We show in this paper how several proposed Physical Unclonable Functions (PUFs) can be broken by numerical modeling attacks. Given a set of challenge-response pairs (CRPs) of a PUF, our attacks construct a computer algorithm which behaves indistinguishably from the original PUF on almost all CRPs. This algorithm can subsequently impersonate the PUF, and can be cloned and distributed arbitrarily. This breaks the security of essentially all applications and protocols that are based on the respective PUF. The PUFs we attacked successfully include standard Arbiter PUFs and Ring Oscillator PUFs of arbitrary sizes, and XOR Arbiter PUFs, Lightweight Secure PUFs, and FeedForward Arbiter PUFs of up to a given size and complexity. Our attacks are based upon various machine learning techniques, including Logistic Regression and Evolution Strategies. Our work leads to new design requirements for secure electrical PUFs, and will be useful to PUF designers and attackers alike.
For example, Arbiter PUFs, Ring Oscillator PUFs, XOR Arbiter PUFs, Lightweight Secure PUFs and FeedForward Arbiter PUFs have all been attacked by Rührmair et al. using machine learning techniques REF .
Modeling attacks on physical unclonable functions
CCS '10
Computer Science