112 research outputs found
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
Privacy Protection in Distributed Fingerprint-based Authentication
Biometric authentication is getting increasingly popular due to the
convenience of using unique individual traits, such as fingerprints, palm
veins, irises. Especially fingerprints are widely used nowadays due to the
availability and low cost of fingerprint scanners. To avoid identity theft or
impersonation, fingerprint data is typically stored locally, e.g., in a trusted
hardware module, in a single device that is used for user enrollment and
authentication. Local storage, however, limits the ability to implement
distributed applications, in which users can enroll their fingerprint once and
use it to access multiple physical locations and mobile applications
afterwards.
In this paper, we present a distributed authentication system that stores
fingerprint data in a server or cloud infrastructure in a privacy-preserving
way. Multiple devices can be connected and perform user enrollment or
verification. To secure the privacy and integrity of sensitive data, we employ
a cryptographic construct called fuzzy vault. We highlight challenges in
implementing fuzzy vault-based authentication, for which we propose and compare
alternative solutions. We conduct a security analysis of our biometric
cryptosystem, and as a proof of concept, we build an authentication system for
access control using resource-constrained devices (Raspberry Pis) connected to
fingerprint scanners and the Microsoft Azure cloud environment. Furthermore, we
evaluate the fingerprint matching algorithm against the well-known FVC2006
database and show that it can achieve comparable accuracy to widely-used
matching techniques that are not designed for privacy, while remaining
efficient with an authentication time of few seconds.Comment: This is an extended version of the paper with the same title which
has been accepted for publication at the Workshop on Privacy in the
Electronic Society (WPES 2019
Ensuring patients privacy in a cryptographic-based-electronic health records using bio-cryptography
Several recent works have proposed and implemented cryptography as a means to
preserve privacy and security of patients health data. Nevertheless, the
weakest point of electronic health record (EHR) systems that relied on these
cryptographic schemes is key management. Thus, this paper presents the
development of privacy and security system for cryptography-based-EHR by taking
advantage of the uniqueness of fingerprint and iris characteristic features to
secure cryptographic keys in a bio-cryptography framework. The results of the
system evaluation showed significant improvements in terms of time efficiency
of this approach to cryptographic-based-EHR. Both the fuzzy vault and fuzzy
commitment demonstrated false acceptance rate (FAR) of 0%, which reduces the
likelihood of imposters gaining successful access to the keys protecting
patients protected health information. This result also justifies the
feasibility of implementing fuzzy key binding scheme in real applications,
especially fuzzy vault which demonstrated a better performance during key
reconstruction
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
CALIPER: Continuous Authentication Layered with Integrated PKI Encoding Recognition
Architectures relying on continuous authentication require a secure way to
challenge the user's identity without trusting that the Continuous
Authentication Subsystem (CAS) has not been compromised, i.e., that the
response to the layer which manages service/application access is not fake. In
this paper, we introduce the CALIPER protocol, in which a separate Continuous
Access Verification Entity (CAVE) directly challenges the user's identity in a
continuous authentication regime. Instead of simply returning authentication
probabilities or confidence scores, CALIPER's CAS uses live hard and soft
biometric samples from the user to extract a cryptographic private key embedded
in a challenge posed by the CAVE. The CAS then uses this key to sign a response
to the CAVE. CALIPER supports multiple modalities, key lengths, and security
levels and can be applied in two scenarios: One where the CAS must authenticate
its user to a CAVE running on a remote server (device-server) for access to
remote application data, and another where the CAS must authenticate its user
to a locally running trusted computing module (TCM) for access to local
application data (device-TCM). We further demonstrate that CALIPER can leverage
device hardware resources to enable privacy and security even when the device's
kernel is compromised, and we show how this authentication protocol can even be
expanded to obfuscate direct kernel object manipulation (DKOM) malwares.Comment: Accepted to CVPR 2016 Biometrics Worksho
- …