A Probability-Based Strong Physical Unclonable Function With Strong Machine Learning Immunity

Zezhong Tu,Meng Li,Ru Huang,Runsheng Wang,Jianfu Zhang,Yongkang Xue,Pengpeng Ren,Zhigang Ji,Feng Hao

doi:10.1109/led.2021.3130606

A Probability-Based Strong Physical Unclonable Function With Strong Machine Learning Immunity

Zezhong Tu, Meng Li + Show 7 more

Open Access

https://doi.org/10.1109/led.2021.3130606

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Journal: IEEE Electron Device Letters	Publication Date: Jan 1, 2022
License type: publisher-specific, author manuscript

Affiliation: Shanghai Jiao Tong University, The University of Texas at Austin, Peking University, Institute of Microelectronics, University of Warwick

#Physical Unclonable Function #Strong Physical Unclonable Function + Show 8 more

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Abstract

A novel strong physical unclonable function (PUF), called Probability-based PUF (Prob-PUF), is proposed using the stochastic process of trap emission in nano-scaled transistors. For the first time, the information of trap emission probability is used in the PUF design. This new approach offers ideal immunity to machine learning (ML) attacks. Since Prob-PUF only stores a mathematical model, it naturally avoids the dilemma between the requirement of a large number of challenge-response pairs (CRPs) and the limited storage space, making it a potential solution for future secure storage.

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