A Lightweight Design of True Random Number Generator Based on Superparamagnetic Tunnel Junction

With the rapid development of artificial intelligence (AI), a variety of attack techniques have emerged, threatening the data security. In this background, energy-efficient lightweight security primitives are required to guarantee the security of the Internet of Things (IoT). The conventional silicon-based true random number generator (TRNG) suffers from design complexity, high power consumption, and limited throughput, making it unsuitable for low-power and high-performance applications. Magnetic tunnel junctions (MTJs) can be used as a random source due to the random switching behaviors. However, most of the existing MTJ-based TRNG designs rely on reset–write–read operations, which limit throughput and energy efficiency. In this work, we propose a high-throughput TRNG based on the superparamagnetic tunnel junction (SMTJ). By reducing the thermal stability factor, SMTJ undergoes spontaneous random switching driven by thermal fluctuation, eliminating the need for costly reset and write operations. A compact spin-orbit torque (SOT)controlled SMTJ model is developed and integrated by using the NAND-SPIN structure, achieving a TRNG design with low power, high throughput, and high randomness.