Identification and Security Implications of Biometrics

The usage of biometrics has become more frequent over the past couple of decades, notably due to technological advancements. Evolving technology in the field of biometrics has also led to increased accuracy of associated software, which have provided the opportunity to use a multitude of different human characteristics for identification and/or verification purposes. The current study assessed the usage of biometrics in casinos, hospitals, and law enforcement agencies using a survey methodology. Results indicated that privacy concerns related to the use of biometrics may not be as prevalent as indicated in the literature. Additionally, results indicated that the utilization of biometrics has led to increased accuracy in identification and verification processes, led to enhanced security, and would be highly recommended to other institutions. Information obtained from the literature notes the racial bias in facial recognition technologies due to algorithmic development based solely upon features of Caucasian individuals. Efforts need to be made to create facial recognition algorithms that are more racially and ethnically diverse

Fusion of fingerprint presentation attacks detection and matching: a real approach from the LivDet perspective

The liveness detection ability is explicitly required for current personal verification systems in many security applications. As a matter of fact, the project of any biometric verification system cannot ignore the vulnerability to spoofing or presentation attacks (PAs), which must be addressed by effective countermeasures from the beginning of the design process. However, despite significant improvements, especially by adopting deep learning approaches to fingerprint Presentation Attack Detectors (PADs), current research did not state much about their effectiveness when embedded in fingerprint verification systems. We believe that the lack of works is explained by the lack of instruments to investigate the problem, that is, modelling the cause-effect relationships when two systems (spoof detection and matching) with non-zero error rates are integrated. To solve this lack of investigations in the literature, we present in this PhD thesis a novel performance simulation model based on the probabilistic relationships between the Receiver Operating Characteristics (ROC) of the two systems when implemented sequentially. As a matter of fact, this is the most straightforward, flexible, and widespread approach. We carry out simulations on the PAD algorithms’ ROCs submitted to the editions of LivDet 2017-2019, the NIST Bozorth3, and the top-level VeriFinger 12.0 matchers. With the help of this simulator, the overall system performance can be predicted before actual implementation, thus simplifying the process of setting the best trade-off among error rates. In the second part of this thesis, we exploit this model to define a practical evaluation criterion to assess whether operational points of the PAD exist that do not alter the expected or previous performance given by the verification system alone. Experimental simulations coupled with the theoretical expectations confirm that this trade-off allows a complete view of the sequential embedding potentials worthy of being extended to other integration approaches

DIGITAL SIGNATURE IN CYBER SECURITY

For secure exchanges over open organizations, the Digital Signature method is basic. It is having assortments of uses to guarantee the uprightness of information traded or put away and to demonstrate the character of the originator to the beneficiary. Computerized Signature plans are regularly utilized in cryptographic conventions to offer types of assistance like element verification, confirmed key vehicle and validated key arrangement. Multi-biometric frameworks are as a rule perpetually sent in some huge scope biometric applications (e.g., FBI-IAFIS, UIDAI plot in India) since they have many points of interest, for example, second rate mistake rates and more prominent people inclusion contrasted with uni-biometric frameworks. In this paper, we propose a component level combination system to all the while ensure various layouts of a client as a sole secure sketch. Our main commitments include: 1) useful execution of the proposed highlight level combination development utilizing two notable biometric cryptosystems, in particular, fluffy vault and fluffy responsibility, and 2) nitty gritty investigation of the compromise between coordinating exactness and security in the proposed multibiometric cryptosystems dependent on two divergent information bases (one genuine and one virtual multimodal information base), each containing the three most famous biometric modalities, to be specific, unique mark, iris, and face. Test results give subtleties that together the multibiometric cryptosystems proposed here have progressed safe-haven and equal execution contrasted with their uni-biometric partners

Biometrics in forensic science: challenges, lessons and new technologies

Biometrics has historically found its natural mate in Forensics. The first applications found in the literature and over cited so many times, are related to biometric measurements for the identification of multiple offenders from some of their biometric and anthropometric characteristics (tenprint cards) and individualization of offender from traces found on crime-scenes (e.g. fingermarks, earmarks, bitemarks, DNA). From sir Francis Galton, to the introduction of AFIS systems in the scientific laboratories of police departments, Biometrics and Forensics have been "dating" with alternate results and outcomes. As a matter of facts there are many technologies developed under the "Biometrics umbrella" which may be optimised to better impact several Forensic scenarios and criminal investigations. At the same time, there is an almost endless list of open problems and processes in Forensics which may benefit from the introduction of tailored Biometric technologies. Joining the two disciplines, on a proper scientific ground, may only result in the success for both fields, as well as a tangible benefit for the society. A number of Forensic processes may involve Biometric-related technologies, among them: Evidence evaluation, Forensic investigation, Forensic Intelligence, Surveillance, Forensic ID management and Verification.\ud The COST Action IC1106 funded by the European Commission, is trying to better understand how Biometric and Forensics synergies can be exploited within a pan-European scientific alliance which extends its scope to partners from USA, China and Australia.\ud Several results have been already accomplished pursuing research in this direction. Notably the studies in 2D and 3D face recognition have been gradually applied to the forensic investigation process. In this paper a few solutions will be presented to match 3D face shapes along with some experimental results

