Can Tesla Sphere be used for Random Number Generation?

Yıl 2023, Cilt: 14 Sayı: 1, 185 - 195, 22.06.2023

Oğuzhan Arslan İsmail Kırbaş

https://doi.org/10.29048/makufebed.1273073

Öz

The use of random numbers to represent uncertainty and unpredictability is essential in many industries. This is crucial in disciplines such as computer science, cryptography and statistics, where the use of randomness helps to guarantee the security and reliability of systems and procedures. In computer science, random number generation is used to generate passwords, keys and other security tokens, as well as to add randomness to algorithms and simulations. According to recent research, the hardware random number generators used in billions of IoT devices do not generate enough entropy. This paper describes how raw data collected by IoT system sensors can be used to generate random numbers for cryptography systems and also examines the consequences of these random numbers. Colour, light and camera are used as sensors. Monobit and poker test results are analysed to measure the quality of randomness. Sequences were obtained with the method that gave quality values as a result of the analysis and these sequences were entered into the NIST and FIPS 140-1 randomness test packages. When the results of these two tests were analysed, it was observed that the sequences passed all tests successfully.

Anahtar Kelimeler

Cryptography, internet of things, light sensor, random number generators, webcam sensor

Destekleyen Kurum

Burdur Mehmet Akif Ersoy University Scientific Research Project Unit

Proje Numarası

0800-YL-21

Teşekkür

This study was supported by Burdur Mehmet Akif Ersoy University within the scope of Scientific Research Project No. 0800-YL-21.

Rastgele Sayı Üretimi İçin Tesla Küresi Kullanılabilir mi?

Öz

Belirsizliği ve öngörülemezliği temsil etmek için rasgele sayıların kullanılması birçok endüstride esastır. Bu, rastgelelik kullanımının sistemlerin ve prosedürlerin güvenliğini ve güvenilirliğini garanti etmeye yardımcı olduğu bilgisayar bilimi, kriptografi ve istatistik gibi disiplinlerde çok önemlidir. Bilgisayar biliminde, rastgele sayı üretimi parolalar, anahtarlar ve diğer güvenlik belirteçleri oluşturmak ve ayrıca algoritmalara ve simülasyonlara rastgelelik eklemek için kullanılır. Son araştırmalara göre milyarlarca Nesnelerin İnterneti cihazında kullanılan donanımsal rastgele sayı üreteçleri yeterli entropi üretmiyor. Bu makale, IoT sistem sensörleri tarafından toplanan ham verilerin kriptografi sistemleri için rastgele sayılar oluşturmak üzere nasıl kullanılabileceğini açıklamakta ve ayrıca bu rastgele sayıların sonuçlarını incelemektedir. Sensör olarak renk, ışık ve kamera kullanılmıştır. Rastgelelik kalitesini ölçmek maksadıyla monobit ve poker test sonuçları analiz edilmiştir. Analiz sonucu kaliteli değerler veren yöntem ile diziler elde edilip NIST ve FIPS 140-1 rastgelelik test paketlerine bu diziler sokulmuştur. Bu iki testin sonuçları irdelendiğinde ise bütün testlerden başarıyla geçtiği gözlemlenmiştir.

Anahtar Kelimeler

Kriptografi, nesnelerin interneti, ışık sensörü, rastgele sayı üreteçleri, webcam sensörü

