True Random Number Generator With a Metastability-Based Quality Control

Tokunaga, Carlos; Blaauw, David; Mudge, T.

doi:10.1109/jssc.2007.910965

Cited by 149 publications

(26 citation statements)

References 5 publications

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“…It relies on intrinsic stochasticity in physical variables as a source of randomness. For example, thermal noise is often exploited by TRNGs via oscillator jitter 4 , resistor-amplifier-Analog/Digital converter chains 5 , or metastable elements with capacitive feedback 6 . Other approaches include using telegraph noise 7 , current fluctuation in oxide after soft breakdown 8 , or time-dependent oxide breakdown process 9 .…”

Section: Introductionmentioning

confidence: 99%

A novel true random number generator based on a stochastic diffusive memristor

et al. 2017

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The intrinsic variability of switching behavior in memristors has been a major obstacle to their adoption as the next generation of universal memory. On the other hand, this natural stochasticity can be valuable for hardware security applications. Here we propose and demonstrate a novel true random number generator utilizing the stochastic delay time of threshold switching in a Ag:SiO2 diffusive memristor, which exhibits evident advantages in scalability, circuit complexity, and power consumption. The random bits generated by the diffusive memristor true random number generator pass all 15 NIST randomness tests without any post-processing, a first for memristive-switching true random number generators. Based on nanoparticle dynamic simulation and analytical estimates, we attribute the stochasticity in delay time to the probabilistic process by which Ag particles detach from a Ag reservoir. This work paves the way for memristors in hardware security applications for the era of the Internet of Things.

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Section: Introductionmentioning

confidence: 99%

A novel true random number generator based on a stochastic diffusive memristor

et al. 2017

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“…This feature, however, is handy when we consider the random number generation procedure. conventional Trngs use the metastable state in cmos back-to-back inverter loop [18], [19] or they combine a fast clock with a slow jittery clock [20]. Both of these approaches, however, are vulnerable to process variations and mismatch.…”

Section: True Random Number Generatormentioning

confidence: 99%

Straintronics: A leap toward ultimate energy efficiency of magnetic random access memories

Barangi

Mazumder

2015

IEEE Nanotechnology Mag.

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“…However, cryptographic applications demand true randomness, so as to circumvent attacks based on predictability. True random bits are typically generated by sampling chaotic physical phenomena, such as thermal noise, quantummechanical measurement, meta-stability in latches, etc [19]. Such TRNGs are a major component in cryptographic applications and can be found in commercial ICs.…”

Section: On-chip True Random Number Generators (Trngs)mentioning

confidence: 99%

Epic

Roy

Koushanfar

Markov

2008

Proceedings of the Conference on Design, Automation and Test in Europe

426

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As semiconductor manufacturing requires greater capital investments, the use of contract foundries has grown dramatically, increasing exposure to mask theft and unauthorized excess production. While only recently studied, IC piracy has now become a major challenge for the electronics and defense industries [6].We propose a novel comprehensive technique to end piracy of integrated circuits (EPIC). It requires that every chip be activated with an external key, which can only be generated by the holder of IP rights, and cannot be duplicated. EPIC is based on (i) automatically-generated chip IDs, (ii) a novel combinational locking algorithm, and (iii) innovative use of public-key cryptography. Our evaluation suggests that the overhead of EPIC on circuit delay and power is negligible, and the standard flows for verificationand test do not require change. In fact, major required components have already been integrated into several chips in production. We also use formal methods to evaluate combinational locking and computational attacks. A comprehensive protocol analysis concludes that EPIC is surprisingly resistant to various piracy attempts.

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True Random Number Generator With a Metastability-Based Quality Control

Cited by 149 publications

References 5 publications

A novel true random number generator based on a stochastic diffusive memristor

A novel true random number generator based on a stochastic diffusive memristor

Straintronics: A leap toward ultimate energy efficiency of magnetic random access memories

Epic

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