbers Random number generators Post processing algorithms Web-based application
Kaynakça
- Avaroğlu E., Türk M., (2013). Son İşlemin Gerçek Rasgele Sayı Üreteçleri Üzerindeki Etkisinin İncelenmesi. 6th International Information Security and Cryptology Conference, ISCTURKEY 2013, 290–294.
- 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.
- Avaroğlu E., Tuncer T., Özer A.B., Türk M., (2014). A new method for hybrid pseudo random number generator. J. Microelectron. Electron. Compon. Mater, 4(4), 303–311.
- 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.
- 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. 2013 European Conference on Circuit Theory and Design (ECCTD).
- Kyaw T.N.N., Tsuneda A., (2017). Generation of chaos-based random bit sequences with prescribed auto-correlations by post-processing using linear feedback shift registers. NOLTA 2017, 8, 224–234.
- 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.
- Trevisan L., (2001). Extractors and pseudorandom generators. Journal of the ACM, 48(4), 860–879. Raz R., Reingold O., Vadhan S., (2002). Extracting all the Randomness and Reducing the Error in Trevisan’s Extractors. Journal of Computer and System Sciences, 65(1), 97–128.
- Wegman M. N., Carter, J. L., (1981). New hash functions and their use in authentication and set equality. Journal of Computer and System Sciences, 22(3), 265–279, 1981.
- Zhang X., Nie Y., Liang H., Zhang J., (2016). FPGA implementation of Toeplitz hashing extractor for real time post-processing of raw random numbers. 2016 IEEE-NPSS Real Time Conference (RT), Padua 2016, 1-5, doi: 10.1109/RTC.2016.7543094.
- 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, 29(15).
- Kaya T., (2020). Memristor and Trivium-based true random number generator. Phys. A Stat. Mech. its Appl., 124071.
- Davies R. B., (2002). Exclusive OR (XOR) and hardware random number generators. http://www.robertnz.net/pdf/xor2.pdf.
- Suresh V. B., Burleson W. P., (2010). Entropy extraction in metastability-based TRNG. Proceedings of the IEEE International Symposium on Hardware-Oriented Security and Trust (HOST), 135–140.
- Dichtl M., (2007) Bad and Good Ways of Post-processing Biased Physical Random Numbers. 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.
- 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.
- 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.
- Peres Y., (1992). Iterating Von Neumann’s Procedure for Extracting Random Bits. Annals Statistics, 20(1), 590–597.
Ayrıntılar
| Birincil Dil | Türkçe |
|---|---|
| Konular | Mühendislik |
| Bölüm | Makaleler |
| Yazarlar | |
| Yayımlanma Tarihi | 30 Kasım 2021 |
| Yayımlandığı Sayı | Yıl 2021 Sayı: 28 |
- Makale Dosyaları
