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Real Random Number Generation by Chemical Reactions Based on Quantum Wave Equation

Yıl 2024, Cilt: 5 Sayı: 2, 47 - 58
https://doi.org/10.54047/bibted.1544204

Öz

Random Number Generators are software or hardware components that allow the production of unpredictable number sequences without any pattern or relationship between them. Various studies have been conducted with different techniques regarding RNG. In these studies, the difficulties of random number generation and the high cost negatively affect the efficiency of the developed generators. Many different methods have been used in real random number generation, and even quantum random number generators have been developed to make predictability difficult. Quantum Random Number Generators; are a tepe of generator based on the laws of Quantum physics instead of classical physics.
In photonic-based RNG, random numbers are generated after various software and hardware operations by utilizing the uncertainty of photons. This study, it is aimed to develop a true random number generator using chemical reactions that have not been studied before.
Data was produced by using sensors and other hardware elements together, the values produced were taken as seed values and assigned as input to the algorithm used in generating random numbers, and true random numbers were produced and these numbers were tested in detail with known test methods.

Etik Beyan

x

Destekleyen Kurum

TÜBİTAK

Proje Numarası

121E323

Teşekkür

x

Kaynakça

  • Chaitin, GJ. (2001). Exploring Randomness, London, Springer.
  • Daemen, J., Rijmen V. (2013). The Design of Rijndael: AESThe Advanced Encryption Standard, New York, Springer Science & Business Media.
  • Robinson SO., Dessart, DJ. (1998). Teaching and Learning of Algorithms in School Mathematics, USA, National Council of Teachers of Mathematics.
  • Schoukens, J., Pintelon, R., van der Ouderaa, E., Renneboog. (1998) J. Survey of excitation signals for FFT based signal analyzers, IEEE Transactions on Instrumentation and Measurements, 37(3), 342-352.
  • Schindler, W., Killmann, W. (2002). Evaluation criteria for true (physical) random number generators used in cryptographic applications, Cryptographic Hardware and Embedded Systems.
  • Avaroğlu, E. (2017). LFSR soru girdisi ile puf tasarımının gerçeklenmesi, Fırat Üniversitesi Mühendislik Bilimleri Dergisi. 29(2), 15–21.
  • Tuncer, SA., Genç, Y. (2019). İnsan hareketleri tabanlı gerçek rastgele sayı üretimi. 8(1), 261–269.
  • Yalçın M., Suykens J., Vandewalle J. (2004). True Random Bit Generation from a Double Scroll Attractor, IEEE Trans. Circuits Syst.. 51(7), 1395-1404.
  • Koç, Ç. K. (2009). Cryptographic Engineering, SpringerVerlag.
  • Von Neumann, J. (1951). Various Techniques Used in Connection with Random Digits, National Bureau of Standards Applied Mathematics Series. 12, 36-38.
  • Wold, K. (2011). Security Properties of a Class of True Random Number Generators in Programmable Logic, Doctoral Degree, Gjøvik University College, Doctor of Philosophy in Information Security.
  • Sanguinetti, B., Martin, A., Zbinden, H., Gisin, N. (2014). Quantum random number generation on a mobile phone, Physical Review. 4(3), 031056.
  • Avaroğlu, E. (2014). Donanım Tabanlı Rastgele Sayı Üretecinin Gerçekleştirilmesi, Doktora Tezi, Fırat Üniversitesi, Fen Bilimleri Enstitüsü.
  • Kapur, JN., Kesavan, HK. (1992). Entropy Optimization Principles and Their Applications, Netherlands, Springer.
  • Dichtl, M. (2007). Bad and good ways of post processing biased physical random numbers, International Workshop on Fast Software Encryption.
  • Yıldırım, S. (2012). A True Random Number Generator in FPGA for Cryptographıc Applications, Master's degree, Middle East Technical University, Graduate School of Natural and Applied Sciences.
  • Özkaynak, F. (2013). Security problems for a pseudorandom sequence generator based on the Chen chaotic system, Computer Physics Communications.184(9), 2178-2181.
  • Özkaynak, F. (2020). Cryptographically secure random number generator with chaotic additional input, Nonlinear Dynamics. 78, 2015-2020. Özkaynak, F. (2015). Kriptolojik Rasgele Sayı Üreteçleri, Türkiye Bilişim Vakfi Bilgisayar Bilimleri ve Mühendisliği Dergisi. 8(2), 37-45. Voris, J., Saxena, N., Halevi, T. (2011). Accelerometers and randomness: perfect together, Proceedings of the fourth ACM conference on Wireless network security, Hamburg, Germany.