Proje Numarası

0800-YL-21

Kaynakça

• Abood, O.G., Guirguis S, Guirguis, S.K. (2018). A survey on cryptography algorithms. International Journal of Sci-entific and Research Publications, 8(7): 495-516.
• Ansari, U., Chaudhary, A.K., Verma S. (2022). True random number generator (TRNG) using sensors for low cost IoT applications. In 2022 International Conference on Communication, Computing and Internet of Things (IC3IoT), March 10-11, 2022, Chennai, India, 1-6.
• Atar, E., Ersoy, O.K., Özyılmaz, L. (2017). Hybrid data compression and optical cryptography with steep matching search method. Journal of the Faculty of En-gineering and Architecture of Gazi University, 32(1): 139–147.
• Chen, I-Te. (2013) Random numbers generated from audio and video sources. Mathematical problems in engineering; DOI:10.1155/2013/285373.
• Conti, M., Dehghantanha, A., Franke K., Watson, S. (2018). Internet of things security and forensics: Challenges and opportunities. Future Generation Computer Sys-tems, 78: 544–546.
• Coşkun, A., Ülker, Ü. (2013). Development of a cryptography algorithm for national information security and reliability determination against letter frequency analysis. Journal of Information Technologies, 6(2): 31.
• Demirkol, A.Ş. (2007). Adc based random number generator with chaotic oscillator input. PhD Thesis, Istanbul Technical University, Istanbul, Turkey.
• Etem, T., Kaya, T. (2020). Trivium-linear conjugate generator based bit generation for image encryption. Fırat University Journal of Engineering Science, 32(1): 287–294.
• Genç, Y., Arslan Tuncer, S. (2019). Human movements based true random number generation. Bitlis Eren University Journal of Science and Technology, 8(1): 261–269.
• Gözüaçık, N. (2015). Parent based routing algorithm for rpl used in IoT networks. MSc Thesis, Istanbul Technical University, İstanbul, Türkiye.
• Huang, M., Chen, Z., Zhang, Y., Guo, H. (2020). A phase fluctuation based practical quantum random number generator scheme with delay-free structure. Applied Sciences, 10(7): 2431.
• Luengo, E.A., Cerna, M.B.L., Villalba, L.J.G., Hurley-Smith D, Hernandez-Castro J. (2022). Critical analysis of hypothesis tests in federal ınformation processing standard (140-2). Entropy, 24(5): 613.
• Maqsood, F., Ahmed, M., Mumtaz Ali, M., Ali Shah, M. (2017). Cryptography: A comparative analysis for modern techniques. International Journal of Advanced Computer Science and Applications, 8(6).
• Rehman, A.U., Hussain, M., Munawar, A., Attique, M., Idress, M., Anwar, F., Ahmad, M. (2020). E-cultivation using the IoT with adafruit cloud. International Journal of Advance and Applied Sciences, 7(9): 75–82.
• Sezgin, Z.E. (2021). Tesla coil. Master Project, Maltepe University, Istanbul, Turkey.
• Sunny, A.I., Zhao, A., Li, L., Kanteh Sakiliba, S. (2020). Low-cost IoT-based sensor system: A case study on harsh environmental monitoring. Sensors, 21(1): 214.
• Tavas, V. (2011). Random number generators suitable for integration. PhD Thesis, Istanbul Technical University, Istanbul, Turkey.
• Üçgün, H., Gömbeci, F., Yüzgeç, U., Yalçin, N. (2020). Real-time indoor air quality monitoring system with IoT based platform. Bilecik Şeyh Edebali University Journal of Science and Technology, 7(1): 370–381.
• Yalman, Y., Ertürk, İ. (2016). The use of steganography in ensuring personal information security. ÜNAK Existence in the Information Age "Opportunities and Threats" Symposium, 2(2): 215.
• Yaşar, S.N., Ceren Dikici, F., Tanyildizi, E., Karaköse, E. (2021). Design of a generator based on middle square and SHA3 algorithm for randomisation requirements in science and engineering studies. Fırat University Journal of Science and Technology, 33(1): 81–91.
• Yılmaz, M., Ballı, S. (2016). Development of an intelligent selection system for the use of data encryption algorithms. International Journal of Information Security Engineering, 2(2): 18–28.
• Yosunlu, D., Avaroğlu, E. (2020). Investigation of post processing algorithms. Journal of Computer Science and Technology, 1(2): 66–73.
• Zhang, X., Qi, L., Tang, Z. ve Zhang, Y. (2014). Portable true random number generator for personal encryption application based on smartphone camera. Electronics Letters, 50(24): 1841–1843.