Physically Unclonable Functions and AI: Two Decades of Marriage

The current chapter aims at establishing a relationship between artificial intelligence (AI) and hardware security. Such a connection between AI and software security has been confirmed and well-reviewed in the relevant literature. The main focus here is to explore the methods borrowed from AI to assess the security of a hardware primitive, namely physically unclonable functions (PUFs), which has found applications in cryptographic protocols, e.g., authentication and key generation. Metrics and procedures devised for this are further discussed. Moreover, By reviewing PUFs designed by applying AI techniques, we give insight into future research directions in this area

Novel Randomized Placement for FPGA Based Robust ROPUF with Improved Uniqueness

The physical unclonable functions (PUF) are used to provide software as well as hardware security for the cyber-physical systems. They have been used for performing significant cryptography tasks such as generating keys, device authentication, securing against IP piracy, and to produce the root of trust as well. However, they lack in reliability metric. We present a novel approach for improving the reliability as well as the uniqueness of the field programmable gated arrays (FPGAs) based ring oscillator PUF and derive a random number, consuming very small area (< 1%) concerning look-up tables (LUTs). We use frequency profiling method for distributing frequency variations in ring oscillators (RO), spatially placed all across the FPGA floor. We are able to spot suitable locations for RO mapping, which leads to enhanced ROPUF reliability. We have evaluated the proposed methodology on Xilinx -7 series FPGAs and tested the robustness against environmental variations, e.g. temperature and supply voltage variations, simultaneously. The proposed approach achieves significant improvement (i) in uniqueness value upto 49:90%, within 0.1% of the theoretical value (ii) in the reliability value upto 99:70%, which signifies that less than 1 bit flipping has been observed on average, and (iii) in randomness, signified by passing NIST test suite. The response generated through the ROPUF passes all the applicable relevant tests of NIST uniformity statistical test suite