204 research outputs found

    Biometric encryption system for increased security

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    Security is very important in present day life. In this highly-interconnected world, most of our daily activities are computer based, and the data transactions are protected by passwords. These passwords identify various entities such as bank accounts, mobile phones, etc. People might reuse the same password, or passwords related to an individual that can lead to attacks. Indeed, remembering several passwords can become a tedious task. Biometrics is a science that measures an individual’s physical characteristics in a unique way. Thus, biometrics serves as a method to replace the cumbersome use of complex passwords. Our research uses the features of biometrics to efficiently implement a biometric encryption system with a high level of security

    Developing an Algorithm for Securing the Biometric Data Template in the Database

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    This research article published by the International Journal of Advanced Computer Science and Applications, Vol. 10, No. 10, 2019In the current technology advancement, biometric template provides a dependable solution to the problem of user verification in an identity control system. The template is saved in the database during the enrollment and compared with query information in the verification stage. Serious security and privacy concerns can arise, if raw, unprotected data template is saved in the database. An attacker can hack the template information in the database to gain illicit access. A novel approach of encryption-decryption algorithm utilizing a design pattern of Model View Template (MVT) is developed to secure the biometric data template. The model manages information logically, the view shows the visualization of the data, and the template addresses the data migration into pattern object. The established algorithm is based on the cryptographic module of the Fernet key instance. The Fernet keys are combined to generate a multiFernet key to produce two encrypted files (byte and text file). These files are incorporated with Twilio message and securely preserved in the database. In the event where an attacker tries to access the biometric data template in the database, the system alerts the user and stops the attacker from unauthorized access, and cross-verify the impersonator based on the validation of the ownership. Thus, helps inform the users and the authority of, how secure the individual biometric data template is, and provided a high level of the security pertaining the individual data privac

    Privacy in Biometric Systems

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    Biometrics are physiological and/or behavioral characteristics of a person that have been used to provide an automatic proof of identity in a growing list of applications including crime/terrorism fighting, forensics, access and border control, securing e-/m-commerce transactions and service entitlements. In recent years, a great deal of research into a variety of new and traditional biometrics has widened the scope of investigations beyond improving accuracy into mechanisms that deal with serious concerns raised about the potential misuse of collected biometric data. Despite the long list of biometrics’ benefits, privacy concerns have become widely shared due to the fact that every time the biometric of a person is checked, a trace is left that could reveal personal and confidential information. In fact, biometric-based recognition has an inherent privacy problem as it relies on capturing, analyzing, and storing personal data about us as individuals. For example, biometric systems deal with data related to the way we look (face, iris), the way we walk (gait), the way we talk (speaker recognition), the way we write (handwriting), the way we type on a keyboard (keystroke), the way we read (eye movement), and many more. Privacy has become a serious concern for the public as biometric systems are increasingly deployed in many applications ranging from accessing our account on a Smartphone or computer to border control and national biometric cards on a very large scale. For example, the Unique Identification Authority of India (UIDAI) has issued 56 million biometric cards as of January 2014 [1], where each biometric card holds templates of the 10 fingers, the two irises and the face. An essential factor behind the growing popularity of biometrics in recent years is the fact that biometric sensors have become a lot cheaper as well as easier to install and handle. CCTV cameras are installed nearly everywhere and almost all Smartphones are equipped with a camera, microphone, fingerprint scanner, and probably very soon, an iris scanner

    Information Forensics and Security: A quarter-century-long journey

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    Information forensics and security (IFS) is an active R&D area whose goal is to ensure that people use devices, data, and intellectual properties for authorized purposes and to facilitate the gathering of solid evidence to hold perpetrators accountable. For over a quarter century, since the 1990s, the IFS research area has grown tremendously to address the societal needs of the digital information era. The IEEE Signal Processing Society (SPS) has emerged as an important hub and leader in this area, and this article celebrates some landmark technical contributions. In particular, we highlight the major technological advances by the research community in some selected focus areas in the field during the past 25 years and present future trends

    Ridge orientation modeling and feature analysis for fingerprint identification

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    This thesis systematically derives an innovative approach, called FOMFE, for fingerprint ridge orientation modeling based on 2D Fourier expansions, and explores possible applications of FOMFE to various aspects of a fingerprint identification system. Compared with existing proposals, FOMFE does not require prior knowledge of the landmark singular points (SP) at any stage of the modeling process. This salient feature makes it immune from false SP detections and robust in terms of modeling ridge topology patterns from different typological classes. The thesis provides the motivation of this work, thoroughly reviews the relevant literature, and carefully lays out the theoretical basis of the proposed modeling approach. This is followed by a detailed exposition of how FOMFE can benefit fingerprint feature analysis including ridge orientation estimation, singularity analysis, global feature characterization for a wide variety of fingerprint categories, and partial fingerprint identification. The proposed methods are based on the insightful use of theory from areas such as Fourier analysis of nonlinear dynamic systems, analytical operators from differential calculus in vector fields, and fluid dynamics. The thesis has conducted extensive experimental evaluation of the proposed methods on benchmark data sets, and drawn conclusions about strengths and limitations of these new techniques in comparison with state-of-the-art approaches. FOMFE and the resulting model-based methods can significantly improve the computational efficiency and reliability of fingerprint identification systems, which is important for indexing and matching fingerprints at a large scale

