Biometric Antispoofing Methods: A Survey in Face Recognition <s> I. INTRODUCTION ''Fingerprints cannot lie, but liars can make fingerprints''. <s> The recognizer discussed will automatically recognize telephone‐quality digits spoken at normal speech rates by a single individual, with an accuracy varying between 97 and 99 percent. After some preliminary analysis of the speech of any individual, the circuit can be adjusted to deliver a similar accuracy on the speech of that individual. The circuit is not, however, in its present configuration, capable of performing equally well on the speech of a series of talkers without recourse to such adjustment.Circuitry involves division of the speech spectrum into two frequency bands, one below and the other above 900 cps. Axis‐crossing counts are then individually made of both band energies to determine the frequency of the maximum syllabic rate energy with each band. Simultaneous two‐dimensional frequency portrayal is found to possess recognition significance. Standards are then determined, one for each digit of the ten‐digit series, and are built into the recognizer as a form of elemental memory. By means of... <s> BIB001 </s> Biometric Antispoofing Methods: A Survey in Face Recognition <s> I. INTRODUCTION ''Fingerprints cannot lie, but liars can make fingerprints''. <s> Abstract Biometrics authentication offers many advantages over conventional authentication systems that rely on possessions or special knowledge. With conventional technology, often the mere possession of an employee ID card is proof of ID, while a password potentially can be used by large groups of colleagues for long times without change. The fact that biometrics authentication is non-repudiable (hard to refute) and, yet, convenient, is among its most important advantages. Biometrics systems, however, suffer from some inherent biometrics-specific security threats. These threats are mainly related to the use of digital signals and the need for additional input devices, though we also discuss brute-force attacks of biometrics systems. There are also problems common to any pattern recognition system. These include “wolves” and “lambs”, and a new group we call “chameleons”. An additional issue with the use of biometrics is the invasion of privacy because the user has to enroll with an image of a body part. We discuss these issues and suggest some methods for mitigating their impact. <s> BIB002 </s> Biometric Antispoofing Methods: A Survey in Face Recognition <s> I. INTRODUCTION ''Fingerprints cannot lie, but liars can make fingerprints''. <s> Establishing identity is becoming critical in our vastly interconnected society. Questions such as "Is she really who she claims to be?," "Is this person authorized to use this facility?," or "Is he in the watchlist posted by the government?" are routinely being posed in a variety of scenarios ranging from issuing a driver's license to gaining entry into a country. The need for reliable user authentication techniques has increased in the wake of heightened concerns about security and rapid advancements in networking, communication, and mobility. Biometrics, described as the science of recognizing an individual based on his or her physical or behavioral traits, is beginning to gain acceptance as a legitimate method for determining an individual's identity. Biometric systems have now been deployed in various commercial, civilian, and forensic applications as a means of establishing identity. In this paper, we provide an overview of biometrics and discuss some of the salient research issues that need to be addressed for making biometric technology an effective tool for providing information security. The primary contribution of this overview includes: 1) examining applications where biometric scan solve issues pertaining to information security; 2) enumerating the fundamental challenges encountered by biometric systems in real-world applications; and 3) discussing solutions to address the problems of scalability and security in large-scale authentication systems. <s> BIB003 </s> Biometric Antispoofing Methods: A Survey in Face Recognition <s> I. INTRODUCTION ''Fingerprints cannot lie, but liars can make fingerprints''. <s> Biometric recognition offers a reliable solution to the problem of user authentication in identity management systems. With the widespread deployment of biometric systems in various applications, there are increasing concerns about the security and privacy of biometric technology. Public acceptance of biometrics technology will depend on the ability of system designers to demonstrate that these systems are robust, have low error rates, and are tamper proof. We present a high-level categorization of the various vulnerabilities of a biometric system and discuss countermeasures that have been proposed to address these vulnerabilities. In particular, we focus on biometric template security which is an important issue because, unlike passwords and tokens, compromised biometric templates cannot be revoked and reissued. Protecting the template is a challenging task due to intrauser variability in the acquired biometric traits. We present an overview of various biometric template protection schemes and discuss their advantages and limitations in terms of security, revocability, and impact on matching accuracy. A template protection scheme with provable security and acceptable recognition performance has thus far remained elusive. Development of such a scheme is crucial as biometric systems are beginning to proliferate into the core physical and information infrastructure of our society. <s> BIB004 </s> Biometric Antispoofing Methods: A Survey in Face Recognition <s> I. INTRODUCTION ''Fingerprints