HOW TO FAKE HARDWARE FINGERPRINT SKIN
HOW TO FAKE HARDWARE FINGERPRINT VERIFICATION

HOW TO FAKE HARDWARE FINGERPRINT SKIN

(2007a), the majority of approaches are aimed to characterize physiological features of the skin by image processing algorithms, e.g., physiological features such as the perspiration (Derakshani et al., 2003 Parthasaradhi et al., 2005 Marcialis et al., 2010), and the elastic deformation of fingerprints (Antonelli et al., 2008 Chen & Jain, 2005). Recently, two integrated systems (hardware and software methods) have been proposed (Russo, 2007 Diaz-Santana & Parziale, 2006).Р”Р„ccording to Coli et al. These software- based solutions are obviously less intrusive and cheaper than the hardware-based ones. The majority of them is based on the use of hardware, embedded in the sensor, which can detect the vitality, or liveness, of the finger, e.g., through a blood pressure measurement.Р”Р„nother class of approaches is based on the extraction of features which can discriminate between live and fake fingerprints by processing images acquired by the sensor. In order to prevent these fraudulent attempts, some solutions have been proposed. Acquired image is processed as well as a РІР‚СљgenuineРІР‚Сњ image. (2002) and Sandstrom (2005) showed that many fingerprint sensors can be deceived by submitting a РІР‚СљgummyРІР‚Сњ finger.

HOW TO FAKE HARDWARE FINGERPRINT VERIFICATION

The robustness of a fingerprint verification system under fraudulent attempts through fake fingers is an important issue. Experiments are carried out on a data set much larger than commonly adopted ones, containing images from three different optical sensors. The proposal is compared and integrated with several live-based features at the state-of-the-art, and shows very good liveness detection performances. Then the authors propose a possibile implementation of this kind of features based on the power spectrum of the fingerprint image. In this paper, the authors propose and motivate the use of a novel kind of features exploiting characteristics noticed in the reproduction of fake fingers, that they named fake-based features.

Such features can be named live-based, or vitality-based features. So far, proposed approaches are based on features exploiting characteristics of a live finger (e.g., finger perspiration). Since introducing hardware dedicated to liveness detection in scanners is expensive, software-based solutions, based on image processing algorithms, have been proposed as alternative. An image quite similar to that of true, alive, fingerprint, is derived if such РІР‚Сљfake fingersРІР‚Сњ are submitted to an electronic scanner. This problem, raised some years ago, is related to the fact that the 3d shape pattern of a fingerprint can be reproduced using artificial materials.

AbstractThe vitality detection of fingerprints is currently acknowledged as a serious issue for personal identity verification systems.

How to fake hardware fingerprint