  • Mitra, M. (2012). A Low-Cost Lightweight Random Number Generator Implementation, International Journal of Engineering Research & Technology. 1(10), 1-9.
  • Hennebert, C., Hossayni, H., Lauradoux, C. (2013). Entropy harvesting from physical sensors, Proceedings of the sixth ACM conference on Security and privacy in wireless and mobile networks, Budapest, Hungary.
  • Bedekar, N., Shee, C. (2015). A Novel Approach to True Random Number Generation in Wearable Computing Environments Using MEMS Sensors. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics. 8957, 530-546.
  • Contassot-Vivier, S., Couchot, JF., Guyeux, C., Heam, P.C. (2017). Random Walk in a N-Cube Without Hamiltonian Cycle to Chaotic Pseudorandom Number Generation: Theoretical and Practical Considerations, International Journal of Bifurcation and Chaos. 27(1), 1750014.
  • Akgül, A., Arslan, C., Arıcıoğlu, B. (2019). Design of an Interface for Random Number Generators based on Integer and Fractional Order Chaotic Systems, Chaos Theory and Applications. 1(1), 1-18.
  • Rezk, A., Madian, A., Radwan, A., Soliman, A.M. (2019). Multiplierless Chaotic Pseudo Random Number Generators, AEU- International Journal of Electronics and Communications. 113, 152947.
  • 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.
  • Khan, F. U., Bhatia, S. (2012). A Novel Approach to Genetıc Algorıthm Based Cryptography, International Journal of Research in Computer Science. 2(3), 7-10. Hurley-Smith, D., Hernandez-Castro, J. (2020). Quantum Leap and Crash: Searching and Finding Bias in Quantum Random Number Generators, ACM Transactions on Privacy and Security. 23(3), 1-25.
  • Lin, X., Wang, S., Yin, Z.Q. (2020). Security analysis and improvement of source independent quantum random number generators with imperfect devices, Npj Quantum Information. 6(1), 100.
  • Kavulich, J., Van Deren, B., Schlosshauer, M. (2021). Searching for evidence of algorithmic randomness and incomputability in the output of quantum random number generators, Physics Letters; 2021. A (388), 127032.
  • Dutang, C., Wuertz. D. (2009). A note on random number generation, Overview of Random Generation Algoritms. Gençoğlu, MT. (2021). Quantum cryptography, quantum communicatıon and quantum computing problems and solutions, Turkish Journal of Science and Technology. 16 (1), 97-101.
  • Gençoğlu, MT., Agarwal, P. (2021). Use of Quantum Differential Equations in Sonic Processes, Applied Mathematics and Nonlinear Science. 6(1), 21-8.
  • Gençoğlu, MT. (2013). Complex solutions for Burgers-Like equation, F.U. Türkish Journal of Science and Technology. 8(2), 121-123.
  • Bujang MA., Sapri, F. (2018). An Application of the Runs Test to Test for Randomness of Observations Obtained from a Clinical Survey in an Ordered Population, Malaysian Journal of Medical Sciences. 25, 146-151.
  • Yakut, S., Tuncer, T., Ozer, A. B. (2019). Secure and Efficient Hybrid Random Number Generator Based on Sponge Constructions for Cryptographic Applications. Elektronika Ir Elektrotechnika, 25(4), 40-46. https://doi.org/10.5755/j01.eie.25.4.23969
  • Yakut, S., Tuncer, T., Ozer, A. B. (2020). A New Secure and Efficient Approach for TRNG and Its Post-Processing Algorithms, Journal of Circuits, Systems and Computers. 29:15.
  • 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
  • Yakut, S. (2022). Kayıplı Resim Sıkıştırma Algoritmalarını Temel Alan Rastgele Sayı Üreteci. Adıyaman Üniversitesi Mühendislik Bilimleri Dergisi, 9(18), 571-580. https://doi.org/10.54365/adyumbd.1145590
  • He, D., Huang, W., Chen, L., Chan, S. (2024). A Secure and Efficient Software Random Number Generator Applicable to the Internet of Things, IEEE Internet of Things Journal, 1-12. doi: 10.1109/JIOT.2024.3468451.
  • Santa Cruz, L.J.M., Faina, L.F., Souza Pereira, J.H. (2025). Exploring quantum systems for pseudo-random number generation. Quantum Stud.: Math. Found. 12, 3. https://doi.org/10.1007/s40509-024-00348-1 Cirauqui, D., Ángel, M., Guillem, G.M., Corominas, G., Graß, T., Grzybowski, P.R., Muñoz-Gil, G., Saavedra,J.R.M., Lewenstein, M. (2024). Comparing pseudo- and quantum-random number generators with Monte Carlo simulations. APL Quantum, 1 (3): 036125. https://doi.org/10.1063/5.0199568

