Author:
Yoon Inkwon,Han Jong Hyeok,Park Byeong Uk,Jeon Hee-Jae
Abstract
AbstractThe development of random number generators (RNGs) using speckle patterns is pivotal for secure encryption key generation, drawing from the recent statistical properties identified in speckle-based imaging. Speckle-based RNG systems generate a sequence of random numbers through the unpredictable and reproducible nature of speckle patterns, ensuring a source of randomness that is independent of algorithms. However, to guarantee their effectiveness and reliability, these systems demand a meticulous and rigorous approach. In this study, we present a blood-inspired RNG system with a microfluidics device, designed to generate random numbers at a rate of 5.5 MHz and a high-speed of 1250 fps. This process is achieved by directing a laser beam through a volumetric scattering medium to procure speckle patterns. Additionally, designed microfluidic device requires only a minimal blood sample of 5 µl to capture these speckle patterns effectively. After implementing the two-pass tuple-output von Neumann debiasing algorithm to counteract statistical biases, we utilized the randomness statistical test suite from the National Institute of Standards and Technology for validation. The generated numbers successfully passed these tests, ensuring their randomness and unpredictability. Our blood-inspired RNG, utilizing whole blood, offers a pathway for affordable, high-output applications in fields like encryption, computer security, and data protection.
Funder
the National Research Foundation of Korea (NRF) grant under the auspices of the Korea government
IITP and funded by the Ministry of Science and ICT
Korea and Regional Innovation Strategy
Publisher
Springer Science and Business Media LLC
Reference35 articles.
1. Aumasson, J.-P. Serious Cryptography: A Practical Introduction to Modern Encryption (No Starch Press, 2017).
2. Chowdhury, S. et al. Physical security in the post-quantum era: A survey on side-channel analysis, random number generators, and physically unclonable functions. Preprint at https://arxiv.org/abs/2005.04344 (2005)
3. Buchanan, W. & Woodward, A. Will quantum computers be the end of public key encryption?. J. Cyber Secur. Technol. 1, 1–22 (2017).
4. Rezk, A. A., Madian, A. H., Radwan, A. G. & Soliman, A. M. Reconfigurable chaotic pseudo random number generator based on FPGA. AEU Int. J. Electron. Commun. 98, 174–180 (2019).
5. Tuna, M. A novel secure chaos-based pseudo random number generator based on ANN-based chaotic and ring oscillator: Design and its FPGA implementation. Analog Integr. Circ. Sig. Process 105, 167–181 (2020).
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