DESIGN AND IMPLEMENTATION OF PUFS FOR AUTOMOTIVE APPLICATIONS

Abstract

The automotive industry has undergone remarkable changes in recent times, characterized by an emphasis on the integration of complex electronic systems into vehicles. The goal of this evolution is to improve user experience, security and performance. However, this has also brought new challenges in ensuring the safety and reliability of automotive systems. To overcome these obstacles, this thesis focuses on creating Physical Unclonable Functions (PUFs) based on Field Programmable Gate Arrays (FPGAs) that are specifically suited for automotive applications. Since PUFs are inherently unpredictable and unique, they present a promising option for safe hardware authentication and protection against a wide range of security risks. This study investigates the architectural layout, methods of application and the fundamental ideas behind FPGA-based PUFs. The proposed PUF design produces 128-bit distinct and unclonable identifiers (IDs) by utilizing the inherent manufacturing variances of FPGAs and provides a strong security measure. Thorough testing that extends the three standard performance metrics of uniqueness, uniformity, and reliability shows how well the implemented PUF design satisfies the demanding security and performance standards of automotive systems. Resource utilization analysis highlights the design’s suitability for the resource-constrained automotive applications by revealing its efficiency in terms of power and FPGA resource consumption. The thesis also suggests future directions for investigation, such as the development of advanced error correction methods to increase the dependability of PUF responses, scalability improvements, and the integration of the PUF design with different automotive subsystems. This thesis adds to the body of knowledge in the field of automotive security by providing a novel method for utilizing FPGA-based PUFs to improve the security infrastructure of contemporary vehicles through a thorough investigation and empirical evaluation. The study’s findings will have a major impact on the automotive industry and help create safer, more reliable and trustworthy automotive systems.