cannot lie, but liars can make fingerprints''. <s> This paper addresses the issue of counterfeit iris detection, which is a liveness detection problem in biometrics. Fake iris mentioned here refers to iris wearing color contact lens with textures printed onto them. We propose three measures to detect fake iris: measuring iris edge sharpness, applying Iris-Texton feature for characterizing the visual primitives of iris textures and using selected features based on co-occurrence matrix (CM). Extensive testing is carried out on two datasets containing different types of contact lens with totally 640 fake iris images, which demonstrates that Iris-Texton and CM features are effective and robust in anticounterfeit iris. Detailed comparisons with two state-of-the-art methods are also presented, showing that the proposed iris edge sharpness measure acquires a comparable performance with these two methods, while Iris-Texton and CM features outperform the state-of-the-art. <s> BIB005 </s> Biometric Antispoofing Methods: A Survey in Face Recognition <s> I. INTRODUCTION ''Fingerprints cannot lie, but liars can make fingerprints''. <s> In this contribution, the vulnerabilities of iris-based recognition systems to direct attacks are studied. A database of fake iris images has been created from real iris of the BioSec baseline database. Iris images are printed using a commercial printer and then, presented at the iris sensor. We use for our experiments a publicly available iris recognition system, which some modifications to improve the iris segmentation step. Based on results achieved on different operational scenarios, we show that the system is vulnerable to direct attacks, pointing out the importance of having countermeasures against this type of fraudulent actions. <s> BIB006 </s> Biometric Antispoofing Methods: A Survey in Face Recognition <s> I. INTRODUCTION ''Fingerprints cannot lie, but liars can make fingerprints''. <s> In this paper we propose a modified hill-climbing attack to iris biometric systems. Applying our technique we are able to effectively gain access to iris biometric systems at very low effort. Furthermore, we demonstrate that reconstructing approximations of original iris images is highly non-trivial. <s> BIB007 </s> Biometric Antispoofing Methods: A Survey in Face Recognition <s> I. INTRODUCTION ''Fingerprints cannot lie, but liars can make fingerprints''. <s> A common technique to by-pass 2-D face recognition systems is to use photographs of spoofed identities. Unfortunately, research in counter-measures to this type of attack have not kept-up - even if such threats have been known for nearly a decade, there seems to exist no consensus on best practices, techniques or protocols for developing and testing spoofing-detectors for face recognition. We attribute the reason for this delay, partly, to the unavailability of public databases and protocols to study solutions and compare results. To this purpose we introduce the publicly available PRINT-ATTACK database and exemplify how to use its companion protocol with a motion-based algorithm that detects correlations between the person's head movements and the scene context. The results are to be used as basis for comparison to other counter-measure techniques. The PRINT-ATTACK database contains 200 videos of real-accesses and 200 videos of spoof attempts using printed photographs of 50 different identities. <s> BIB008 </s> Biometric Antispoofing Methods: A Survey in Face Recognition <s> I. INTRODUCTION ''Fingerprints cannot lie, but liars can make fingerprints''. <s> A biometric system is essentially a pattern recognition system being used in ad-versarial environment. Since, biometric system like any conventional security system is exposed to malicious adversaries, who can manipulate data to make the system ineffective by compromising its integrity. Current theory and de- sign methods of biometric systems do not take into account the vulnerability to such adversary attacks. Therefore, evaluation of classical design methods is an open problem to investigate whether they lead to design secure systems. In order to make biometric systems secure it is necessary to understand and evalu-ate the threats and to thus develop effective countermeasures and robust system designs, both technical and procedural, if necessary. Accordingly, the extension ::: of theory and design methods of biometric systems is mandatory to safeguard the security and reliability of biometric systems in adversarial environments. In ::: this thesis, we provide some contributions towards this direction. Among all the potential attacks discussed in the literature, spoof attacks are one of the main threats against the security of biometric systems for identity ::: recognition. Multimodal biometric systems are commonly believed to be in-trinsically more robust to spoof attacks than systems based on a single biomet-ric trait, as they combine information coming from different biometric traits. ::: However, recent works have question such belief and shown that multimodal systems can be misled by an attacker (impostor) even by spoofing only one of the biometric traits. Therefore, we first provide a detailed review of state-of-the-art works in multimodal biometric systems against spoof attacks. The scope ofstate-of-the-art results is very limited, since they were obtained under a very ::: restrictive “worst-case” hypothesis, where the attacker is assumed to be able to fabricate a perfect replica of a biometric trait whose matching score distribu-tion is identical to the one of genuine traits. Thus, we argue and investigate the validity of “worst-case” hypothesis using large set of real spoof attacks and provide empirical evidence