1,634 research outputs found
Vulnerabilities in biometric systems: Attacks and recent advances in liveness detection
This is an electronic version of the paper presented at the Spanish Workshop on Biometrics 2007, SWB-07 held in Girona (Spain)A review of the state-of-the-art in direct and indirect attacks to fingerprint and iris automatic recognition security systems is presented. A summary of the novel liveness detection methods, which take advantage of different physiological properties to distinguish between real and fake biometric traits, is also reported.This work has been supported by the TIC2006-13141-C03-03 project of the Spanish Ministry of Science and Technology and the BioSecure NoE
LivDet in Action - Fingerprint Liveness Detection Competition 2019
The International Fingerprint liveness Detection Competition (LivDet) is an
open and well-acknowledged meeting point of academies and private companies
that deal with the problem of distinguishing images coming from reproductions
of fingerprints made of artificial materials and images relative to real
fingerprints. In this edition of LivDet we invited the competitors to propose
integrated algorithms with matching systems. The goal was to investigate at
which extent this integration impact on the whole performance. Twelve
algorithms were submitted to the competition, eight of which worked on
integrated systems.Comment: Preprint version of a paper accepted at ICB 201
Biometric antispoofing methods: A survey in face recognition
Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works. J. Galbally, S. Marcel and J. Fierrez, "Biometric Antispoofing Methods", IEEE Access, vol.2, pp. 1530-1552, Dec. 2014In recent decades, we have witnessed the evolution of biometric technology from the rst
pioneering works in face and voice recognition to the current state of development wherein a wide spectrum
of highly accurate systems may be found, ranging from largely deployed modalities, such as ngerprint,
face, or iris, to more marginal ones, such as signature or hand. This path of technological evolution has
naturally led to a critical issue that has only started to be addressed recently: the resistance of this rapidly
emerging technology to external attacks and, in particular, to spoo ng. Spoo ng, referred to by the term
presentation attack in current standards, is a purely biometric vulnerability that is not shared with other
IT security solutions. It refers to the ability to fool a biometric system into recognizing an illegitimate user
as a genuine one by means of presenting a synthetic forged version of the original biometric trait to the sensor.
The entire biometric community, including researchers, developers, standardizing bodies, and vendors, has
thrown itself into the challenging task of proposing and developing ef cient protection methods against this
threat. The goal of this paper is to provide a comprehensive overview on the work that has been carried out
over the last decade in the emerging eld of antispoo ng, with special attention to the mature and largely
deployed face modality. The work covers theories, methodologies, state-of-the-art techniques, and evaluation
databases and also aims at providing an outlook into the future of this very active eld of research.This work was supported in part by the CAM under Project S2009/TIC-1485, in part by the Ministry of Economy and Competitiveness through the Bio-Shield Project under Grant TEC2012-34881, in part by the TABULA RASA Project under Grant FP7-ICT-257289, in part by the BEAT Project under Grant FP7-SEC-284989 through the European Union, and in part by the Cátedra Universidad Autónoma de Madrid-Telefónica
Biometric Spoofing: A JRC Case Study in 3D Face Recognition
Based on newly available and affordable off-the-shelf 3D sensing, processing and printing technologies, the JRC has conducted a comprehensive study on the feasibility of spoofing 3D and 2.5D face recognition systems with low-cost self-manufactured models and presents in this report a systematic and rigorous evaluation of the real risk posed by such attacking approach which has been complemented by a test campaign. The work accomplished and presented in this report, covers theories, methodologies, state of the art techniques, evaluation databases and also aims at providing an outlook into the future of this extremely active field of research.JRC.G.6-Digital Citizen Securit
Biometrics in ABC: counter-spoofing research
Automated border control (ABC) is concerned with fast and secure processing for intelligence-led identification. The
FastPass project aims to build a harmonised, modular reference system for future European ABC. When biometrics is taken on
board as identity, spoofing attacks become a concern. This paper presents current research in algorithm development for
counter-spoofing attacks in biometrics. Focussing on three biometric traits, face, fingerprint, and iris, it examines possible types
of spoofing attacks, and reviews existing algorithms reported in relevant academic papers in the area of countering measures to
biometric spoofing attacks. It indicates that the new developing trend is fusion of multiple biometrics against spoofing attacks
Face Liveness Detection under Processed Image Attacks
Face recognition is a mature and reliable technology for identifying people. Due
to high-definition cameras and supporting devices, it is considered the fastest and
the least intrusive biometric recognition modality. Nevertheless, effective spoofing
attempts on face recognition systems were found to be possible. As a result, various anti-spoofing algorithms were developed to counteract these attacks. They are
commonly referred in the literature a liveness detection tests. In this research we highlight the effectiveness of some simple, direct spoofing attacks, and test one of
the current robust liveness detection algorithms, i.e. the logistic regression based face liveness detection from a single image, proposed by the Tan et al. in 2010, against malicious attacks using processed imposter images. In particular, we study experimentally the effect of common image processing operations such as sharpening and smoothing, as well as corruption with salt and pepper noise, on the face liveness detection algorithm, and we find that it is especially vulnerable against spoofing attempts using processed imposter images. We design and present a new facial database, the Durham Face Database, which is the first, to the best of our knowledge, to have client, imposter as well as processed imposter images. Finally, we evaluate our claim on the effectiveness of proposed imposter image attacks using transfer learning on Convolutional Neural Networks. We verify that such attacks are more difficult to detect even when using high-end, expensive machine learning techniques
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