Design, build, and analyse hardware-based security primitives that work well

Abstract

Hardware security has drawn more and more attention in both academia and business over the past two decades. Flash memory has received attention recently due to the debate over whether or not it can serve a security purpose. Flash memory modules have been suggested as sites for hardware security primitives because of their intrinsic process diversity, which can offer a distinctive fingerprint for a device. These primitives include true random number generators (TRNGs), physical unlovable functions (PUFs), and integrated circuit (IC) counterfeit detection Hardware-based security primitives are essential for preserving and securing a system in Internet of Things (loT) applications. The main primitives explored in this work are true random number generators (TRNG) and physically unlovable functions (PUF). The study makes recommendations for an efficient FPGA implementation and relevant security analysis using accepted criteria. The Internet of Things (loT) is a current innovative technology that is widespread and rapidly growing. The creation of an authenticated key agreement protocol is made possible by the application of designed TRNG and PUF. For a number of purposes, the internet will be connected to billions of new electronic gadgets. Along with the significant growth in the adoption and use of new technology, security weaknesses are multiplying swiftly. The Xilinx Spartan-3A FPGA can be seen as a grid of integrated Configurable Logic Blocks (CLBs) divided into four logical slices when it is deployed in the TRNG model arrangement. The delay control inputs for each sampling clock were arbitrarily adjusted to 8 discrete levels, and the outputs of these rings were all sampled at an external sampling frequency of 24 MHz.