Relevant bibliographies by topics / Random number generator

Contents

  1. Journal articles
  2. Dissertations / Theses
  3. Books
  4. Book chapters
  5. Conference papers
  6. Reports

Academic literature on the topic 'Random number generator'

Author: Grafiati
Published: 4 June 2021
Last updated: 25 July 2025

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Journal articles on the topic "Random number generator"

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Malikovich, Karimov Madjit, Komil Tashev, Nuriddin Safoev, Tashmatova Shaxnoza Sabirovna, Qurbonova Kabira Erkinovna, and Fayziraxmonov Boburjon Baxtiyorjon o‘g‘li. "Random and Pseudo-Random Number Generation Methods." American Journal of Applied Science and Technology 5, no. 5 (2025): 70–73. https://doi.org/10.37547/ajast/volume05issue05-16.

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Random number generation is a fundamental aspect of computer science, cryptography, simulations, and statistical sampling. This paper explores the definitions, classifications, and implementations of random and pseudo-random number generators (RNGs and PRNGs). We examine true random number generators (TRNGs), which derive randomness from physical phenomena, and pseudo-random number generators (PRNGs), which use deterministic algorithms to produce sequences that mimic randomness. Case studies, including Random.org, HotBits, laser-based RNGs, and the Linux random number generator, illustrate pra
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Manli Xu, Manli Xu, Jingzheng Huang Jingzheng Huang, Wenye Liang Wenye Liang, et al. "Adjustable unbalanced quantum random-number generator." Chinese Optics Letters 13, no. 2 (2015): 021405–21409. http://dx.doi.org/10.3788/col201513.021405.

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Harangus, Katalin, and András Kakucs. "Random Number Generator." Műszaki Tudományos Közlemények 18 (2023): 37–44. http://dx.doi.org/10.33894/mtk-2023.18.07.

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Illustration plays an important role during education: The Galton board is a suitable tool for illustrating random processes and explaining probability distributions. We have created this tool in a virtual version, which facilitates data collection for statistical processing of experimental data and also enables the study of non-symmetrical distributions. The random processes on the device are simulated, which requires a random number generator. Since there were some doubts about the software-generated pseudo-random numbers, we created a true random number generator based on the input noise of
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Thomas, Antu Annam, and Varghese Paul. "Nested Random Number Generator." International Journal of Advanced Research in Computer Science and Software Engineering 7, no. 5 (2017): 767–73. http://dx.doi.org/10.23956/ijarcsse/sv7i5/0327.

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Iavich, Maksim, Tamari Kuchukhidze, Giorgi Iashvili, and Sergiy Gnatyuk. "Hybrid quantum random number generator for cryptographic algorithms." RADIOELECTRONIC AND COMPUTER SYSTEMS, no. 4 (November 29, 2021): 103–18. http://dx.doi.org/10.32620/reks.2021.4.09.

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The subject matter of the article is pseudo-random number generators. Random numbers play the important role in cryptography. Using not secure pseudo-random number generators is a very common weakness. It is also a fundamental resource in science and engineering. There are algorithmically generated numbers that are similar to random distributions but are not random, called pseudo-random number generators. In many cases the tasks to be solved are based on the unpredictability of random numbers, which cannot be guaranteed in the case of pseudo-random number generators, true randomness is require
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Chen, I.-Te. "Random Numbers Generated from Audio and Video Sources." Mathematical Problems in Engineering 2013 (2013): 1–7. http://dx.doi.org/10.1155/2013/285373.

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Random numbers are very useful in simulation, chaos theory, game theory, information theory, pattern recognition, probability theory, quantum mechanics, statistics, and statistical mechanics. The random numbers are especially helpful in cryptography. In this work, the proposed random number generators come from white noise of audio and video (A/V) sources which are extracted from high-resolution IPCAM, WEBCAM, and MPEG-1 video files. The proposed generator applied on video sources from IPCAM and WEBCAM with microphone would be the true random number generator and the pseudorandom number genera
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Dodge, Yadolah. "A Natural Random Number Generator." International Statistical Review / Revue Internationale de Statistique 64, no. 3 (1996): 329. http://dx.doi.org/10.2307/1403789.

