Over the recent years, the explosive growth of digital technologies allowed to implement disruptive business models driven by data collection and processing. In particular, the internet of things (IoT), where massive number of “things” (sensors, actuators, drones, etc.) interact with the environment and with each other, unlocks a significant value for consumers (smart society), organisations/companies (industry 4.0/ smart factories) and governments (smart nations). However, as every adoption of new technologies involves some risks, security attacks are today one of the biggest challenges for IoT. The overall inflicted damages of cybercrime in 2021, in fact, have an estimated total of $6 trillion which makes Cybercrime one of the world’s largest economy comparable to U.S. and China. Security of IoT is generally enabled by the physical unclonable function (PUF), namely a hardware function which is embedded in the chip and capable of generating a random response to a given challenge. Recently, PUFs based on emerging nonvolatile memory have attracted a strong interest thanks to their high scalability, high density, low cost and good integration with CMOS technology. However, NVM with high resistance to tampering and high reliability to temperature variations are not available yet.
The objective of this project is to demonstrate the feasibility of an invisible PUF (iPUF) based on a nonvolatile memory with stochastic states which cannot be identified externally from optical or magnetic microsensors. The iPUF relies on (i) a stochastic nonvolatile memory technology, (ii) an efficient algorithm capable of generating a PUF response from an applied challenge with high reliability to temperature variations and resistance to tampering.