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Relevant bibliographies by topics / True Random Number Generator (TRNG)

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Academic literature on the topic 'True Random Number Generator (TRNG)'

Author: Grafiati

Published: 25 May 2024

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Journal articles on the topic "True Random Number Generator (TRNG)"

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Xingyuan, Wang, Qin Xue, and Teng Lin. "A Novel True Random Number Generator Based on Mouse Movement and a One-Dimensional Chaotic Map." Mathematical Problems in Engineering 2012 (2012): 1–9. http://dx.doi.org/10.1155/2012/931802.

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We propose a novel true random number generator using mouse movement and a one-dimensional chaotic map. We utilize thex-coordinate of the mouse movement to be the length of an iteration segment of our TRNs and they-coordinate to be the initial value of this iteration segment. And, when it iterates, we perturb the parameter with the real value produced by the TRNG itself. And we find that the TRNG we proposed conquers several flaws of some former mouse-based TRNGs. At last we take experiments and test the randomness of our algorithm with the NIST statistical test suite; results illustrate that

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Randa, Maulana, Mohammad Samie, and Ian K. Jennions. "Delay-Based True Random Number Generator in Sub-Nanomillimeter IoT Devices." Electronics 9, no. 5 (2020): 817. http://dx.doi.org/10.3390/electronics9050817.

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True Random Number Generators (TRNGs) use physical phenomenon as their source of randomness. In electronics, one of the most popular structures to build a TRNG is constructed based on the circuits that form propagation delays, such as a ring oscillator, shift register, and routing paths. This type of TRNG has been well-researched within the current technology of electronics. However, in the future, where electronics will use sub-nano millimeter (nm) technology, the components become smaller and work on near-threshold voltage (NTV). This condition has an effect on the timing-critical circuit, a

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Akashi, Nozomi, Kohei Nakajima, Mitsuru Shibayama, and Yasuo Kuniyoshi. "A mechanical true random number generator." New Journal of Physics 24, no. 1 (2022): 013019. http://dx.doi.org/10.1088/1367-2630/ac45ca.

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Abstract Random number generation has become an indispensable part of information processing: it is essential for many numerical algorithms, security applications, and in securing fairness in everyday life. Random number generators (RNGs) find application in many devices, ranging from dice and roulette wheels, via computer algorithms, lasers to quantum systems, which inevitably capitalize on their physical dynamics at respective spatio-temporal scales. Herein, to the best of our knowledge, we propose the first mathematically proven true RNG (TRNG) based on a mechanical system, particularly the

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Prasannanjali, C. "Ring Oscillator Based True Random Number Generator." International Journal for Research in Applied Science and Engineering Technology 12, no. 2 (2024): 276–83. http://dx.doi.org/10.22214/ijraset.2024.58320.

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Abstract: A true random number generator (TRNG), also known as a hardware random number generator (HRNG), does not use a computer algorithm. Instead, it uses an external unpredictable physical variable such as stochastic models to generate random numbers. Here it gathers data from random electronic signals. Then, the data is converted into digital form and any patterns registered are removed to make it random. This data is used to create random numbers. It is mainly used in Cryptographic Security, authentication, secure communications, e-commerce transactions, Digital Signatures etc. In Existi

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Zong, Yi, Lihua Dong, and Xiaoxin Lu. "Entropy Model of Rosin Autonomous Boolean Network Digital True Random Number Generator." Electronics 13, no. 6 (2024): 1140. http://dx.doi.org/10.3390/electronics13061140.

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A True Random Number Generator (TRNG) is an important component in cryptographic algorithms and protocols. The Rosin Autonomous Boolean Network (ABN) digital TRNG has been widely studied due to its nice properties, such as low energy consumption, high speed, strong platform portability, and strong randomness. However, there is still a lack of suitable entropy models to deduce the requirement of design parameters to ensure true randomness. The current model to evaluate the entropy of oscillator-based TRNGs is not applicable for Rosin ABN TRNGs due to low-frequency noise. This work presents a ne

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Gupta, Ramji, Alpana Pandey, and R. K.Baghel. "Efficient design of chaos based 4 bit true random number generator on FPGA." International Journal of Engineering & Technology 7, no. 3 (2018): 1783. http://dx.doi.org/10.14419/ijet.v7i3.16586.

