A novel Physical Unclonable Function using RTN

PUFs have emerged as an alternative to traditional Non-Volatile Memories in the field of hardware security. In this paper, a novel PUF is proposed that uses the Random Telegraph Noise phenomenon as the underlying source of entropy. This phenomenon manifests as discrete and random shifts in the drain current of transistors and it is characterized by several parameters like the number of the defects in the device, as well as the emission and capture time constants and current shifts of these defects. Using the recently reported Maximum Current Fluctuation metric, it is possible to condense all this information and use it for the PUF design. By forming pairs of transistors, measuring, and comparing their Maximum Current Fluctuation over a given time interval, we demonstrate using numerical experiments that it is possible to obtain a PUF. Furthermore, the results reported here show that this RTN-based PUF matches, and even out-performs, other silicon PUFs in terms of uniqueness, unpredictability, and reliability with an evident advantage in silicon area.

I. Introduction

Nowadays, Non-Volatile Memories (NVMs) are widely used as a method to store keys and thus secure sensitive information. However, threats like counterfeiting, reverse engineering, and tampering [1] are becoming serious concerns for the security protocols using NVMs, putting at risk the information stored. In this scenario, Physical Unclonable Functions or PUFs arise as an alternative to traditional NVMs for their superior resilience to attacks, higher flexibility, and lower costs [2]. This is an especially attractive solution in hardware-constrained applications like IoT (where power and area are limited). PUFs are physical objects (e.g., an integrated circuit) that generate a physically defined response (output) for a given challenge (input) in a manner that is specific to the exact hardware instance impossible to replicate. Such response is used, for instance, to authenticate any object the PUF instance is attached to: at the end of the manufacturing process, a collection of PUF instances is given a set of challenges and each response recorded; at any later moment, a PUF instance is given the same challenge and, if the response coincides with the one stored, the PUF instance is the manufactured one [3].