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Stefanov, André, Nicolas Gisin, Olivier Guinnard, Laurent Guinnard, and Hugo Zbinden. "Optical quantum random number generator." Journal of Modern Optics 47, no. 4 (2000): 595–98. http://dx.doi.org/10.1080/09500340008233380.

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Li, Pu, Jian-Zhong Zhang, and Yun-Cai Wang. "All-optical Random Number Generator." IEICE Proceeding Series 1 (March 17, 2014): 130–33. http://dx.doi.org/10.15248/proc.1.130.

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Komo, John J., and William J. Park. "Decimal pseudo-random number generator." SIMULATION 57, no. 4 (1991): 228–30. http://dx.doi.org/10.1177/003754979105700405.

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Dissertations / Theses on the topic "Random number generator"

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Karanam, Shashi Prashanth. "Tiny true random number generator." Fairfax, VA : George Mason University, 2009. http://hdl.handle.net/1920/4587.

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Thesis (M.S.)--George Mason University, 2009.<br>Vita: p. 91. Thesis director: Jens-Peter Kaps. Submitted in partial fulfillment of the requirements for the degree of Master of Science in Computer Engineering. Title from PDF t.p. (viewed Oct. 12, 2009). Includes bibliographical references (p. 88-90). Also issued in print.
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Crunk, Anthony Wayne. "A portable C random number generator." Thesis, Virginia Tech, 1985. http://hdl.handle.net/10919/45720.

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Proliferation of computers with varying word sizes has led to increases in software use where random number generation is required. Several techniques have been developed. Criteria of randomness, portability, period, reproducibility, variety, speed, and storage are used to evaluate developed generation methods. The Tausworthe method is the only method to meet the portability requirement, and is chosen to be implemented. A C language implementation is proposed as a possible implementation and test results are presented to confirm the acceptability of the proposed code.<br>Master of Science
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Franco, Juan. "Rapid Prototyping and Design of a Fast Random Number Generator." Thesis, University of North Texas, 2011. https://digital.library.unt.edu/ark:/67531/metadc115036/.

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Information in the form of online multimedia, bank accounts, or password usage for diverse applications needs some form of security. the core feature of many security systems is the generation of true random or pseudorandom numbers. Hence reliable generators of such numbers are indispensable. the fundamental hurdle is that digital computers cannot generate truly random numbers because the states and transitions of digital systems are well understood and predictable. Nothing in a digital computer happens truly randomly. Digital computers are sequential machines that perform a current state and
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Franco, Juan. "Rapid Prototyping and Design of a Fast Random Number Generator." Thesis, University of North Texas, 2012. https://digital.library.unt.edu/ark:/67531/metadc115040/.

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Information in the form of online multimedia, bank accounts, or password usage for diverse applications needs some form of security. the core feature of many security systems is the generation of true random or pseudorandom numbers. Hence reliable generators of such numbers are indispensable. the fundamental hurdle is that digital computers cannot generate truly random numbers because the states and transitions of digital systems are well understood and predictable. Nothing in a digital computer happens truly randomly. Digital computers are sequential machines that perform a current state and
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Mitchum, Sam. "Digital Implementation of a True Random Number Generator." VCU Scholars Compass, 2010. http://scholarscompass.vcu.edu/etd/2327.

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Random numbers are important for gaming, simulation and cryptography. Random numbers have been generated using analog circuitry. Two problems exist with using analog circuits in a digital design: (1) analog components require an analog circuit designer to insure proper structure and functionality and (2) analog components are not easily transmigrated into a different fabrication technology. This paper proposes a class of random number generators that are constructed using only digital components and typical digital design methodology. The proposed classification is called divergent path si
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Yadav, Avantika. "Design and Analysis of Digital True Random Number Generator." VCU Scholars Compass, 2013. http://scholarscompass.vcu.edu/etd/3229.

