Memory circuit elements for hardware security: a review from memristors to memcapacitors and meminductors

Abstract

The security of modern electronic systems is increasingly grounded in the physical properties of hardware, rather than on purely algorithmic assumptions. In this context, passive circuit elements with memory, commonly referred to as mem-elements, have emerged as promising candidates for implementing hardware-based security primitives. Among them, memristors, as the most experimentally mature devices, have demonstrated significant potential in Physical Unclonable Functions (PUFs) and True Random Number Generators (TRNGs) by exploiting their intrinsic variability, nonlinearity, and history-dependent behavior. By contrast, memcapacitors and meminductors, which extend memory effects to energy-storing electrical and magnetic domains, remain largely unexplored in security applications, despite their richer dynamical structure and greater theoretical potential for entropy generation and resistance to inference. This mini-review provides a structured overview of the state of the art of mem-elements in hardware security, highlighting the differences in dynamical behavior and security-relevant properties across memristors, memcapacitors, and meminductors. The review identifies key limitations of current approaches based on static or low-dimensional variability, discusses the implications of machine-learning-based modelling attacks, and outlines open research challenges associated with the limited availability of memcapacitive and meminductive devices. Finally, it explores the potential of coupled memcapacitor–meminductor systems as a fundamentally new platform for entropy-driven and dynamically evolving security primitives, opening promising directions for next-generation hardware security.