Kuantum Dalga Denklemi Tabanlı Kimyasal Reaksiyonlarla Gerçek Rastgele Sayı Üretme

Yıl 2024, Cilt: 5 Sayı: 2, 47 - 58
https://doi.org/10.54047/bibted.1544204

Öz

Rastgele Sayı Üreteçleri, aralarında herhangi bir örüntü veya ilişki olmayacak şekilde tahmin edilemeyecek sayı dizileri üretilmesini sağlayan yazılımsal veya donanımsal bileşenlerdir. RSÜ ile ilgili farklı tekniklerle çeşitli çalışmalar yapılmıştır. Bu çalışmalarda rastgele sayı üretiminin zorlukları ve maliyetin yüksek olması geliştirilen üreteçlerin verimliliğini olumsuz etkilemektedir. Gerçek rastgele sayı üretiminde çok farklı yöntemler kullanılmış hatta tahmin edilebilirliği zorlaştırmak için kuantum rastgele sayı üreteci dahi geliştirilmiştir. Kuantum Rastgele Sayı Üreteçleri; klasik fizik yerine Kuantum fiziği yasalarının temel alındığı bir üreteç çeşididir.
Fotonik tabanlı KRSÜ'de fotonların belirsizliğinden faydalanılarak çeşitli yazılımsal ve donanımsal işlemlerden sonra rastgele sayılar üretilir. Üretilen bu sayılar, tahmin edilemeyecek seviyede güçlü rastgele sayılardır. Ancak bu yöntemin hem insan sağlığı hem de maliyet açısından olumsuzlukları mevcuttur. Bu çalışmada, özellikle radyoaktif rastgele sayı üreteçlerine alternatif olacak ve maliyeti düşürmek adına daha önce çalışılmamış olan kimyasal reaksiyonlar kullanılarak gerçek rastgele sayı üreteci geliştirilmesi amaçlanmıştır.
Donanımsal kaynaklar ve kimyasal reaksiyonlar birlikte kullanılarak gerçek rastgele sayılar üretilmiştir. Sensörler ve diğer donanım elemanlarının ortak kullanımıyla veri üretilmiş, üretilen değerler tohum değeri olarak alınıp, rastgele sayı üretmede kullanılan algoritmaya girdi olarak atanarak gerçek rastgele sayılar üretilmiş ve bu sayılar bilinen test yöntemleriyle detaylı olarak test edilmiştir.

