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Cryptography 2017, 1(3), 17;

Leveraging Distributions in Physical Unclonable Functions

Department of Electrical and Computer Engineering, University of New Mexico, Albuquerque, NM 87131, USA
Department of Electrical and Computer Engineering, Florida Institute of Technology, Melbourne, FL 32901, USA
Authors to whom correspondence should be addressed.
Received: 5 July 2017 / Revised: 25 September 2017 / Accepted: 26 October 2017 / Published: 30 October 2017
(This article belongs to the Special Issue PUF-Based Authentication)
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A special class of Physical Unclonable Functions (PUFs) referred to as strong PUFs can be used in novel hardware-based authentication protocols. Strong PUFs are required for authentication because the bit strings and helper data are transmitted openly by the token to the verifier, and therefore are revealed to the adversary. This enables the adversary to carry out attacks against the token by systematically applying challenges and obtaining responses in an attempt to machine learn, and later predict, the token’s response to an arbitrary challenge. Therefore, strong PUFs must both provide an exponentially large challenge space and be resistant to machine-learning attacks in order to be considered secure. We investigate a transformation called temperature–voltage compensation (TVCOMP), which is used within the Hardware-Embedded Delay PUF (HELP) bit string generation algorithm. TVCOMP increases the diversity and unpredictability of the challenge–response space, and therefore increases resistance to model-building attacks. HELP leverages within-die variations in path delays as a source of random information. TVCOMP is a linear transformation designed specifically for dealing with changes in delay introduced by adverse temperature–voltage (environmental) variations. In this paper, we show that TVCOMP also increases entropy and expands the challenge–response space dramatically. View Full-Text
Keywords: physical unclonable function; entropy; strong PUF physical unclonable function; entropy; strong PUF

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Che, W.; Kajuluri, V.K.; Saqib, F.; Plusquellic, J. Leveraging Distributions in Physical Unclonable Functions. Cryptography 2017, 1, 17.

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