that “worst-case” scenario can not be representa- ::: ixtive of real spoof attacks: its suitability may depend on the specific biometric trait, the matching algorithm, and the techniques used to counterfeit the spoofed traits. Then, we propose a security evaluation methodology of biometric systems against spoof attacks that can be used in real applications, as it does not require fabricating fake biometric traits, it allows the designer to take into account the different possible qualities of fake traits used by different attackers, and it exploits only information on genuine and impostor samples which is col- ::: lected for the training of a biometric system. Our methodology evaluates the performances under a simulated spoof attack using model of the fake score distribution that takes into account explicitly different degrees of the quality of fake biometric traits. In particular, we propose two models of the match score distribution of fake traits that take into account all different factors which can affect the match score distribution of fake traits like the particular spoofed biometric, the sensor, the algorithm for matching score computation, the technique used to construct fake biometrics, and the skills of the attacker. All these factors are summarized in a single parameter, that we call “attack strength”. Further, we propose extension of our security evaluation method to rank several biometric ::: score fusion rules according to their relative robustness against spoof attacks. This method allows the designer to choose the most robust rule according to the method prediction. We then present empirical analysis, using data sets of face and fingerprints including real spoofed traits, to show that our proposed models provide a good approximation of fake traits’ score distribution and our ::: method thus providing an adequate estimation of the security1 of biometric systems against spoof attacks. We also use our method to show how to evaluate the security of different multimodal systems on publicly available benchmark ::: data sets without spoof attacks. Our experimental results show that robustness of multimodal biometric systems to spoof attacks strongly depends on the particular matching algorithm, the score fusion rule, and the attack strength of fake traits. We eventually present evidence, considering a multimodal system based on face and fingerprint biometrics, that the proposed methodology to rank score ::: fusion rules is capable of providing correct ranking of score fusion rules under spoof attacks. <s> BIB009 </s> Biometric Antispoofing Methods: A Survey in Face Recognition <s> I. INTRODUCTION ''Fingerprints cannot lie, but liars can make fingerprints''. <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> BIB010 </s> Biometric Antispoofing Methods: A Survey in Face Recognition <s> I. INTRODUCTION ''Fingerprints cannot lie, but liars can make fingerprints''. <s> Recent researches have shown great attention in biometric systems due to the importance of its applications and its challenges. Researchers proved that the available fingerprint recognition systems are vulnerable to attack at sensor level. Thus, developing an efficient algorithm to protect fingerprint systems from imposer access is urgent. This can be achieved by checking the vitality of a presented fingerprint using hardware or software solutions. This survey focuses on current state of art in the field of fingerprint liveness detection by summarizing the related researches. <s> BIB011 </s> Biometric Antispoofing Methods: A Survey in Face Recognition <s> I. INTRODUCTION ''Fingerprints cannot lie, but liars can make fingerprints''. <s> The use of an artificial replica of a biometric characteristic in an attempt to circumvent a system is an example of a biometric presentation attack. Liveness detection is one of the proposed countermeasures, and has been widely implemented in fingerprint and iris recognition systems in recent years to reduce the consequences of spoof attacks. The goal for the Liveness Detection (LivDet) competitions is to compare software-based iris liveness detection methodologies using a standardized testing protocol and large quantities of spoof and live images. Three submissions were received for the competition Part 1; Biometric Recognition Group de Universidad Autonoma de Madrid, University of Naples Federico II, and Faculdade de Engenharia de Universidade do Porto. The best results from across all three datasets was from Federico with a rate of falsely rejected live samples of 28.6% and the rate of falsely accepted fake samples of 5.7%. <s> BIB012 </s> Biometric Antispoofing Methods: A Survey in Face Recognition <s> I. INTRODUCTION ''Fingerprints cannot lie, but liars can make fingerprints''. <s> Face authentication is one of promising biometrics-based user authentication mechanisms that have been widely available in this era of mobile computing. With built-in camera capability on smart phones, tablets, and laptops, face authentication provides an attractive alternative of legacy passwords for its memory-less authentication process. Although it has inherent vulnerability against spoofing attacks, it is generally considered sufficiently secure as an authentication factor for common access protection. However, this belief becomes questionable since image sharing has been popular in online social networks (OSNs). A huge number of personal images are shared every day and accessible to potential adversaries. This OSN-based facial disclosure (OSNFD) creates a significant threat against face authentication. In this paper, we make the first attempt to quantitatively measure the threat of OSNFD. We examine real-world face-authentication systems designed for