Cryptanalysis of the Fuzzy Vault for Fingerprints: Vulnerabilities and Countermeasures

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

State of the Art in Biometric Key Binding and Key Generation Schemes

Direct storage of biometric templates in databases exposes the authentication system and legitimate users to numerous security and privacy challenges. Biometric cryptosystems or template protection schemes are used to overcome the security and privacy challenges associated with the use of biometrics as a means of authentication. This paper presents a review of previous works in biometric key binding and key generation schemes. The review focuses on key binding techniques such as biometric encryption, fuzzy commitment scheme, fuzzy vault and shielding function. Two categories of key generation schemes considered are private template and quantization schemes. The paper also discusses the modes of operations, strengths and weaknesses of various kinds of key-based template protection schemes. The goal is to provide the reader with a clear understanding of the current and emerging trends in key-based biometric cryptosystems

Secure key agreement using pure biometrics

In this paper, we propose a novel secure key agreement protocol that uses biometrics with unordered set of features. Our protocol enables the user and the server to agree on a symmetric key, which is generated by utilizing only the feature points of the user's biometrics. It means that our protocol does not generate the key randomly or it does not use any random data in the key itself. As a proof of concept, we instantiate our protocol model using fingerprints. In our protocol, we employ a threshold-based quantization mechanism, in order to group the minutiae in a predefined neighborhood. In this way, we increase the chance of user-server agreement on the same set of minutiae. Our protocol works in rounds. In each round, depending on the calculated similarity score on the common set of minutiae, the acceptance/rejection decision is made. Besides, we employ multi-criteria security analyses for our proposed protocol. These security analyses show that the generated keys possess acceptable randomness according to Shannon's entropy. In addition, the keys, which are generated after each protocol run, are indistinguishable from each other, as measured by the Hamming distance metric. Our protocol is also robust against brute-force, replay and impersonation attacks, proven by high attack complexity and low equal error rates

Protection of privacy in biometric data

Biometrics is commonly used in many automated veri cation systems offering several advantages over traditional veri cation methods. Since biometric features are associated with individuals, their leakage will violate individuals\u27 privacy, which can cause serious and continued problems as the biometric data from a person are irreplaceable. To protect the biometric data containing privacy information, a number of privacy-preserving biometric schemes (PPBSs) have been developed over the last decade, but they have various drawbacks. The aim of this paper is to provide a comprehensive overview of the existing PPBSs and give guidance for future privacy-preserving biometric research. In particular, we explain the functional mechanisms of popular PPBSs and present the state-of-the-art privacy-preserving biometric methods based on these mechanisms. Furthermore, we discuss the drawbacks of the existing PPBSs and point out the challenges and future research directions in PPBSs

Secure key agreement using cancelable and noninvertible biometrics based on periodic transformation

Nowadays, many of the security-providing applications use biometric-based authentication, such as electronic banking, health and social services, commercial applications and law enforcement. However, since each person’s biometrics is unique and not replaceable, once it is compromised, it will be compromised forever. Therefore, it is indeed hard for the users to trust biometrics. To overcome this problem, in this thesis, we propose a novel protocol SKA-CaNPT: Secure Key Agreement Protocol using Cancelable and Noninvertible Biometrics based on Periodic Transformation. In this research, we use a periodic transformation function to make our biometrics cancelable and noninvertible. At the very end of our SKA-CaNPT protocol, the user and the server make an agreement on a symmetric shared key that is based on the feature points of the biometrics of the user. As a proof of concept, we apply our SKA-CaNPT protocol on fingerprints. In our protocol, after extracting minutiae from the fingerprints, we first employ a periodic transformation function and then we categorize our minutiae points in a predefined neighborhood by using a threshold-based quantization mechanism. Our SKA-CaNPT protocol runs in a round-manner and in each round, the server decides about the acceptance or rejection of the user according to the similarity score of the common minutiae. In addition, if the transformed data is compromised, it can be renewed just by changing one of the inputs of our transformation function. Besides, we apply different security analyses on our protocol. First of all, we use Shannon’s entropy to analyze the randomness of the agreed keys, and it shows that the generated keys have enough randomness. Secondly, to analyze the distinctiveness of the agreed keys, we use the Hamming distance metric, results of which show that the keys of different people are distinguishable from each other. Moreover, according to the low IKGR (Incorrect Key Generation Rate), high CKGR (Correct Key Generation Rate) and high attack complexity possessed by our SKA-CaNPT protocol, we can conclude that our scheme is secure against brute-force, replay and impersonation attacks