By Topic

Fast physical object identification based on unclonable features and soft fingerprinting

Sign In

Cookies must be enabled to login.After enabling cookies , please use refresh or reload or ctrl+f5 on the browser for the login options.

Formats Non-Member Member
$33 $13
Learn how you can qualify for the best price for this item!
Become an IEEE Member or Subscribe to
IEEE Xplore for exclusive pricing!
close button

puzzle piece

IEEE membership options for an individual and IEEE Xplore subscriptions for an organization offer the most affordable access to essential journal articles, conference papers, standards, eBooks, and eLearning courses.

Learn more about:

IEEE membership

IEEE Xplore subscriptions

4 Author(s)
Taras Holotyak ; University of Geneva, Department of Computer Science, 7, route de Drize, CH-1227, Switzerland ; Sviatoslav Voloshynovskiy ; Oleksiy Koval ; Fokko Beekhof

In this paper we advocate a new technique for the fast identification of physical objects based on their physical unclonable features (surface microstructures). The proposed identification method is based on soft fingerprinting and consists of two stages: at the first stage the list of possible candidates is estimated based on the most reliable bits of a soft fingerprint and the traditional maximum likelihood decoding is applied to the obtained list to find a single best match at the second stage. The soft fingerprint is computed based on random projections with a sign-magnitude decomposition of projected coefficients. The estimate of a bit reliability is deduced directly from the observed coefficients. We investigate different decoding strategies to estimate the list of candidates, which minimize the probability of miss of the right index on the list. The obtained results show the flexibility of the proposed identification method to provide the performance-complexity trade-off.

Published in:

2011 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)

Date of Conference:

22-27 May 2011