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True random number generator is a basic building block of any modern secure communication and cryptography system. FPGA implementation of any system has a flexible architecture and low-cost test cycle. In this paper, we present an FPGA implementation of a high speed true random number generator based on chaos oscillator which gives optimize ratio of bit rate to area. The proposed generator is faster and more compact than the existing chaotic oscillator based TRNGs. The Experimental result shows that the proposed TRNG gives 1439 Mbps with optimizing the use of LUTs and registers. It is verified

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Nor Hashim, Noor Alia, Julius Teo Han Loong, Azrul Ghazali, and Fazrena Azlee Hamid. "Memristor based ring oscillators true random number generator with different window functions for applications in cryptography." Indonesian Journal of Electrical Engineering and Computer Science 14, no. 1 (2019): 201. http://dx.doi.org/10.11591/ijeecs.v14.i1.pp201-209.

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<span>Cryptographic applications require numbers that are random and pseudorandom. Keys must be produced in a random manner in order to be used in common cryptosystems. Random or pseudorandom inputs at different terminals are also required in a lot of cryptographic protocols. For example, producing digital signatures using supporting quantities or in verification procedures that requires generating challenges. Random number generation is an important part of cryptography because there are flaws in random number generation that can be taken advantage by attackers that compromised encrypti

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Khan, Mohammad Nasim Imtiaz, Chak Yuen Cheng, Sung Hao Lin, Abdullah Ash-Saki, and Swaroop Ghosh. "A Morphable Physically Unclonable Function and True Random Number Generator Using a Commercial Magnetic Memory." Journal of Low Power Electronics and Applications 11, no. 1 (2021): 5. http://dx.doi.org/10.3390/jlpea11010005.

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We use commercial magnetic memory to realize morphable security primitives, a Physically Unclonable Function (PUF) and a True Random Number Generator (TRNG). The PUF realized by manipulating the write time and the TRNG is realized by tweaking the number of write pulses. Our analysis indicates that more than 75% bits in the PUF are unusable without any correction due to their inability to exhibit any randomness. We exploit temporal randomness of working columns to fix the unusable columns and write latency to fix the unusable rows during the enrollment. The intra-HD, inter-HD, energy, bandwidth

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Lee, Kyungroul, and Manhee Lee. "True Random Number Generator (TRNG) Utilizing FM Radio Signals for Mobile and Embedded Devices in Multi-Access Edge Computing." Sensors 19, no. 19 (2019): 4130. http://dx.doi.org/10.3390/s19194130.

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As transmissions of data between mobile and embedded devices in multi-access edge computing (MEC) increase, data must be protected, ensuring confidentiality and integrity. These issues are usually solved with cryptographic algorithms systems, which utilize a random number generator to create seeds and keys randomly. Their role in cryptography is so important that they need to be generated securely. In this paper, a true random number generator (TRNG) utilizing FM radio signals as a source is proposed. The proposed method can generate random numbers with high entropy, increased by at least 118%

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G, Anahita, Krishnapriya KPM, Shiva Prasad R, and Mohan Kumar N. "HD-Sign: Hardware Based Digital Signature Generation Using True Random Number Generator." International Journal of Engineering & Technology 7, no. 3.8 (2018): 147. http://dx.doi.org/10.14419/ijet.v7i3.8.16850.

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With the recent advancements in the field of computing, a fair share of easier and safer practices to exchange and share information between multiple parties have propped up. While some of these are improvisations, a few such as the Digital Signatures, have fast replaced conventional signing practices. It’s wide use and acceptance in the industry as well as officially, has necessitated higher security to protect data integrity and privacy. These digital Signatures are generated on the basis of various schemes that are designed to accommodate efficiency, crypto security and algorithmic complexi

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Dissertations / Theses on the topic "True Random Number Generator (TRNG)"

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Petura, Oto. "True random number generators for cryptography : Design, securing and evaluation." Thesis, Lyon, 2019. http://www.theses.fr/2019LYSES053.

