Title
PUF Modeling Attacks on Simulated and Silicon Data
Abstract
We discuss numerical modeling attacks on several proposed strong physical unclonable functions (PUFs). Given a set of challenge-response pairs (CRPs) of a Strong PUF, the goal of our attacks is to construct a computer algorithm which behaves indistinguishably from the original PUF on almost all CRPs. If successful, this algorithm can subsequently impersonate the Strong PUF, and can be cloned and distributed arbitrarily. It breaks the security of any applications that rest on the Strong PUF's unpredictability and physical unclonability. Our method is less relevant for other PUF types such as Weak PUFs. The Strong PUFs that we could attack successfully include standard Arbiter PUFs of essentially arbitrary sizes, and XOR Arbiter PUFs, Lightweight Secure PUFs, and Feed-Forward Arbiter PUFs up to certain sizes and complexities. We also investigate the hardness of certain Ring Oscillator PUF architectures in typical Strong PUF applications. Our attacks are based upon various machine learning techniques, including a specially tailored variant of logistic regression and evolution strategies. Our results are mostly obtained on CRPs from numerical simulations that use established digital models of the respective PUFs. For a subset of the considered PUFs—namely standard Arbiter PUFs and XOR Arbiter PUFs—we also lead proofs of concept on silicon data from both FPGAs and ASICs. Over four million silicon CRPs are used in this process. The performance on silicon CRPs is very close to simulated CRPs, confirming a conjecture from earlier versions of this work. Our findings lead to new design requirements for secure electrical Strong PUFs, and will be useful to PUF designers and attackers alike.
Year
DOI
Venue
2013
10.1109/TIFS.2013.2279798
IEEE Transactions on Information Forensics and Security
Keywords
DocType
Volume
cryptography,application specific integrated circuits,evolutionary computation,regression analysis,learning artificial intelligence,field programmable gate arrays
Journal
8
Issue
ISSN
Citations 
11
1556-6013
123
PageRank 
References 
Authors
3.87
24
10
Search Limit
100123
Name
Order
Citations
PageRank
Ulrich Rührmair168538.92
Jan Sölter242618.21
Frank Sehnke352739.18
Xiaolin Xu426825.21
Ahmed Mahmoud51656.62
Vera Stoyanova61285.36
Gideon Dror71761104.44
Jürgen Schmidhuber8178361238.63
W. Burleson92190208.72
Srinivas Devadas1086061146.30