Paper Info
Title
Fast physical object identification based on unclonable features and soft fingerprinting
Abstract
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.
Year
DOI
Venue
2011
10.1109/ICASSP.2011.5946831
Acoustics, Speech and Signal Processing
Keywords
Field
DocType
fingerprint identification,bit reliability,fast physical object identification,maximum likelihood decoding,performance-complexity trade-off,sign-magnitude decomposition,soft fingerprinting,unclonable features,Identification,Physical Unclonable Function (PUF),computational complexity,fingerprint
Pattern recognition,Computer science,Signal-to-noise ratio,Maximum likelihood,Algorithm,Fingerprint,Artificial intelligence,Decoding methods,Computational complexity theory
Conference
ISSN
ISBN
Citations 
1520-6149 E-ISBN : 978-1-4577-0537-3
978-1-4577-0537-3
5
PageRank 
References 
Authors
0.47
3
4
Name
Order
Citations
PageRank
Taras Holotyak125927.21
Sviatoslav Voloshynovskiy277380.94
Oleksiy J. Koval311817.75
Fokko Beekhof47511.28