A novel design method for discrete time chaos based true random number generators

Cicek, Ihsan; Pusane, Alí Emre; Dündar, Günhan

doi:10.1016/j.vlsi.2013.06.003

Cited by 88 publications

(35 citation statements)

References 21 publications

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“…TRNGs extract entropy from processes that are unpredictable, such as physical events like radioactive decay [1], thermal noise [2,3], electrical noise [4,5], lasers [6,7] and quantum randomness [8]. Some TRNGs take advantage of human characteristics, extracting entropy from mouse movement [9,10], keystrokes [11] or biometric signatures [12,13].…”

Section: Introductionmentioning

confidence: 99%

GPUs and chaos: a new true random number generator

et al. 2015

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For applications where security and unpredictability is of utmost importance, true random number generators (TRNGs) play a heavy role compared to its pseudo-random counterparts. Most TRNGs obtain randomness from physical phenomena such as radio noise, radioactive decay or thermal noise that are unpredictable. These applications usually require external hardware to extract entropy and convert them into digital signals. This paper introduces a TRNGs that utilizes graphics processing units as the source of entropy. Its unpredictable behavior is harnessed by computing chaotic maps that are highly sensitive to slight changes to their control parameters and have pseudo-random behavior. A simple post-processing function based on modular addition and XOR is then used to achieve an unbiased output. The security of the proposed TRNG is evaluated using statistical test suites such as the NIST SP 800-22, DIEHARD and ENT, as well as entropy analysis to determine unpredictability. Results indicate that the proposed TRNG has strong statistical quality

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Section: Introductionmentioning

confidence: 99%

GPUs and chaos: a new true random number generator

et al. 2015

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“…A designer can only control device dimensions, layout, and bias point to deal with matching [7]. The circuits used to implement map equations has to operate with high accuracy since any device mismatch induced blind region in the state space of a chaotic map translates into randomness loss [8]. In a simple current mirror, accuracy is bias point, and device area dependent as pointed out by…”

Section: A Design Of the Bernoulli And Tent Map Circuitsmentioning

confidence: 99%

“…7 has been designed for driving the chaotic dynamics of the map circuits. In [8], we estimated the maximum allowable parameter variances using mathematical modeling, and T-entropy calculations. Required device area can be calculated using (5), and estimated variance.…”

Section: B Design Of the Sample And Hold Circuitmentioning

confidence: 99%

An Integrated Dual Entropy Core True Random Number Generator

Cicek

Pusane

Dündar

2017

IEEE Trans. Circuits Syst. II

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In this work, we present the first integrated circuit implementation of our previously proposed dual entropy core TRNG architecture, which is designed following a novel parameter variation-aware approach. A prototype integrated circuit has been fabricated in 180nm CMOS technology. Prototype chip achieved 35Mbps throughput with approximately 33pJ/bit energy efficiency. Random numbers acquired from the prototype chip have successfully passed all NIST 800.22 statistical tests without requiring any post-processing.

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“…Table I shows PL1D maps recently used for the purpose of truly random generation [14,17,18]. The paper is organized as follows.…”

Section: Introductionmentioning

confidence: 99%

A switched‐capacitor skew‐tent map implementation for random number generation

Valtierra

Tlelo‐Cuautle

Rodríguez-Vázquez

2016

Circuit Theory & Apps

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Piecewise linear one-dimensional maps have been proposed as the basis for low-power analog and mixedsignal true random number generators (TRNGs). Recent research has moved towards conceiving maps that operate robustly under the consideration of parameter variations. In this paper, we introduce an oscillator circuit mapping a low-complexity map known as the skew-tent. This oscillator is employed as the basis for a TRNG scheme. Simulation results in TSMC 0.18 m validate the chaotic oscillator and the randomness of the TRNG scheme is verified with the NIST test suite 800-22.

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A novel design method for discrete time chaos based true random number generators

Cited by 88 publications

References 21 publications

GPUs and chaos: a new true random number generator

GPUs and chaos: a new true random number generator

An Integrated Dual Entropy Core True Random Number Generator

A switched‐capacitor skew‐tent map implementation for random number generation

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