both smartphones, tablets, and laptops. Interestingly, our results find that the percentage of vulnerable images that can used for spoofing attacks is moderate, but the percentage of vulnerable users that are subject to spoofing attacks is high. The difference between systems designed for smartphones/tablets and laptops is also significant. In our user study, the average percentage of vulnerable users is 64% for laptop-based systems, and 93% for smartphone/tablet-based systems. This evidence suggests that face authentication may not be suitable to use as an authentication factor, as its confidentiality has been significantly compromised due to OSNFD. In order to understand more detailed characteristics of OSNFD, we further develop a risk estimation tool based on logistic regression to extract key attributes affecting the success rate of spoofing attacks. The OSN users can use this tool to calculate risk scores for their shared images so as to increase their awareness of OSNFD. <s> BIB013 </s> Biometric Antispoofing Methods: A Survey in Face Recognition <s> I. INTRODUCTION ''Fingerprints cannot lie, but liars can make fingerprints''. <s> The vulnerability of finger vein recognition to spoofing is studied in this paper. A collection of spoofing finger vein images has been created from real finger vein samples. Finger vein images are printed using a commercial printer and then, presented at an open source finger vein sensor. Experiments are carried out using an extensible framework, which allows fair and reproducible benchmarks. Experimental results lead to a spoofing false accept rate of 86%, thus showing that finger vein biometrics is vulnerable to spoofing attacks, pointing out the importance to investigate countermeasures against this type of fraudulent actions. <s> BIB014
Unfortunately, this paraphrase of an old quote attributed to Mark Twain 1 has been proven right in many occasions now. And not only for fingerprints, but also for many other biometric traits such as face, iris, voice or even gait. Every technology has its own time. Since the first pioneering works on automatic voice and face recognition over 40 years ago  - BIB001 , steady and continuous progress has been made in the development of biometric technology. Driven by the very appealing new security biometric paradigm ''forget about cards and passwords, you are your own key'', researchers from many different fields such as image processing, computer vision or pattern recognition, have applied the newest techniques in each of these areas to improve the  Figures do not lie, but liars do figure. performance of biometric systems BIB003 . This path of technological evolution has permitted the use of biometrics in many diverse activities such as forensics, border and access control, surveillance or on-line commerce. In this scenario of constant expansion, and as a consequence of its own natural progress, new concerns are arising regarding biometric technology different from the mere improvement of its recognition performance. Among these new issues and challenges that have emerged around biometrics, its resilience against external threats has lately drawn a significant level of attention. Currently it is an accepted fact that, as the deployment of biometric systems keeps growing year after year in such different environments as airports, laptops or mobile phones, users are also becoming more familiar with their use in everyday life and, as a result, their security weaknesses are better known to the general public. Nowadays, it is not difficult to find websites with tutorial videos which give detailed guidance on how to create fake masks, fingerprints or irises that may be used to fool biometric systems. Attacks are not any more restricted to a mere theoretical or academic sphere, but are starting to be carried out against real operational applications. The fairly easy hacking of the long anticipated new iPhone 5S fingerprint reader, just a day after it hit the shelves and using a regular and well-known type of fingerprint spoof  , is only another example in the list of practical attacks and vulnerabilities of biometric systems that are being reported to the public from hacking groups attempting to get recognition  -  , from real criminal cases  -  , or even from live demonstrations at biometric and security specific conferences  ,  . As a consequence, in recent years, there has been an increasing interest on the evaluation of biometric systems security, which has led to the creation of numerous and very diverse initiatives focused on this field of research  , BIB002 : publication of many research works disclosing and evaluating different biometric vulnerabilities  - BIB007 ; proposal of new protection methods BIB004 - BIB005 ; related books and book chapters  -  ; PhD and MSc Theses which propose and analyse different biometric spoofing and anti-spoofing techniques BIB009 -  ; publication of several standards in the area [40] -  and of different Supporting Documents and Protection Profiles in the framework of the security evaluation standard Common Criteria for the objective assessment of commercial systems  ,  ; certification of different commercial products in the framework of the Common Criteria  -  ; patented anti-spoofing mechanisms for biometric systems  -  ; specific tracks, sessions and workshops in biometric-specific and general signal processing conferences  -  ; organization of competitions focused on vulnerability assessment BIB010 - BIB012 , acquisition of specific datasets BIB006 - BIB008 ; creation of groups and laboratories specialized in the evaluation of biometric security  -  ; European Projects with the biometric security topic as their main research interest [63] ,  . All these initiatives clearly highlight the effort put by all parties involved in the development of biometrics (i.e., researchers, developers and industry) to improve the systems' security in order to bring this technology to comparable deployment levels to other well established security-related solutions. Among the different vulnerabilities analyzed, intensive research efforts have been focused on the study of direct or spoofing attacks. Spoofing is a purely biometric vulnerability that is not shared with other IT security solutions. In these attacks, intruders use some type of synthetically produced artefact (e.g., face mask, gummy finger or printed iris image) or try to mimic the behaviour of genuine users (e.g., gait, signature), to fraudulently access the biometric system. This way, spoofing takes advantage of the fact that our fingerprints, face, iris, voice or even our DNA, are publicly available data. This is one of the well-known drawbacks of biometrics: ''biometric traits are not secrets''  ,  - BIB013 . Such public dimension of biometrics is one of the main reasons why spoofing has attracted a lot of interest not only from researchers but also from general users who are seduced by the ''do-it-yourself'' nature of these attacks. It is precisely this characteristic that renders spoofing really dangerous, as it transforms every user into a potential attacker. The public, low-cost and low-tech features of spoofing are well reported in the literature, where it has been shown in different works that many, if not all, biometric modalities are vulnerable to this threat BIB008 ,  - BIB014 . Therefore, nowadays the question is not any more whether or not biometrics can be copied or forged, but rather to what extent systems are robust to these attacks and if they incorporate the necessary countermeasures to detect them. However, counterfeiting this type of threats is not a straight forward problem. As they are performed in the analog domain and interaction with the acquisition device is done following the regular protocol, usual digital protection mechanisms are not effective (e.g., encryption, digital signature or watermarking). As a result, specific countermeasures that allow biometric systems detecting fake samples and rejecting them have to be developed. The spoofing biometric security context described above has promoted in the last 10 years a significant amount of research which has resulted in publications in journals, conferences and media, describing new anti-spoofing algorithms and systems that intend to make this technology safer. This has been specially the case for some of the most deployed, popular and mature modalities such as face, fingerprints and iris, which have also been shown to be the most exposed to spoofing. At the moment, the amount of new contributions and initiatives in the area of anti-spoofing requires a significant condensation effort to keep track of all new information in order to form a clear picture of the state-ofthe-art as of today. As an example, a series of chronological milestones related to the evolution of biometric spoofing are shown in Fig. 1 . We are aware that there are other works that merit being included in the diagram, however, due to space restrictions, we have focused on those that, from our point of view, can better help the reader to see the progress of anti-spoofing algorithms both from a technological and a performance perspective. Similarly to what has been recently published for the fingerprint modality BIB011 -  , the current article is an attempt to contribute to this difficult review task. It presents a comprehensive survey of anti-spoofing methodologies proposed until mid 2014 in the widely used face modality, following a systematic categorization. It also provides an overview of publicly available evaluation benchmarks for face anti-spoofing approaches, summarizing the detection rates achieved by state-of-the-art methods in the international competitions that have been organized up to date. The article concludes with an outline of the lessons learnt in these more than 10 years of intensive anti-spoofing research, and with a personal vision of VOLUME 2, 2014 FIGURE 1. Chronological evolution of biometric spoofing and anti-spoofing with a series of significant milestones that have been covered in this field so far. All events are referenced throughout the article. the challenges to be faced and possible future research lines that may contribute to the general improvement of the security level offered by biometric systems against spoofing. In brief, the paper is thought as a tool to provide biometric researchers, either newcomers or experts in security related aspects of this technology, an overall picture of the current panorama in biometric anti-spoofing with special focus on the face trait. It also aims at presenting the current strengths, shortcomings and challenges of these security protection techniques. Although the work is thought to be self-contained, some previous general knowledge on biometrics can help to better understand some of the concepts introduced in the article. The rest of the paper is structured as follows. In Sect. II some general anti-spoofing concepts are summarized and the techniques classification that will be followed throughout the paper is presented. In Sect. III the reader can find a comprehensive survey of the different research works that have been presented until mid 2014 in face anti-spoofing. Sect. IV addresses the important issue of anti-spoofing evaluation and presents the datasets that are publicly available for this purpose in the face modality. To conclude, the summary and discussion, with some insight into the future, are given in Sect. V.