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Les nombres aléatoires sont essentiels pour les systèmes cryptographiques modernes. Ils servent de clés cryptographiques, de nonces, de vecteurs d’initialisation et de masques aléatoires pour la protection contre les attaques par canaux cachés. Dans cette thèse, nous traitons des générateurs de nombres aléatoires dans les circuits logiques (FPGA et ASIC). Nous présentons les méthodes fondamentales de génération de nombres aléatoires dans des circuits logiques. Ensuite, nous discutons de différents types de TRNG en utilisant le jitter d’horloge comme source d’aléa. Nous faisons une évaluation r

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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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Mureddu, Ugo. "Génération d'aléa dans les circuits électroniques numériques exploitant des cellules oscillantes." Thesis, Lyon, 2019. http://www.theses.fr/2019LYSES018.

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Les objets connectés sont omniprésents dans notre société actuelle (ex. véhicules, transports en commun, santé, domotique, smartphone, moyen de paiement, etc.). La connexion et l'accès à distance des appareils d'usage quotidien améliorent considérablement notre confort et notre efficacité dans notre vie professionnelle comme personnelle. Cependant, cela peut également nous confronter à des problèmes de sécurité sans précédent. Les risques liés à la large expansion des systèmes embarqués et de l'internet des objets sont doubles :- L'accès d'une personne non autorisée aux données pour la lecture

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Noumon, Allini Elie. "Caractérisation, évaluation et utilisation du jitter d'horloge comme source d'aléa dans la sécurité des données." Thesis, Lyon, 2020. http://www.theses.fr/2020LYSES019.

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Cette thèse, financée par la DGA, est motivée par la problématique d’évaluation des TRNG pour des applications à très haut niveau de sécurité. Les standards actuels tels que AIS-31 n’étant pas suffisants pour ces types d’applications, la DGA propose une procédure complémentaire, validée sur les TRNG utilisant les oscillateurs en anneau (RO), qui vise à caractériser la source d’aléa des TRNG afin d’identifier les bruits électroniques présents dans celle-ci. Ces bruits se traduisent dans les circuits numériques par le jitter d’horloge générée dans les RO. Ils peuvent être caractérisés par leur d

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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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Bazzi, Hussein. "Resistive memory co-design in CMOS technologies." Electronic Thesis or Diss., Aix-Marseille, 2020. http://www.theses.fr/2020AIXM0567.

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De nombreuses applications (internet des objets, systèmes embarqués automobiles et médicales, intelligence artificielle) ont besoin d’un circuit intégré (ou SoC pour System on Chip) avec des mémoires non volatiles embarquées performantes pour fonctionner de manière optimale. Bien que la mémoire Flash soit largement utilisée aujourd'hui, cette technologie nécessite une tension élevée pour les opérations de programmation et présente des problèmes de fiabilité difficiles à gérer au-delà du nœud technologique 18 nm, augmentant les coûts de conception et de fabrication des circuits. Dans ce context

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Shanmuga, Sundaram Prassanna. "Development of a FPGA-based True Random Number Generator for Space Applications." Thesis, Linköping University, Electronics System, 2010. http://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-54534.

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<p>Random numbers are required for cryptographic applications such as IT security products, smart cards etc. Hardwarebased random number generators are widely employed. Cryptographic algorithms are implemented on FieldProgrammable Gate Arrays (FPGAs). In this work a True Random Number Generator (TRNG) employed for spaceapplication was designed, investigated and evaluated. Several cryptographic requirements has to be satisfied for therandom numbers. Two different noise sources was designed and implemented on the FPGA. The first design wasbased on ring oscillators as a noise source. The second d

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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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Botha, Roelof Cornelis. "The development of a hardware random number generator for gamma-ray astronomy / R.C. Botha." Thesis, North-West University, 2005. http://hdl.handle.net/10394/581.

