Process Variation-Resilient STT-MTJ based TRNG using Linear Correcting Codes

Abstract

With the increasing applications of artificial intelligence (AI) attacks, the requirement for high-quality security system becomes urgent. True random number generator (TRNG) is the core block of many cryptographic systems, of which the security is determined by the randomness source of TRNG. In this paper, stochastic switching behavior of spin transfer torque magnetic tunnel junction (STT-MTJ) device is exploited for generation of random numbers. Stochastic switching of STT-MTJ provides an excellent physical randomness source. However, due to the limited technology and correlation between different process steps, process variation has a significant impact on the randomness of MTJ based TRNG. Therefore, post processing-based control mechanism is also necessary to guarantee reliable randomness. The method of linear corrector is integrated into STT-MTJ based TRNG, resulting in improved entropy of randomness. The design is implemented by a 40nm CMOS technology and a compact model of the MTJ. By using the output random bitstream with and without process variations, the efficiency of linear corrector is demonstrated by passing the National Institute of Standards and Technology (NIST) statistical test suite.