A true Random Number Generator using RTN noise and a sigma delta converter

Figliolia, Tomas; Julián, P.; Tognetti, Gaspar; Andreou, Andreas G.

doi:10.1109/iscas.2016.7527159

Cited by 16 publications

(8 citation statements)

References 6 publications

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“…The design of Figliolia et al 53 does have potentially greater generation rate, but is significantly more complex and requires a lot more design area when implemented onto an IC. Also, Figliolia's design was not tested using the DIEHARD or NIST test suite, so the randomness of the generated bitstream is not verified.…”

Section: Discussionmentioning

confidence: 99%

Random-telegraph-noise-enabled true random number generator for hardware security

Brown

Zhang

Zhou

et al. 2020

Sci Rep

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The future security of Internet of Things is a key concern in the cyber-security field. One of the key issues is the ability to generate random numbers with strict power and area constrains. “True Random Number Generators” have been presented as a potential solution to this problem but improvements in output bit rate, power consumption, and design complexity must be made. In this work we present a novel and experimentally verified “True Random Number Generator” that uses exclusively conventional CMOS technology as well as offering key improvements over previous designs in complexity, output bitrate, and power consumption. It uses the inherent randomness of telegraph noise in the channel current of a single CMOS transistor as an entropy source. For the first time multi-level and abnormal telegraph noise can be utilised, which greatly reduces device selectivity and offers much greater bitrates. The design is verified using a breadboard and FPGA proof of concept circuit and passes all 15 of the NIST randomness tests without any need for post-processing of the generated bitstream. The design also shows resilience against machine learning attacks performed by the LSTM neural network.

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Section: Discussionmentioning

confidence: 99%

Random-telegraph-noise-enabled true random number generator for hardware security

Brown

Zhang

Zhou

et al. 2020

Sci Rep

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“…Recently, the presence of RTN signals in RRAM devices has drawn attention, as their inherent randomness can be exploited as a possible source of entropy for RNG circuits [24][25]. Nevertheless, a proper design of such circuits can be attained only by introducing suitable compact models, as the one proposed in this work.…”

Section: Design Of An Rtn-based Rng Circuitmentioning

confidence: 99%

“…In addition, RNGs and PUFs performances can be adversely affected by RTN, worsening their figures of merit (e.g., randomness). Nevertheless, it has been suggested [24][25] to exploit the intrinsic randomness of RTN as an entropy source to realize RTN-based PUFs and RNGs, which could open new interesting perspectives. Finally, RRAM-based temperature sensors that exploit RTN have been proposed [26].…”

Section: Introduction He Relentless Scaling Of Complementary Metal Oxidementioning

confidence: 99%

Random Telegraph Noise in Resistive Random Access Memories: Compact Modeling and Advanced Circuit Design

Puglisi

Zagni

Larcher

et al. 2018

IEEE Trans. Electron Devices

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In this work we report about the derivation of a physics-based compact model of Random Telegraph Noise (RTN) in HfO2-based Resistive Random Access Memory (RRAM) devices. Starting from the physics of charge transport, which is different in the high and low resistive states (HRS and LRS), we explore the mechanisms responsible for RTN exploiting a hybrid approach, based on self-consistent physics simulations and geometrical simplifications. Then, we develop a simple yet effective physics-based compact model of RTN valid in both states, which can be steadily integrated in state-of-the-art RRAM compact models. The RTN compact model predictions are validated by comparison with both a large experimental dataset obtained by measuring RRAM devices in different conditions, and data reported in the literature. In addition, we show how the model enables advanced circuit simulations by exploring three different circuits for memory, security, and logic applications.

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“…Random telegraph noise (RTN) has recently attracted a growing attention as probabilistic and relatively strong source of noise [15]. RTN has been studied in various types of devices including FETs [16][17][18][19], carbon nanotube transistors (CNTs) [20] and broad class of resistive switching memories [21][22][23][24][25][26].…”

Section: Introductionmentioning

confidence: 99%

Nano-Intrinsic True Random Number Generation: A Device to Data Study

Kim

Nili

Truong

et al. 2019

IEEE Trans. Circuits Syst. I

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Recent advances in predictive data analytics and ever growing digitalization and connectivity with explosive expansions in industrial and consumer Internet-of-Things (IoT) has raised significant concerns about security of people's identities and data. It has created close to ideal environment for adversaries in terms of the amount of data that could be used for modeling and also greater accessibility for side-channel analysis of security primitives and random number generators. Random number generators (RNGs) are at the core of most security applications. Therefore, a secure and trustworthy source of randomness is required to be found. Here, we present a differential circuit for harvesting one of the most stochastic phenomenon in solidstate physics, random telegraphic noise (RTN), that is designed to demonstrate significantly lower sensitivities to other sources of noises, radiation and temperature fluctuations. We use RTN in amorphous SrTiO3-based resistive memories to evaluate the proposed true random number generator (TRNG). Successful evaluation on conventional true randomness tests (NIST tests) has been shown. Robustness against using predictive machine learning and side-channel attacks have also been demonstrated in comparison with non-differential readouts methods.

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A true Random Number Generator using RTN noise and a sigma delta converter

Cited by 16 publications

References 6 publications

Random-telegraph-noise-enabled true random number generator for hardware security

Random-telegraph-noise-enabled true random number generator for hardware security

Random Telegraph Noise in Resistive Random Access Memories: Compact Modeling and Advanced Circuit Design

Nano-Intrinsic True Random Number Generation: A Device to Data Study

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