Fast physical object identification based on unclonable features and soft fingerprinting

In this paper we advocate a new technique for the fast identi cation of physical objects based on their physical unclonable features (surface microstructures). The proposed identi cation method is based on soft ngerprinting and consists of two stages: at the rst stage the list of possible candidates is estimated based on the most reliable bits of a soft ngerprint and the traditional maximum likelihood decoding is applied to the obtained list to nd a single best match at the second stage. The soft ngerprint is computed based on random projections with a sign-magnitude decomposition of projected coef cients. The estimate of a bit reliability is deduced directly from the observed coef cients. 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 exibility of the proposed identi cation method to provide the performance-complexity trade-off.

• Type: Journal
• Year: 2011
• Where: ICASSP
• Authors: Taras Holotyak, Sviatoslav Voloshynovskiy, Oleksiy J. Koval, Fokko Beekhof
• Keywords: Coef Cients, ICASSP 2011, Identi Cation Method, Signal Processing, Soft Ngerprint