Results 251 to 260 of about 27,378 (290)
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2014
Random numbers are needed in many areas: cryptography, Monte Carlo computation and simulation, industrial testing and labeling, hazard games, gambling, etc. Our assumption has been that random numbers cannot be computed ; because digital computers operate deterministically, they cannot produce random umbrs.
Mario Stipčević, Çetin Kaya Koç
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Random numbers are needed in many areas: cryptography, Monte Carlo computation and simulation, industrial testing and labeling, hazard games, gambling, etc. Our assumption has been that random numbers cannot be computed ; because digital computers operate deterministically, they cannot produce random umbrs.
Mario Stipčević, Çetin Kaya Koç
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A 0.43pJ/bit true random number generator
2014 IEEE Asian Solid-State Circuits Conference (A-SSCC), 2014A small-area energy-efficient true random number generator (TRNG) is presented. This TRNG introduces a jitter signal generator to realize the noise pre-amplification, and utilizes a metastable latch to resolve the jitter edges. Moreover, to tolerate the process and environment variations, an offset calibration is employed to dynamically correct the ...
Ting-Kuei Kuan +2 more
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A true random number generator with on-line testability
2014 19th IEEE European Test Symposium (ETS), 2014True random number generators (TRNGs) are widely used throughout cryptography. They are used in the challenge response authentication procedures, key generation and for hardening measures against power analysis attacks. An important feature of each TRNG is true randomness. Such randomness can be obtained from random physical effects like noise.
Eberhard Böhl +2 more
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An embedded true random number generator for FPGAs
Proceedings of the 2004 ACM/SIGDA 12th international symposium on Field programmable gate arrays, 2004Field Programmable Gate Arrays (FPGAs) are an increasingly popular choice of platform for the implementation of cryptographic systems. Until recently, designers using FPGAs had less than optimal choices for a source of truly random bits. In this paper we extend a technique that uses on-chip jitter and PLLs to a much larger class of FPGAs that do not ...
Paul Kohlbrenner, Kris Gaj
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A meta-level true random number generator
International Journal of Critical Computer-Based Systems, 2010True random number generators (TRNGs) are extensively used in cryptography, simulations and statistics. In this work, we introduce, extend and analyse the concept of the randomised bit cell (RBC), introducing a second meta-level of randomisation, being able to simultaneously produce random numbers and detect active non-intrusive attacks. The concept is
Bernhard Fechner, Andre Osterloh
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2021 IEEE 11th Annual Computing and Communication Workshop and Conference (CCWC), 2021
Currently, True Random Number Generation (TRNG) is relatively slow, utilizing natural, physical processes as its entropy source. Other types of random numbers, such as Pseudo-Random Numbers, lack true randomness as eventually they repeat, but can be generated with great speed.
Thomas Arciuolo, Khaled M. Elleithy
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Currently, True Random Number Generation (TRNG) is relatively slow, utilizing natural, physical processes as its entropy source. Other types of random numbers, such as Pseudo-Random Numbers, lack true randomness as eventually they repeat, but can be generated with great speed.
Thomas Arciuolo, Khaled M. Elleithy
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Influence of the temperature on true random number generators
2011 IEEE International Symposium on Hardware-Oriented Security and Trust, 2011Today TRNGs are used in many different applications. The quality of their randomness is determined by these applications: for example those with security requirements need very good random numbers while simulations have fewer constraints on their properties.
Mathilde Soucarros +4 more
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[Intel random number generator-based true random number generator].
Di 1 jun yi da xue xue bao = Academic journal of the first medical college of PLA, 2007To establish a true random number generator on the basis of certain Intel chips.The random numbers were acquired by programming using Microsoft Visual C++ 6.0 via register reading from the random number generator (RNG) unit of an Intel 815 chipset-based computer with Intel Security Driver (ISD).We tested the generator with 500 random numbers in NIST ...
Feng, Huang, Hong, Shen
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Physical true random number generator
Chinese Science Bulletin, 2009The requirement of physical true random number generator and the difference between the true random number and pseudo-random number are presented. The recent experiements of true ran-dom number generator, expetically, the various schemes of true random number generator based on lasers, are summarized.
Yu LIU, Hong GUO, AnHong WEI Wei DANG
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An Analysis of DCM-Based True Random Number Generator
IEEE Transactions on Circuits and Systems II: Express Briefs, 2020A true random number generator (TRNG) using Digital clock manager (DCM) blocks of a Xilinx FPGA has advantages of minimal usage of logic elements and tunability of clock frequencies to search for better randomness. Its operating principle is beat frequency detection, which uses the least significant bits (LSBs) of a counter that counts the number of ...
Naoki Fujieda +2 more
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