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Lightweight obfuscation techniques for modeling attacks resistant PUFs

Lightweight obfuscation techniques for modeling attacks resistant PUFs
Lightweight obfuscation techniques for modeling attacks resistant PUFs
Building lightweight security for low-cost pervasive
devices is a major challenge considering the design requirements
of a small footprint and low power consumption. Physical Unclonable
Functions (PUFs) have emerged as a promising technology to
provide a low-cost authentication for such devices. By exploiting
intrinsic manufacturing process variations, PUFs are able to
generate unique and apparently random chip identifiers. Strong-
PUFs represent a variant of PUFs that have been suggested
for lightweight authentication applications. Unfortunately, many
of the Strong-PUFs have been shown to be susceptible to
modelling attacks (i.e., using machine learning techniques) in
which an adversary has access to challenge and response pairs.
In this study, we propose an obfuscation technique during postprocessing
of Strong-PUF responses to increase the resilience
against machine learning attacks. We conduct machine learning
experiments using Support Vector Machines and Artificial Neural
Networks on two Strong-PUFs: a 32-bit Arbiter-PUF and a 2-
XOR 32-bit Arbiter-PUF. The predictability of the 32-bit Arbiter-
PUF is reduced to ~ 70% by using an obfuscation technique.
Combining the obfuscation technique with 2-XOR 32-bit Arbiter-
PUF helps to reduce the predictability to ~ 64%. More reduction
in predictability has been observed in an XOR Arbiter-PUF
because this PUF architecture has a good uniformity. The area
overhead with an obfuscation technique consumes only 788 and
1080 gate equivalents for the 32-bit Arbiter-PUF and 2-XOR 32-
bit Arbiter-PUF, respectively.
IEEE
Mispan, Mohd Syafiq
568c91c3-c200-441c-887b-8f299635b94e
Halak, Basel
8221f839-0dfd-4f81-9865-37def5f79f33
Zwolinski, Mark
adfcb8e7-877f-4bd7-9b55-7553b6cb3ea0
Mispan, Mohd Syafiq
568c91c3-c200-441c-887b-8f299635b94e
Halak, Basel
8221f839-0dfd-4f81-9865-37def5f79f33
Zwolinski, Mark
adfcb8e7-877f-4bd7-9b55-7553b6cb3ea0

Mispan, Mohd Syafiq, Halak, Basel and Zwolinski, Mark (2017) Lightweight obfuscation techniques for modeling attacks resistant PUFs In 2nd International Verification and Security Workshop: IVSW 2017. IEEE..

Record type: Conference or Workshop Item (Paper)

Abstract

Building lightweight security for low-cost pervasive
devices is a major challenge considering the design requirements
of a small footprint and low power consumption. Physical Unclonable
Functions (PUFs) have emerged as a promising technology to
provide a low-cost authentication for such devices. By exploiting
intrinsic manufacturing process variations, PUFs are able to
generate unique and apparently random chip identifiers. Strong-
PUFs represent a variant of PUFs that have been suggested
for lightweight authentication applications. Unfortunately, many
of the Strong-PUFs have been shown to be susceptible to
modelling attacks (i.e., using machine learning techniques) in
which an adversary has access to challenge and response pairs.
In this study, we propose an obfuscation technique during postprocessing
of Strong-PUF responses to increase the resilience
against machine learning attacks. We conduct machine learning
experiments using Support Vector Machines and Artificial Neural
Networks on two Strong-PUFs: a 32-bit Arbiter-PUF and a 2-
XOR 32-bit Arbiter-PUF. The predictability of the 32-bit Arbiter-
PUF is reduced to ~ 70% by using an obfuscation technique.
Combining the obfuscation technique with 2-XOR 32-bit Arbiter-
PUF helps to reduce the predictability to ~ 64%. More reduction
in predictability has been observed in an XOR Arbiter-PUF
because this PUF architecture has a good uniformity. The area
overhead with an obfuscation technique consumes only 788 and
1080 gate equivalents for the 32-bit Arbiter-PUF and 2-XOR 32-
bit Arbiter-PUF, respectively.

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More information

Published date: 3 July 2017

Identifiers

Local EPrints ID: 412725
URI: http://eprints.soton.ac.uk/id/eprint/412725
PURE UUID: fa5c91d8-8bcb-47cd-860a-b5e2dab075ea
ORCID for Mark Zwolinski: ORCID iD orcid.org/0000-0002-2230-625X

Catalogue record

Date deposited: 27 Jul 2017 16:30
Last modified: 27 Jul 2017 16:30

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Contributors

Author: Mohd Syafiq Mispan
Author: Basel Halak
Author: Mark Zwolinski ORCID iD

University divisions

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