High-Speed Magnetoresistive Random-Access Memory Random Number Generator Using Error-Correcting Code

Tanamoto, Tetsufumi; Shimomura, N.; Ikegawa, S.; Matsumoto, Masaaki; Fujita, Shinobu; Yasuda, Hiroaki

doi:10.7567/jjap.50.04dm01

Cited by 4 publications

(1 citation statement)

References 8 publications

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“…Spin transfer switching (STS) is essential in MTJs for enabling spintronic applications with low-power write operations [3], [5]. The STS stochastically occurs under a particular bias current, thus, a random number generator for secure information was proposed and demonstrated [6], [7]. There is an increasing need for better hardware security to defend against semiconductor device counterfeiting, theft of service, and tampering, and secure cryptographic key storage is an essential part of such security.…”

Section: Introductionmentioning

confidence: 99%

Extracting Physically Unclonable Function From Spin Transfer Switching Characteristics in Magnetic Tunnel Junctions

2014

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Hardware security devices that include physically unclonable function (PUF) hold significant advantages over software-based secure identification and key storage. We propose a PUF for magnetic tunnel junctions (MTJs) and a method for extracting PUF based on intrinsic properties of spin transfer switching (STS). The STS characteristics of MTJs with perpendicular layers were measured and analyzed to determine how to extract PUF properties. Given the experimental intrinsic stochastic properties combined with the proposed sequence, we discuss the PUF properties extracted from MTJs. To realize secure hardware key in non-volatile devices, our methods and results are promising for constructing MTJ-PUF based on spintronic LSI devices.Index Terms-Magnetic tunnel junctions (MTJs), physically unclonable functions (PUFs), spin transfer switching (STS).

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Section: Introductionmentioning

confidence: 99%

Extracting Physically Unclonable Function From Spin Transfer Switching Characteristics in Magnetic Tunnel Junctions

2014

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Spintronics and Security: Prospects, Vulnerabilities, Attack Models, and Preventions

Ghosh

2016

Proc. IEEE

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A 126 μW Readout Circuit in 65 nm CMOS With Successive Approximation-Based Thresholding for Domain Wall Magnet-Based Random Number Generator

et al. 2020

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We present a novel readout circuit for a ferromagnetic Hall cross-bar based random number generator. The random orientation of magnetic domains are result of anomalous Hall-effect. These ferromagnetic Hall cross-bar structures can be integrated with the read out circuit to form a plug and play random number generator. The system can resolve up to 15-20 µV Hall-voltages from Hall probe. Application of current densities around 10 12 A/m 2 through the Ferromagnetic Hall cross-bar produces random Hall-voltage on the output terminals. To amplify the weak Hall-voltages (10-100 µV) in the presence of DC offsets, a modulation scheme is used to up-convert the signal and a band-pass amplifier is used to amplify the modulated signal. The band-pass amplifier circuit, motivated by neural recording amplifier is designed in 65nm CMOS and consumes 126 µW of power from a 1.2 V supply. Further, we present a successive approximation algorithm and its embedded implementation to set the desired threshold for digitizing the amplified Hall-voltage in presence of signal drift. Experimental results show that the resulting system can tolerate drifts in voltage up to 440 µV. I. INTRODUCTIONRandom bit streams find application in generating keys in cryptography and initialization of parameters in a encrypted communication protocols. Random number generators are useful in realising Physically Unclonable Function (PUF) in microprocessors [1], [2]. These streams are also useful in stochastic simulations, gaming and events where random sampling is required. Random number generators can be divided into two classes based on their source, namely true random number generator (TRNG) and pseudo random number generator (PRNG). TRNG generates randomness from inherent stochastic physical feature of the source. On the other hand PRNG generates lengthy stream of digital bits which are difficult to predict. Most on-chip TRNG of present day use techniques like sampling of thermal noise [3] or exploiting meta stability of latching circuits [4]. Recently, magnetic random number generators (MRNG) have been proposed which *Corresponding Author is Arindam Basu. Equal contribution of Govind and Joydeep.

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High-Speed Magnetoresistive Random-Access Memory Random Number Generator Using Error-Correcting Code

Cited by 4 publications

References 8 publications

Extracting Physically Unclonable Function From Spin Transfer Switching Characteristics in Magnetic Tunnel Junctions

Extracting Physically Unclonable Function From Spin Transfer Switching Characteristics in Magnetic Tunnel Junctions

Spintronics and Security: Prospects, Vulnerabilities, Attack Models, and Preventions

A 126 μW Readout Circuit in 65 nm CMOS With Successive Approximation-Based Thresholding for Domain Wall Magnet-Based Random Number Generator

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