PUF-ML: Machine Learning - Based Physical Unclonable Functions For Cost Effective Integration In Smart Healthcare

Physical Unclonable Functions (PUF) are hardwareassisted security (HAS) primitives that provide robust and lightweight security in Internet of Things (IoT) environments. PUF is a hardware module that can generate natural random numbers using the manufacturing variations introduced during Integrated Circuits (IC) fabrication. However, as a hardware module, it is difficult to integrate into legacy devices, or “things” deployed in the field. This paper presents a machine learningbased PUF, PUF-ML, which uses machine learning models to generate the keys at the devices. We use XOR-based PUF design to make it more resistant to machine learning attacks. The PUF can generate keys with a uniqueness of around $49 \%$ and a reliability of $98 \%$. This can help to integrate PUF in various environments, such as blockchain, where devices or “things” are already deployed in the environments.