Biometric Antispoofing Methods: A Survey in Face Recognition <s> 5) REPLAY-ATTACK DB <s> Spoofing attacks are one of the security traits that biometric recognition systems are proven to be vulnerable to. When spoofed, a biometric recognition system is bypassed by presenting a copy of the biometric evidence of a valid user. Among all biometric modalities, spoofing a face recognition system is particularly easy to perform: all that is needed is a simple photograph of the user. In this paper, we address the problem of detecting face spoofing attacks. In particular, we inspect the potential of texture features based on Local Binary Patterns (LBP) and their variations on three types of attacks: printed photographs, and photos and videos displayed on electronic screens of different sizes. For this purpose, we introduce REPLAY-ATTACK, a novel publicly available face spoofing database which contains all the mentioned types of attacks. We conclude that LBP, with ∼15% Half Total Error Rate, show moderate discriminability when confronted with a wide set of attack types. <s> BIB001 </s> Biometric Antispoofing Methods: A Survey in Face Recognition <s> 5) REPLAY-ATTACK DB <s> As a crucial security problem, anti-spoofing in biometrics, and particularly for the face modality, has achieved great progress in the recent years. Still, new threats arrive inform of better, more realistic and more sophisticated spoofing attacks. The objective of the 2nd Competition on Counter Measures to 2D Face Spoofing Attacks is to challenge researchers to create counter measures effectively detecting a variety of attacks. The submitted propositions are evaluated on the Replay-Attack database and the achieved results are presented in this paper. <s> BIB002
The REPLAY-ATTACK DB BIB001 is publicly available at the IDIAP Research Institute website.  The database was acquired as an extension of the PRINT-ATTACK DB, therefore it also contains short videos (around 10 seconds in mov format) of both real-access and spoofing attack attempts of 50 different subjects, acquired with a 320 × 240 resolution webcam of a 13-inch MacBook Laptop. The recordings were carried out under two different  http://www.cbsr.ia.ac.cn/english/index.asp 12 http://www.idiap.ch/dataset/replayattack conditions: i) controlled, with a uniform background and artificial lighting; and ii) adverse, with natural illumination and non-uniform background. In this case three different attacks with an increasing level of resolution were considered: (i) print, illegal access attempts are carried out with hard copies of high-resolution digital photographs (this data subset corresponds to the PRINT-ATTACK DB described in Sect. IV-C.3); (ii) mobile, attacks are performed using photos and videos taken with the iPhone using the iPhone 4 screen; iii) highdef, similar to the mobile subset but in this case the photos and videos are displayed using an iPad screen with a 1024 × 768 pixel resolution. In addition, access attempts in the three attack subsets (mobile, print and highdef) were recorded in two different modes depending on the strategy followed to hold the attack replay device (mobile phone, paper or tablet): (i) hand-based, and (ii) fixed-support. The database is distributed with an associated protocol which divides the database into a train, a development and a test set with no overlap between them (in terms of users and samples). The database also contains an enrollment subset with 100 videos corresponding only to real access attempts. This subset is provided as a means to evaluate the recognition performance of systems whose vulnerabilities to spoofing attacks will be later evaluated on the rest of the database. The 2013 edition of the Competition on Countermeasures to 2D Facial Spoofing Attacks was held using a subset of all the available attacks on the REPLAY-ATTACK DB (not just the print data as in the 2011 edition). The exact data and protocol followed on this second edition are also released with the database BIB002 . The results of the competition are given in Table 4 .