Impact of minutiae errors in latent fingerprint identification: assessment and prediction

We study the impact of minutiae errors in the performance of latent fingerprint identification systems. We perform several experiments in which we remove ground-truth minutiae from latent fingerprints and evaluate the effects on matching score and rank-n identification using two different matchers and the popular NIST SD27 dataset. We observe how missing even one minutia from a fingerprint can have a significant negative impact on the identification performance. Our experimental results show that a fingerprint which has a top rank can be demoted to a bottom rank when two or more minutiae are missed. From our experimental results, we have noticed that some minutiae are more critical than others to correctly identify a latent fingerprint. Based on this finding, we have created a dataset to train several machine learning models trying to predict the impact of each minutia in the matching score of a fingerprint identification system. Finally, our best-trained model can successfully predict if a minutia will increase or decrease the matching score of a latent fingerprintThis research was partly supported by the National Council of Science and Technology of Mexico under the scholarship grants 717345 and 005438. Authors J.F. and A.M. are funded by project BIBECA (RTI2018-101248-B-I00 MINECO/FEDER) and TRESPASS-ETN (MSCA-ITN-2019-860813

VOICE BIOMETRICS FUSION FOR ENHANCED SECURITY AND SPEAKER RECOGNITION: A COMPREHENSIVE REVIEW

The scope of this paper is purposefully limited to the 15 voice biometrics modalities discussed by Jain et al. (2004). The place of Voice within their classification scheme is reexamined in light of important developments that have taken place since 2010. Additionally, elements are added to Mayhew’s (2018) overview of the history of biometrics as an attempt to fill in missing gaps concerning Voice. All this leads to a reassessment of voice biometrics and how it relates to other biometric modalities. Speech segments that carry extremely high identity vector loads are discussed. The main assertion of this paper is that increased computing power, advanced algorithms, and the deployment of Artificial Intelligent have made voice biometrics optimal for use. Furthermore, the analysis of the compatibility among modalities, the estimation of inconvenience penalty, and the calculation of the arithmetic distances between various modalities indicate that the fusion of {Voice + Face}, {Voice + Fingerprint}, {Voice + Iris}, and {Voice + Signature} on the one hand, and of {Voice + Face +Fingerprint}, {Voice +Fingerprint + Signature} on the other, offer the best liveliness assurance against hacking, spoofing, and other malicious activities

Predictive biometrics: A review and analysis of predicting personal characteristics from biometric data

Interest in the exploitation of soft biometrics information has continued to develop over the last decade or so. In comparison with traditional biometrics, which focuses principally on person identification, the idea of soft biometrics processing is to study the utilisation of more general information regarding a system user, which is not necessarily unique. There are increasing indications that this type of data will have great value in providing complementary information for user authentication. However, the authors have also seen a growing interest in broadening the predictive capabilities of biometric data, encompassing both easily definable characteristics such as subject age and, most recently, `higher level' characteristics such as emotional or mental states. This study will present a selective review of the predictive capabilities, in the widest sense, of biometric data processing, providing an analysis of the key issues still adequately to be addressed if this concept of predictive biometrics is to be fully exploited in the future

Continuous and transparent multimodal authentication: reviewing the state of the art

Individuals, businesses and governments undertake an ever-growing range of activities online and via various Internet-enabled digital devices. Unfortunately, these activities, services, information and devices are the targets of cybercrimes. Verifying the user legitimacy to use/access a digital device or service has become of the utmost importance. Authentication is the frontline countermeasure of ensuring only the authorized user is granted access; however, it has historically suffered from a range of issues related to the security and usability of the approaches. They are also still mostly functioning at the point of entry and those performing sort of re-authentication executing it in an intrusive manner. Thus, it is apparent that a more innovative, convenient and secure user authentication solution is vital. This paper reviews the authentication methods along with the current use of authentication technologies, aiming at developing a current state-of-the-art and identifying the open problems to be tackled and available solutions to be adopted. It also investigates whether these authentication technologies have the capability to fill the gap between high security and user satisfaction. This is followed by a literature review of the existing research on continuous and transparent multimodal authentication. It concludes that providing users with adequate protection and convenience requires innovative robust authentication mechanisms to be utilized in a universal level. Ultimately, a potential federated biometric authentication solution is presented; however it needs to be developed and extensively evaluated, thus operating in a transparent, continuous and user-friendly manner

Mitigating Sensor and Acquisition Method-Dependence of Fingerprint Presentation Attack Detection Systems by Exploiting Data from Multiple Devices

The problem of interoperability is still open in fingerprint presentation attack detection (PAD) systems. This involves costs for designers and manufacturers who intend to change sensors of personal recognition systems or design multi-sensor systems, because they need to obtain sensor-specific spoofs and retrain the system. The solutions proposed in the state of the art to mitigate the problem still require data from the target sensor and are therefore not exempt from the problem of obtaining new data. In this paper, we provide insights for the design of PAD systems thanks to an overview of an interoperability analysis on modern systems: hand-crafted, deep-learning-based, and hybrid. We investigated realistic use cases to determine the pros and cons of training with data from multiple sensors compared to training with single sensor data, and drafted the main guidelines to follow for deciding the most convenient PAD design technique depending on the intended use of the fingerprint identification/authentication system