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Pulsars, as rotating magnetised neutron stars got much attention during the last 40 years since their discovery. Observations revealed them to be gamma-ray emitters with energies continuing up to the sub 100 GeV region. Better observation of this upper energy cut-off region will serve to enhance our theoretical understanding of pulsars and neutron stars. The H-test has been used the most extensively in the latest periodicity searches, whereas other tests have limited applications and are unsuited for pulsar searches. If the probability distribution of a test statistic is not accurately known,

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Book chapters on the topic "True Random Number Generator (TRNG)"

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Tehranipoor, Mark, N. Nalla Anandakumar, and Farimah Farahmandi. "True Random Number Generator (TRNG)." In Hardware Security Training, Hands-on! Springer International Publishing, 2023. http://dx.doi.org/10.1007/978-3-031-31034-8_2.

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Carboni, Roberto. "Characterization and Modeling of Spin-Transfer Torque (STT) Magnetic Memory for Computing Applications." In Special Topics in Information Technology. Springer International Publishing, 2021. http://dx.doi.org/10.1007/978-3-030-62476-7_5.

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AbstractWith the ubiquitous diffusion of mobile computing and Internet of Things (IoT), the amount of data exchanged and processed over the internet is increasing every day, demanding secure data communication/storage and new computing primitives. Although computing systems based on microelectronics steadily improved over the past 50 years thanks to the aggressive technological scaling, their improvement is now hindered by excessive power consumption and inherent performance limitation associated to the conventional computer architecture (von Neumann bottleneck). In this scenario, emerging memory technologies are gaining interest thanks to their non-volatility and low power/fast operation. In this chapter, experimental characterization and modeling of spin-transfer torque magnetic memory (STT-MRAM) are presented, with particular focus on cycling endurance and switching variability, which both present a challenge towards STT-based memory applications. Then, the switching variability in STT-MRAM is exploited for hardware security and computing primitives, such as true-random number generator (TRNG) and stochastic spiking neuron for neuromorphic and stochastic computing.

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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 sensitive data can combine the output from two or more independent sources of randomness for improved security.

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Saki, Abdullah Ash, Mahabubul Alam, and Swaroop Ghosh. "Quantum True Random Number Generator." In Design Automation of Quantum Computers. Springer International Publishing, 2022. http://dx.doi.org/10.1007/978-3-031-15699-1_4.

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Fischer, Viktor, and Miloš Drutarovský. "True Random Number Generator Embedded in Reconfigurable Hardware." In Cryptographic Hardware and Embedded Systems - CHES 2002. Springer Berlin Heidelberg, 2003. http://dx.doi.org/10.1007/3-540-36400-5_30.

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Siripragada, Anirudh, R. Shiva Prasad, and N. Mohankumar. "Power Efficient PUF-Based Random Reseeding True Random Number Generator." In Advances in Intelligent Systems and Computing. Springer Singapore, 2019. http://dx.doi.org/10.1007/978-981-13-3600-3_52.

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Rai, Shubham, Nishant Gupta, Abhiroop Bhattacharjee, et al. "END-TRUE: Emerging Nanotechnology-Based Double-Throughput True Random Number Generator." In VLSI-SoC: Technology Advancement on SoC Design. Springer Nature Switzerland, 2022. http://dx.doi.org/10.1007/978-3-031-16818-5_9.

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Li, Gang, Haoyang Sun, Peiqi Wu, et al. "A True Random Number Generator Based on ADC Random Interval Sampling." In Advances in Artificial Intelligence and Security. Springer International Publishing, 2022. http://dx.doi.org/10.1007/978-3-031-06764-8_56.

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Priyatharishini, M., and M. Nirmala Devi. "Realization of Re-configurable True Random Number Generator on FPGA." In Communications in Computer and Information Science. Springer Singapore, 2020. http://dx.doi.org/10.1007/978-981-15-4825-3_20.

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Fischer, Viktor, Miloš Drutarovský, Martin Šimka, and Nathalie Bochard. "High Performance True Random Number Generator in Altera Stratix FPLDs." In Field Programmable Logic and Application. Springer Berlin Heidelberg, 2004. http://dx.doi.org/10.1007/978-3-540-30117-2_57.