    Hybrid Data Storage Framework for the Biometrics Domain

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    Biometric based authentication is one of the most popular techniques adopted in large-scale identity matching systems due to its robustness in access control. In recent years, the number of enrolments has increased significantly posing serious issues towards the performance and scalability of these systems. In addition, the use of multiple modalities (such as face, iris and fingerprint) is further increasing the issues related to scalability. This research work focuses on the development of a new Hybrid Data Storage Framework (HDSF) that would improve scalability and performance of biometric authentication systems (BAS). In this framework, the scalability issue is addressed by integrating relational database and NoSQL data store, which combines the strengths of both. The proposed framework improves the performance of BAS in three areas (i) by proposing a new biographic match score based key filtering process, to identify any duplicate records in the storage (de-duplication search); (ii) by proposing a multi-modal biometric index based key filtering process for identification and de-duplication search operations; (iii) by adopting parallel biometric matching approach for identification, enrolment and verification processes. The efficacy of the proposed framework is compared with that of the traditional BAS and on several values of False Rejection Rate (FRR). Using our dataset and algorithms it is observed that when compared to traditional BAS, the HDSF is able to show an overall efficiency improvement of more than 54% for zero FRR and above 60% for FRR values between 1-3.5% during identification search operations

    Privacy-Preserving Biometric Authentication

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    Biometric-based authentication provides a highly accurate means of authentication without requiring the user to memorize or possess anything. However, there are three disadvantages to the use of biometrics in authentication; any compromise is permanent as it is impossible to revoke biometrics; there are significant privacy concerns with the loss of biometric data; and humans possess only a limited number of biometrics, which limits how many services can use or reuse the same form of authentication. As such, enhancing biometric template security is of significant research interest. One of the methodologies is called cancellable biometric template which applies an irreversible transformation on the features of the biometric sample and performs the matching in the transformed domain. Yet, this is itself susceptible to specific classes of attacks, including hill-climb, pre-image, and attacks via records multiplicity. This work has several outcomes and contributions to the knowledge of privacy-preserving biometric authentication. The first of these is a taxonomy structuring the current state-of-the-art and provisions for future research. The next of these is a multi-filter framework for developing a robust and secure cancellable biometric template, designed specifically for fingerprint biometrics. This framework is comprised of two modules, each of which is a separate cancellable fingerprint template that has its own matching and measures. The matching for this is based on multiple thresholds. Importantly, these methods show strong resistance to the above-mentioned attacks. Another of these outcomes is a method that achieves a stable performance and can be used to be embedded into a Zero-Knowledge-Proof protocol. In this novel method, a new strategy was proposed to improve the recognition error rates which is privacy-preserving in the untrusted environment. The results show promising performance when evaluated on current datasets

    Cryptanalysis of the Fuzzy Vault for Fingerprints: Vulnerabilities and Countermeasures

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    Das Fuzzy Vault ist ein beliebter Ansatz, um die Minutien eines menschlichen Fingerabdrucks in einer Sicherheitsanwendung geschützt zu speichern. In dieser Arbeit werden verschiedene Implementationen des Fuzzy Vault für Fingerabdrücke in verschiedenen Angriffsszenarien untersucht. Unsere Untersuchungen und Analysen bestätigen deutlich, dass die größte Schwäche von Implementationen des Fingerabdruck Fuzzy Vaults seine hohe Anfälligkeit gegen False-Accept Angriffe ist. Als Gegenmaßnahme könnten mehrere Finger oder sogar mehrere biometrische Merkmale eines Menschen gleichzeitig verwendet werden. Allerdings besitzen traditionelle Fuzzy Vault Konstruktionen eine wesentliche Schwäche: den Korrelationsangriff. Es ist bekannt, dass das Runden von Minutien auf ein starres System, diese Schwäche beheben. Ausgehend davon schlagen wir eine Implementation vor. Würden nun Parameter traditioneller Konstruktionen übernommen, so würden wir einen signifikanten Verlust an Verifikations-Leistung hinnehmen müssen. In einem Training wird daher eine gute Parameterkonfiguration neu bestimmt. Um den Authentifizierungsaufwand praktikabel zu machen, verwenden wir einen randomisierten Dekodierer und zeigen, dass die erreichbaren Raten vergleichbar mit den Raten einer traditionellen Konstruktion sind. Wir folgern, dass das Fuzzy Vault ein denkbarer Ansatz bleibt, um die schwierige Aufgabe ein kryptographisch sicheres biometrisches Kryptosystem in Zukunft zu implementieren.The fuzzy fingerprint vault is a popular approach to protect a fingerprint's minutiae as a building block of a security application. In this thesis simulations of several attack scenarios are conducted against implementations of the fuzzy fingerprint vault from the literature. Our investigations clearly confirm that the weakest link in the fuzzy fingerprint vault is its high vulnerability to false-accept attacks. Therefore, multi-finger or even multi-biometric cryptosystems should be conceived. But there remains a risk that cannot be resolved by using more biometric information of an individual if features are protected using a traditional fuzzy vault construction: The correlation attack remains a weakness of such constructions. It is known that quantizing minutiae to a rigid system while filling the whole space with chaff makes correlation obsolete. Based on this approach, we propose an implementation. If parameters were adopted from a traditional fuzzy fingerprint vault implementation, we would experience a significant loss in authentication performance. Therefore, we perform a training to determine reasonable parameters for our implementation. Furthermore, to make authentication practical, the decoding procedure is proposed to be randomized. By running a performance evaluation on a dataset generally used, we find that achieving resistance against the correlation attack does not have to be at the cost of authentication performance. Finally, we conclude that fuzzy vault remains a possible construction for helping in solving the challenging task of implementing a cryptographically secure multi-biometric cryptosystem in future
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