Estimating the Unpredictability of Multi-Bit Strong PUF Classes

ePrint Report: Estimating the Unpredictability of Multi-Bit Strong PUF Classes

Ahmed Bendary, Wendson A. S. Barbosa, Andrew Pomerance, C. Emre Koksal

With the ongoing advances in machine learning (ML), cybersecurity solutions and security primitives are becoming increasingly vulnerable to successful attacks. Strong physically unclonable functions (PUFs) are a potential solution for providing high resistance to such attacks. In this paper, we propose a generalized attack model that leverages multiple chips jointly to minimize the cloning error. Our analysis shows that …

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