Etik Beyan

x

Destekleyen Kurum

TÜBİTAK

Proje Numarası

121E323

Teşekkür

x

Kaynakça

  • Chaitin, GJ. (2001). Exploring Randomness, London, Springer.
  • Daemen, J., Rijmen V. (2013). The Design of Rijndael: AESThe Advanced Encryption Standard, New York, Springer Science & Business Media.
  • Robinson SO., Dessart, DJ. (1998). Teaching and Learning of Algorithms in School Mathematics, USA, National Council of Teachers of Mathematics.
  • Schoukens, J., Pintelon, R., van der Ouderaa, E., Renneboog. (1998) J. Survey of excitation signals for FFT based signal analyzers, IEEE Transactions on Instrumentation and Measurements, 37(3), 342-352.
  • Schindler, W., Killmann, W. (2002). Evaluation criteria for true (physical) random number generators used in cryptographic applications, Cryptographic Hardware and Embedded Systems.
  • Avaroğlu, E. (2017). LFSR soru girdisi ile puf tasarımının gerçeklenmesi, Fırat Üniversitesi Mühendislik Bilimleri Dergisi. 29(2), 15–21.
  • Tuncer, SA., Genç, Y. (2019). İnsan hareketleri tabanlı gerçek rastgele sayı üretimi. 8(1), 261–269.
  • Yalçın M., Suykens J., Vandewalle J. (2004). True Random Bit Generation from a Double Scroll Attractor, IEEE Trans. Circuits Syst.. 51(7), 1395-1404.
  • Koç, Ç. K. (2009). Cryptographic Engineering, SpringerVerlag.
  • Von Neumann, J. (1951). Various Techniques Used in Connection with Random Digits, National Bureau of Standards Applied Mathematics Series. 12, 36-38.
  • Wold, K. (2011). Security Properties of a Class of True Random Number Generators in Programmable Logic, Doctoral Degree, Gjøvik University College, Doctor of Philosophy in Information Security.
  • Sanguinetti, B., Martin, A., Zbinden, H., Gisin, N. (2014). Quantum random number generation on a mobile phone, Physical Review. 4(3), 031056.
  • Avaroğlu, E. (2014). Donanım Tabanlı Rastgele Sayı Üretecinin Gerçekleştirilmesi, Doktora Tezi, Fırat Üniversitesi, Fen Bilimleri Enstitüsü.
  • Kapur, JN., Kesavan, HK. (1992). Entropy Optimization Principles and Their Applications, Netherlands, Springer.
  • Dichtl, M. (2007). Bad and good ways of post processing biased physical random numbers, International Workshop on Fast Software Encryption.
  • Yıldırım, S. (2012). A True Random Number Generator in FPGA for Cryptographıc Applications, Master's degree, Middle East Technical University, Graduate School of Natural and Applied Sciences.
  • Özkaynak, F. (2013). Security problems for a pseudorandom sequence generator based on the Chen chaotic system, Computer Physics Communications.184(9), 2178-2181.
  • Özkaynak, F. (2020). Cryptographically secure random number generator with chaotic additional input, Nonlinear Dynamics. 78, 2015-2020. Özkaynak, F. (2015). Kriptolojik Rasgele Sayı Üreteçleri, Türkiye Bilişim Vakfi Bilgisayar Bilimleri ve Mühendisliği Dergisi. 8(2), 37-45. Voris, J., Saxena, N., Halevi, T. (2011). Accelerometers and randomness: perfect together, Proceedings of the fourth ACM conference on Wireless network security, Hamburg, Germany.
  • Mitra, M. (2012). A Low-Cost Lightweight Random Number Generator Implementation, International Journal of Engineering Research & Technology. 1(10), 1-9.
  • Hennebert, C., Hossayni, H., Lauradoux, C. (2013). Entropy harvesting from physical sensors, Proceedings of the sixth ACM conference on Security and privacy in wireless and mobile networks, Budapest, Hungary.
  • Bedekar, N., Shee, C. (2015). A Novel Approach to True Random Number Generation in Wearable Computing Environments Using MEMS Sensors. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics. 8957, 530-546.
  • Contassot-Vivier, S., Couchot, JF., Guyeux, C., Heam, P.C. (2017). Random Walk in a N-Cube Without Hamiltonian Cycle to Chaotic Pseudorandom Number Generation: Theoretical and Practical Considerations, International Journal of Bifurcation and Chaos. 27(1), 1750014.
