Applicability of Well-Established Memristive Models for Simulations of Resistive Switching Devices

Highly accurate and predictive models of resistive switching devices are needed to enable future memory and logic design. Widely used is the memristive modeling approach considering resistive switches as dynamical systems. Here we introduce three evaluation criteria for memristor models, checking for plausibility of the I-V characteristics, the presence of a sufficiently non-linearity of the switching kinetics, and the feasibility of predicting the behavior of two anti-serially connected devices correctly. We analyzed two classes of models: the first class comprises common linear memristor models and the second class widely used non-linear memristive models. The linear memristor models are based on Strukovs initial memristor model extended by different window functions, while the non-linear models include Picketts physics-based memristor model and models derived thereof. This study reveals lacking predictivity of the first class of models, independent of the applied window function. Only the physics-based model is able to fulfill most of the basic evaluation criteria.Comment: 9 pages; accepted for IEEE TCAS-

Memristive crypto primitive for building highly secure physical unclonable functions

Physical unclonable functions (PUFs) exploit the intrinsic complexity and irreproducibility of physical systems to generate secret information. The advantage is that PUFs have the potential to provide fundamentally higher security than traditional cryptographic methods by preventing the cloning of devices and the extraction of secret keys. Most PUF designs focus on exploiting process variations in Complementary Metal Oxide Semiconductor (CMOS) technology. In recent years, progress in nanoelectronic devices such as memristors has demonstrated the prevalence of process variations in scaling electronics down to the nano region. In this paper, we exploit the extremely large information density available in nanocrossbar architectures and the significant resistance variations of memristors to develop an on-chip memristive device based strong PUF (mrSPUF). Our novel architecture demonstrates desirable characteristics of PUFs, including uniqueness, reliability, and large number of challenge-response pairs (CRPs) and desirable characteristics of strong PUFs. More significantly, in contrast to most existing PUFs, our PUF can act as a reconfigurable PUF (rPUF) without additional hardware and is of benefit to applications needing revocation or update of secure key information.Yansong Gao, Damith C. Ranasinghe, Said F. Al-Sarawi, Omid Kavehei, Derek Abbot