Splitting the Interpose PUF: A Novel Modeling Attack Strategy


  • Nils Wisiol Technische Universität Berlin, Germany; Freie Universität Berlin, Germany
  • Christopher Mühl Freie Universität Berlin, Germany
  • Niklas Pirnay Technische Universität Berlin, Germany
  • Phuong Ha Nguyen University of Connecticut, USA
  • Marian Margraf Freie Universität Berlin, Germany
  • Jean-Pierre Seifert Technische Universität Berlin, Germany
  • Marten van Dijk University of Connecticut, USA; CWI Amsterdam, Netherlands
  • Ulrich Rührmair University of Connecticut, USA; LMU München, Germany




Physical Unclonable Function, Strong PUFs, Machine Learning, Modeling Attacks, Interpose PUF (iPUF)


We demonstrate that the Interpose PUF proposed at CHES 2019, an Arbiter PUF-based design for so-called Strong Physical Unclonable Functions (PUFs), can be modeled by novel machine learning strategies up to very substantial sizes and complexities. Our attacks require in the most difficult cases considerable, but realistic, numbers of CRPs, while consuming only moderate computation times, ranging from few seconds to few days. The attacks build on a new divide-and-conquer approach that allows us to model the two building blocks of the Interpose PUF separately. For non-reliability based Machine Learning (ML) attacks, this eventually leads to attack times on (kup, kdown)-Interpose PUFs that are comparable to the ones against max{kup, kdown}-XOR Arbiter PUFs, refuting the original claim that Interpose PUFs could provide security similar to (kdown + kup/2)-XOR Arbiter PUFs (CHES 2019). On the technical side, our novel divide-and-conquer technique might also be useful in analyzing other designs, where XOR Arbiter PUF challenge bits are unknown to the attacker.




How to Cite

Wisiol, N., Mühl, C., Pirnay, N., Nguyen, P. H., Margraf, M., Seifert, J.-P., … Rührmair, U. (2020). Splitting the Interpose PUF: A Novel Modeling Attack Strategy. IACR Transactions on Cryptographic Hardware and Embedded Systems, 2020(3), 97–120. https://doi.org/10.13154/tches.v2020.i3.97-120