An Asynchronous and Low-Power True Random Number Generator Using STT-MTJ

Ben Perach,Shahar Kvatinsky

doi:10.1109/tvlsi.2019.2927816

Abstract

The emerging spin-transfer torque magnetic tunnel junction (STT-MTJ) technology exhibits interesting stochastic behavior combined with small area and low operation energy. It is, therefore, a promising technology for security applications, specifically the generation of random numbers. In this paper, STT-MTJ is used to construct an asynchronous true random number generator (TRNG) with low power and a high entropy rate. The asynchronous design enables the decoupling of the random number generation from the system clock, allowing it to be embedded in low-power devices. The proposed TRNG is evaluated by a numerical simulation, using the Landau–Lifshitz–Gilbert (LLG) equation as the model of the STT-MTJ devices. Design considerations, attack analysis, and process variation are discussed and evaluated. We show that our design is robust to process variation, thus achieving an entropy generating rate between 99.7 and 127.8 Mb/s with 6–7.7 pJ per bit for 90% of the instances.

Highlights

S ECURITY is a major concern in modern digital systems
A cryptographic key generated by a PRNG might compromise the encryption since the PRNG outputs are inherently connected [3]–[5], some PRNGs are considered to be sufficiently secured for cryptographic use [22], [23]
We evaluated our true random number generator (TRNG) with Monte Carlo simulations for the Enable step for different topologies, each with a different number of magnetic tunnel junction (MTJ) devices

Summary

Introduction

S ECURITY is a major concern in modern digital systems. One of the main tools used in security is cryptography, which is used to encode information that only authorized entities can access. Changing the cryptographic algorithm or its assumptions, even to a limited extent, can compromise the entire system. One such crucial part of cryptographic algorithms is the generation of the cryptographic keys [1]–[5]. The algorithm itself is assumed to be publicly known, and the key is the only missing information needed to reveal the encrypted data [2]. A cryptographic key generated by a PRNG might compromise the encryption since the PRNG outputs are inherently connected [3]–[5], some PRNGs are considered to be sufficiently secured for cryptographic use [22], [23]. The output of the TRNG can only be predicted according to the physical process probability distribution, even if all the information about the system (register values, voltage levels, and so on) is known prior to the TRNG operation

Methods

Results

Conclusion