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Conference papers on the topic "True Random Number Generator (TRNG)"

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Arciuolo, Thomas, and Khaled M. Elleithy. "Parallel, True Random Number Generator (P-TRNG): Using Parallelism for Fast True Random Number Generation in Hardware." In 2021 IEEE 11th Annual Computing and Communication Workshop and Conference (CCWC). IEEE, 2021. http://dx.doi.org/10.1109/ccwc51732.2021.9375939.

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Sharma, Rahul, Ramya Ullagaddimath, Amit Baran Roy, Apratim Halder, and Veena Hegde. "Optical theremin based true Random Number Generation (TRNG) system." In 2015 International Conference on Advances in Computing, Communications and Informatics (ICACCI). IEEE, 2015. http://dx.doi.org/10.1109/icacci.2015.7275670.

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Ansari, Uzma, Akhilesh Kumar Chaudhary, and Sudhanshu Verma. "True Random Number Generator (TRNG) Using Sensors for Low Cost IoT Applications." In 2022 International Conference on Communication, Computing and Internet of Things (IC3IoT). IEEE, 2022. http://dx.doi.org/10.1109/ic3iot53935.2022.9767999.

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Ansari, Uzma, Akhilesh Kumar Chaudhary, and Sudhanshu Verma. "Enhanced True Random Number Generator (TRNG) using Sensors for IoT Security Applications." In 2022 Third International Conference on Intelligent Computing Instrumentation and Control Technologies (ICICICT). IEEE, 2022. http://dx.doi.org/10.1109/icicict54557.2022.9917919.

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Ji, Zhigang, James Brown, and Jianfu Zhang. "True Random Number Generator (TRNG) for Secure Communications in the Era of IoT." In 2020 China Semiconductor Technology International Conference (CSTIC). IEEE, 2020. http://dx.doi.org/10.1109/cstic49141.2020.9282535.

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Tao, Sha, and Elena Dubrova. "TVL-TRNG: Sub-Microwatt True Random Number Generator Exploiting Metastability in Ternary Valued Latches." In 2017 IEEE 47th International Symposium on Multiple-Valued Logic (ISMVL). IEEE, 2017. http://dx.doi.org/10.1109/ismvl.2017.10.

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Deotare, Vilas, Dinesh Padole, and Lalitkumar Wadhwa. "Parameter Dependencies and Optimization of True Random Number Generator (TRNG) using Genetic Algorithm (GA)." In 2021 8th International Conference on Smart Computing and Communications (ICSCC). IEEE, 2021. http://dx.doi.org/10.1109/icscc51209.2021.9528264.

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Ribeiro, Wellinton Costa, and Marcus Tadeu Pinheiro Silva. "Evaluating the Randomness of the RNG in a Commercial Smart Card." In Simpósio Brasileiro de Segurança da Informação e de Sistemas Computacionais. Sociedade Brasileira de Computação - SBC, 2017. http://dx.doi.org/10.5753/sbseg.2017.19531.

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This paper brings results concerning the quality evaluation for the pseudo-random number generator (PRNG) in a commercial smart card. The RNG is a fundamental part for the cryptography carried out in several applications. We have acquired a huge quantity of random numbers from three samples of a commercial smart card. These data were evaluated using the statistical computation package developed by National Institute of Standards and Technology. In order to be used as gold benchmark and to validate our methodology, we have also tested the true random number generator (TRNG) included in a commer

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Olgun, Ataberk, Minesh Patel, A. Giray Yaglikci, et al. "QUAC-TRNG: High-Throughput True Random Number Generation Using Quadruple Row Activation in Commodity DRAM Chips." In 2021 ACM/IEEE 48th Annual International Symposium on Computer Architecture (ISCA). IEEE, 2021. http://dx.doi.org/10.1109/isca52012.2021.00078.

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Xiao, Y., E. R. Hsieh, Steve S. Chung, et al. "Novel Concept of the Transistor Variation Directed Toward the Circuit Implementation of Physical Unclonable Function (PUF) and True-random-number Generator (TRNG)." In 2019 IEEE International Electron Devices Meeting (IEDM). IEEE, 2019. http://dx.doi.org/10.1109/iedm19573.2019.8993496.

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