A Modeling Attack Resilient Physical Unclonable Function Based on STT-MRAM

Physical unclonable function (PUF) is considered as a promising hardware security primitive for a variety of applications. Recently, with the rapid development of integrated circuit (IC), the requirement for low complexity, high power efficiency and high performance PUFs become urgent. Moreover, a variety of powerful attack approaches have been carried out to counterfeit PUFs. This paper proposes a novel PUF design by utilizing the spin transfer torque magnetic random-access memory (STT-MRAM). The intrinsic process variation of STT-MRAM is exploited as an entropy source for generating PUF response. The primary performance metrics in terms of reliability, uniformity, uniqueness, and diffuseness of our proposed PUF have been verified, which validate its functionality. In addition, machine learning based modeling attacks are employed to evaluate the security level of proposed STT-MRAM based PUF (MPUF). The statistical results show that MPUF is much more immune to modeling attacks compared with the traditional Arbiter PUF.