A Dynamically Configurable PUF and Dynamic Matching Authentication Protocol

Yale Wang, Chenghua Wang, Chongyan Gu, Yijun Cui, Maire O'Neill, Weiqiang Liu

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Abstract

A physical unclonable function (PUF) is a hardware security primitive, which can be used secure various hardware-based applications. As a type of PUFs, strong PUFs have a large number of challenge-response pairs (CRPs), which can be used for authentication. At present, most strong PUF structures follow a one-to-one input/output relationship, i.e. linear function. As such, strong PUF designs are vulnerable to machine learning (ML) based modeling attacks. To address the issue, a dynamically configurable PUF structure is proposed in this paper. A mathematical model of the proposed dynamic PUF is presented and the design is proposed against the effective ML based attacks, such as deep neural network (DNN), logistic regression (LR) and reliability-based covariance matrix adaptation evolution strategies (CMA-ES). Experimental results on field programmable gate arrays (FPGAs) show that the proposed dynamic structure has achived good uniqueness and reliability. It is also shown that the dynamic PUF has a strong resistance to the CMA-ES attack. Due to the dynamic nature of the proposed PUF structure, an authentication protocol is also designed to generate recognizable authentication bits string. The protocol shows strong resistance to classical machine learning attacks including the new variant of CMA-ES.
Original languageEnglish
JournalIEEE Transactions on Emerging Topics in Computing (TETC)
Early online date12 Apr 2021
DOIs
Publication statusEarly online date - 12 Apr 2021

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