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Random number generator is a key component for strengthening and securing the confidentiality of electronic communications. Random number generators can be divided as either pseudo random number generators or true random number generators. A pseudo random number generator produces a stream of numbers that appears to be random but actually follow predefined sequence. A true random number generator produces a stream of unpredictable numbers that have no defined pattern. There has been growing interest to design true random number generator in past few years. Several Field Programmable Gate Array
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Pilcher, Martha Geraldine. "Development and validation of random cut test problem generator." Diss., Georgia Institute of Technology, 1985. http://hdl.handle.net/1853/24560.

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Mattioli, Federico. "Testing a Random Number Generator: formal properties and automotive application." Master's thesis, Alma Mater Studiorum - Università di Bologna, 2019. http://amslaurea.unibo.it/18187/.

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L'elaborato analizza un metodo di validazione dei generatori di numeri casuali (RNG), utilizzati per garantire la sicurezza dei moderni sistemi automotive. Il primo capitolo fornisce una panoramica della struttura di comunicazione dei moderni autoveicoli attraverso l'utilizzo di centraline (ECU): vengono riportati i principali punti di accesso ad un automobile, assieme a possibili tipologie di hacking; viene poi descritto l'utilizzo dei numeri casuali in crittografia, con particolare riferimento a quella utilizzata nei veicoli. Il secondo capitolo riporta le basi di probabilità necessarie a
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Gärtner, Joel. "Analysis of Entropy Usage in Random Number Generators." Thesis, KTH, Skolan för datavetenskap och kommunikation (CSC), 2017. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-214567.

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Cryptographically secure random number generators usually require an outside seed to be initialized. Other solutions instead use a continuous entropy stream to ensure that the internal state of the generator always remains unpredictable. This thesis analyses four such generators with entropy inputs. Furthermore, different ways to estimate entropy is presented and a new method useful for the generator analysis is developed. The developed entropy estimator performs well in tests and is used to analyse entropy gathered from the different generators. Furthermore, all the analysed generators exhibi
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Saiprasert, Chalermpol. "Design exploration of an FPGA-based multivariate Gaussian random number generator." Thesis, Imperial College London, 2010. http://hdl.handle.net/10044/1/6212.

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Monte Carlo simulation is one of the most widely used techniques for computationally intensive simulations in a variety of applications including mathematical analysis and modeling and statistical physics. A multivariate Gaussian random number generator (MVGRNG) is one of the main building blocks of such a system. Field Programmable Gate Arrays (FPGAs) are gaining increased popularity as an alternative means to the traditional general purpose processors targeting the acceleration of the computationally expensive random number generator block due to their fine grain parallelism and reconfigurab
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Books on the topic "Random number generator"

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Percus, O. E. A note on random number generator of Chung et al. Courant Institute of Mathematical Sciences, New York University, 1986.

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M, Kelsey John, and Information Technology Laboratory (National Institute of Standards and Technology). Computer Security Division, eds. Recommendation for random number generation using deterministic random bit generators (revised). U.S. Dept. of Commerce, Technology Administration, National Institute of Standards and Technology, Computer Security Division, Information Technology Laboratory, 2007.

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de la Fraga, Luis Gerardo, José David Rodríguez-Muñoz, and Esteban Tlelo-Cuautle. Random Number Generators. Springer Nature Switzerland, 2025. https://doi.org/10.1007/978-3-031-82865-2.

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Alonso, Laurent. Random generation of trees: Random generators in computer science. Kluwer Academic, 1995.

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Lewis, Peter A. W. Graphical analysis of some pseudo-random number generators. Naval Postgraduate School, 1986.

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Bukin, A. D. Correlations of pseudo-random numbers of multiplicative sequence. Institute of Nuclear Physics, 1989.

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Kollmitzer, Christian, Stefan Schauer, Stefan Rass, and Benjamin Rainer, eds. Quantum Random Number Generation. Springer International Publishing, 2020. http://dx.doi.org/10.1007/978-3-319-72596-3.

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Percus, O. E. Random number generators for ultracomputers. Courant Institute of Mathematical Sciences, New York University, 1987.

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István, Deák. Random number generators and simulation. Akadémiai Kiadó, 1990.

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Peter, Hellekalek, and Larcher Gerhard, eds. Random and quasi-random point sets. Springer, 1998.