  • Akgül, A., Arslan, C., Arıcıoğlu, B. (2019). Design of an Interface for Random Number Generators based on Integer and Fractional Order Chaotic Systems, Chaos Theory and Applications. 1(1), 1-18.
  • Rezk, A., Madian, A., Radwan, A., Soliman, A.M. (2019). Multiplierless Chaotic Pseudo Random Number Generators, AEU- International Journal of Electronics and Communications. 113, 152947.
  • 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.
  • Khan, F. U., Bhatia, S. (2012). A Novel Approach to Genetıc Algorıthm Based Cryptography, International Journal of Research in Computer Science. 2(3), 7-10. Hurley-Smith, D., Hernandez-Castro, J. (2020). Quantum Leap and Crash: Searching and Finding Bias in Quantum Random Number Generators, ACM Transactions on Privacy and Security. 23(3), 1-25.
  • Lin, X., Wang, S., Yin, Z.Q. (2020). Security analysis and improvement of source independent quantum random number generators with imperfect devices, Npj Quantum Information. 6(1), 100.
  • Kavulich, J., Van Deren, B., Schlosshauer, M. (2021). Searching for evidence of algorithmic randomness and incomputability in the output of quantum random number generators, Physics Letters; 2021. A (388), 127032.
  • Dutang, C., Wuertz. D. (2009). A note on random number generation, Overview of Random Generation Algoritms. Gençoğlu, MT. (2021). Quantum cryptography, quantum communicatıon and quantum computing problems and solutions, Turkish Journal of Science and Technology. 16 (1), 97-101.
  • Gençoğlu, MT., Agarwal, P. (2021). Use of Quantum Differential Equations in Sonic Processes, Applied Mathematics and Nonlinear Science. 6(1), 21-8.
  • Gençoğlu, MT. (2013). Complex solutions for Burgers-Like equation, F.U. Türkish Journal of Science and Technology. 8(2), 121-123.
  • Bujang MA., Sapri, F. (2018). An Application of the Runs Test to Test for Randomness of Observations Obtained from a Clinical Survey in an Ordered Population, Malaysian Journal of Medical Sciences. 25, 146-151.
  • Yakut, S., Tuncer, T., Ozer, A. B. (2019). Secure and Efficient Hybrid Random Number Generator Based on Sponge Constructions for Cryptographic Applications. Elektronika Ir Elektrotechnika, 25(4), 40-46. https://doi.org/10.5755/j01.eie.25.4.23969
  • Yakut, S., Tuncer, T., Ozer, A. B. (2020). A New Secure and Efficient Approach for TRNG and Its Post-Processing Algorithms, Journal of Circuits, Systems and Computers. 29:15.
  • 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
  • Yakut, S. (2022). Kayıplı Resim Sıkıştırma Algoritmalarını Temel Alan Rastgele Sayı Üreteci. Adıyaman Üniversitesi Mühendislik Bilimleri Dergisi, 9(18), 571-580. https://doi.org/10.54365/adyumbd.1145590
  • He, D., Huang, W., Chen, L., Chan, S. (2024). A Secure and Efficient Software Random Number Generator Applicable to the Internet of Things, IEEE Internet of Things Journal, 1-12. doi: 10.1109/JIOT.2024.3468451.
  • Santa Cruz, L.J.M., Faina, L.F., Souza Pereira, J.H. (2025). Exploring quantum systems for pseudo-random number generation. Quantum Stud.: Math. Found. 12, 3. https://doi.org/10.1007/s40509-024-00348-1 Cirauqui, D., Ángel, M., Guillem, G.M., Corominas, G., Graß, T., Grzybowski, P.R., Muñoz-Gil, G., Saavedra,J.R.M., Lewenstein, M. (2024). Comparing pseudo- and quantum-random number generators with Monte Carlo simulations. APL Quantum, 1 (3): 036125. https://doi.org/10.1063/5.0199568
Toplam 38 adet kaynakça vardır.

Ayrıntılar

Birincil Dil İngilizce
Konular Bilgi Güvenliği ve Kriptoloji
Bölüm Araştırma Makaleleri
Yazarlar

Muharrem Tuncay Gençoğlu 0000-0002-8784-9634

Tuncay Genç 0000-0002-8325-3243

Proje Numarası 121E323
Erken Görünüm Tarihi 19 Aralık 2024
Yayımlanma Tarihi
Gönderilme Tarihi 5 Eylül 2024
Kabul Tarihi 16 Aralık 2024
Yayımlandığı Sayı Yıl 2024 Cilt: 5 Sayı: 2

Kaynak Göster

APA Gençoğlu, M. T., & Genç, T. (2024). Real Random Number Generation by Chemical Reactions Based on Quantum Wave Equation. Bilgisayar Bilimleri Ve Teknolojileri Dergisi, 5(2), 47-58. https://doi.org/10.54047/bibted.1544204