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Book chapters on the topic "Random number generator"

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Lugrin, Thomas. "Random Number Generator." In Trends in Data Protection and Encryption Technologies. Springer Nature Switzerland, 2023. http://dx.doi.org/10.1007/978-3-031-33386-6_7.

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AbstractMost modern encryption and authentication methods rely on generating random numbers for key generation, initial vectors, or nonces. A Random Number Generator is cryptographically secure if the sequences of numbers that it generates are unpredictable. They are typically grouped into two categories: Pseudo-Random Number Generators and True Random Number Generators. Small-size, low-cost true Random Number Generators have already been integrated into off-the-shelf devices such as smartphones, computers, and hardware security modules. In addition, applications involving particularly sensiti
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Quirk, Thomas J., and Simone Cummings. "Random Number Generator." In Excel 2016 for Social Work Statistics. Springer International Publishing, 2017. http://dx.doi.org/10.1007/978-3-319-66221-3_2.

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Quirk, Thomas J. "Random Number Generator." In Excel 2013 for Social Sciences Statistics. Springer International Publishing, 2015. http://dx.doi.org/10.1007/978-3-319-19177-5_2.

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Quirk, Thomas J. "Random Number Generator." In Excel 2016 for Engineering Statistics. Springer International Publishing, 2016. http://dx.doi.org/10.1007/978-3-319-39182-3_2.

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Quirk, Thomas J. "Random Number Generator." In Excel 2013 for Educational and Psychological Statistics. Springer International Publishing, 2015. http://dx.doi.org/10.1007/978-3-319-26712-8_2.

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Quirk, Thomas J., Meghan Quirk, and Howard F. Horton. "Random Number Generator." In Excel 2013 for Biological and Life Sciences Statistics. Springer International Publishing, 2014. http://dx.doi.org/10.1007/978-3-319-12517-6_2.

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Quirk, Thomas J., and Eric Rhiney. "Random Number Generator." In Excel 2016 for Marketing Statistics. Springer International Publishing, 2016. http://dx.doi.org/10.1007/978-3-319-43376-9_2.

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Quirk, Thomas J. "Random Number Generator." In Excel 2016 in Applied Statistics for High School Students. Springer International Publishing, 2018. http://dx.doi.org/10.1007/978-3-319-89993-0_2.

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Quirk, Thomas J. "Random Number Generator." In Excel 2013 for Engineering Statistics. Springer International Publishing, 2015. http://dx.doi.org/10.1007/978-3-319-23555-4_2.

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Quirk, Thomas J., and Julie Palmer-Schuyler. "Random Number Generator." In Excel 2010 for Human Resource Management Statistics. Springer International Publishing, 2014. http://dx.doi.org/10.1007/978-3-319-10650-2_2.

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Conference papers on the topic "Random number generator"

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Karera, Kashish, Areej Khan, Humanyou Tariq, et al. "Construction of a Quantum Random Number Generator." In 2024 4th International Conference on Innovations in Computer Science (ICONICS). IEEE, 2024. https://doi.org/10.1109/iconics64289.2024.10824418.

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Beltran, J. M. "Real Random Number Generator Hardware by Quantum Decay." In 2024 IEEE Biennial Congress of Argentina (ARGENCON). IEEE, 2024. http://dx.doi.org/10.1109/argencon62399.2024.10735816.

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Chen, Abel C. H. "Pseudo Random Number Generator-Based One-Time Signature." In 2025 3rd International Conference on Smart Systems for applications in Electrical Sciences (ICSSES). IEEE, 2025. https://doi.org/10.1109/icsses64899.2025.11010000.

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Mogos, Gabriela. "Quantum random number generator vs. random number generator." In 2016 International Conference on Communications (COMM). IEEE, 2016. http://dx.doi.org/10.1109/iccomm.2016.7528306.

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Mouttoucoumaran, Dinesh Kumar, Lithish Kumar Vengadathan Munikrishnan, Jeffrey Steve Paul Sudhakar Sunder Raj, Dwaraka Thejdeep, and Vetri Selvan Murugan. "Deterministic random number generation: Pseudorandom number generator." In 6TH INTERNATIONAL CONFERENCE ON INTELLIGENT COMPUTING: IConIC2K23. AIP Publishing, 2025. https://doi.org/10.1063/5.0256110.

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Soubusta, Jan, Ondrej Haderka, and Martin Hendrych. "Quantum random number generator." In 12th Czech-Slovak-Polish Optical Conference on Wave and Quantum Aspects of Contemporary Optics, edited by Jan Perina, Sr., Miroslav Hrabovsky, and Jaromir Krepelka. SPIE, 2001. http://dx.doi.org/10.1117/12.417868.

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Shikano, Yutaka. "Unpredictable random number generator." In APPLICATION OF MATHEMATICS IN TECHNICAL AND NATURAL SCIENCES: 12th International On-line Conference for Promoting the Application of Mathematics in Technical and Natural Sciences - AMiTaNS’20. AIP Publishing, 2020. http://dx.doi.org/10.1063/5.0029701.

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Milinkovic, Luka, Marija Antic, and Zoran Cica. "Pseudo-random number generator based on irrational numbers." In TELSIKS 2011 - 2011 10th International Conference on Telecommunication in Modern Satellite, Cable and Broadcasting Services. IEEE, 2011. http://dx.doi.org/10.1109/telsks.2011.6143212.

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Pandey, Shashi Kant, and R. Jenef. "A Comparative Study and Analysis of Quantum Random Number Generator with True Random Number Generator." In 2024 16th International Conference on COMmunication Systems & NETworkS (COMSNETS). IEEE, 2024. http://dx.doi.org/10.1109/comsnets59351.2024.10426934.

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Aguilar Angulo, Julio A., Edith Kussener, Herve Barthelemy, and Benjamin Duval. "Discrete chaos - based Random Number Generator." In 2014 IEEE Faible Tension Faible Consommation (FTFC). IEEE, 2014. http://dx.doi.org/10.1109/ftfc.2014.6828610.

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Reports on the topic "Random number generator"

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Mcdonald, Kathleen Herrera. Quantum Random Number Generator. Office of Scientific and Technical Information (OSTI), 2019. http://dx.doi.org/10.2172/1557201.

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Newell, Raymond Thorson. Record Breaking Random Number Generator. Office of Scientific and Technical Information (OSTI), 2015. http://dx.doi.org/10.2172/1170694.

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Everhart - Erickson, Michael. Quantum Random Number Generator (QRNG). Office of Scientific and Technical Information (OSTI), 2021. http://dx.doi.org/10.2172/1764183.

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Stern, Ariana. Quantum Random Number Generator (QRNG). Office of Scientific and Technical Information (OSTI), 2021. http://dx.doi.org/10.2172/1829616.

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Josey, Colin. Reassessing the MCNP Random Number Generator. Office of Scientific and Technical Information (OSTI), 2023. http://dx.doi.org/10.2172/1998091.

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Bailey, David H. A Pseudo-Random Number Generator Based on Normal Numbers. Office of Scientific and Technical Information (OSTI), 2004. http://dx.doi.org/10.2172/860344.

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Colwell, C. J., R. A. Dramstad, and M. E. Lopez. A Quickly Tested Pascal Random Number Generator for Microcomputers. Defense Technical Information Center, 1985. http://dx.doi.org/10.21236/ada156059.

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Dolotii, Marharyta H., and Pavlo V. Merzlykin. Using the random number generator with a hardware entropy source for symmetric cryptography problems. [б. в.], 2018. http://dx.doi.org/10.31812/123456789/2883.

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The aim of the research is to test the possibility of using the developed random number generator [1], which utilizes the sound card noise as an entropy source, in the symmetric cryptography algorithms.
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Barker, E. B., and J. M. Kelsey. Recommendation for random number generation using deterministic random bit generators. National Institute of Standards and Technology, 2012. http://dx.doi.org/10.6028/nist.sp.800-90a.

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Barker, Elaine B., and John M. Kelsey. Recommendation for Random Number Generation Using Deterministic Random Bit Generators. National Institute of Standards and Technology, 2015. http://dx.doi.org/10.6028/nist.sp.800-90ar1.

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