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 bio-metric systems are beginning to proliferate into the core physical and information infrastructure of our society.

Abstract-Multibiometric systems are being increasingly deployed in many large scale biometric applications (e.g., FBI-IAFIS, UIDAI system in India) because they have several advantages such as lower error rates and larger population coverage compared to unibiometric systems. However, multibiometric systems require storage of multiple biometric templates (e.g., fingerprint, iris, and face) for each user, which results in increased risk to user privacy and system security. One method to protect individual templates is to store only the secure sketch generated from the corresponding template using a biometric cryptosystem. This requires storage of multiple sketches. In this paper, we propose a feature level fusion framework to simultaneously protect multiple templates of a user as a single secure sketch. Our main contributions include: (i) practical implementation of the proposed feature level fusion framework using two wellknown biometric cryptosystems, namely, fuzzy vault and fuzzy commitment, and (ii) detailed analysis of the trade-off between matching accuracy and security in the proposed multibiometric cryptosystems based on two different databases (one real and one virtual multimodal database), each containing the three most popular biometric modalities, namely, fingerprint, iris, and face. Experimental results show that both the multibiometric cryptosystems proposed here have higher security and matching performance compared to their unibiometric counterparts.

One of the critical steps in designing a secure biometric system is protecting the templates of the users that are stored either in a central database or on smart cards. If a biometric template is compromised, it leads to serious security and privacy threats because unlike passwords, it is not possible for a legitimate user to revoke his biometric identifiers and switch to another set of uncompromised identifiers. One methodology for biometric template protection is the template transformation approach, where the template, consisting of the features extracted from the biometric trait, is transformed using parameters derived from a user specific password or key. Only the transformed template is stored and matching is performed directly in the transformed domain. In this paper, we formally investigate the security strength of template transformation techniques and define six metrics that facilitate a holistic security evaluation. Furthermore, we analyze the security of two wellknown template transformation techniques, namely, Biohashing and cancelable fingerprint templates based on the proposed metrics. Our analysis indicates that both these schemes are vulnerable to intrusion and linkage attacks because it is relatively easy to obtain either a close approximation of the original template (Biohashing) or a pre-image of the transformed template (cancelable fingerprints). We argue that the security strength of template transformation techniques must also consider the computational complexity of obtaining a complete pre-image of the transformed template in addition to the complexity of recovering the original biometric template.

Abstract. Security of stored templates is a critical issue in biometric systems because biometric templates are non-revocable. Fuzzy vault is a cryptographic framework that enables secure template storage by binding the template with a uniformly random key. Though the fuzzy vault framework has proven security properties, it does not provide privacy-enhancing features such as revocability and protection against cross-matching across different biometric systems. Furthermore, non-uniform nature of biometric data can decrease the vault security. To overcome these limitations, we propose a scheme for hardening a fingerprint minutiae-based fuzzy vault using password. Benefits of the proposed password-based hardening technique include template revocability, prevention of cross-matching, enhanced vault security and a reduction in the False Accept Rate of the system without significantly affecting the False Reject Rate. Since the hardening scheme utilizes password only as an additional authentication factor (independent of the key used in the vault), the security provided by the fuzzy vault framework is not affected even when the password is compromised.

No abstract

a b s t r a c tSecurity concerns regarding the stored biometric data is impeding the widespread public acceptance of biometric technology. Though a number of bio-crypto algorithms have been proposed, they have limited practical applicability due to the trade-off between recognition performance and security of the template. In this paper, we improve the recognition performance as well as the security of a fingerprint based biometric cryptosystem, called fingerprint fuzzy vault. We incorporate minutiae descriptors, which capture ridge orientation and frequency information in a minutia's neighborhood, in the vault construction using the fuzzy commitment approach. Experimental results show that with the use of minutiae descriptors, the fingerprint matching performance improves from an FAR of 0.7% to 0.01% at a GAR of 95% with some improvement in security as well. An analysis of security while considering two different attack scenarios is also presented.

No abstract

Many transformation functions have been proposed for generating revocable or non-invertible biometric templates. However, their security analysis either ignores the distribution of biometric features or uses inefficient feature matching. This usually leads to unrealistic estimates of security. In this paper we introduce a new measure of non-invertibility, called the Coverage-Effort (CE) curve which measures the number of guesses (Effort) required by an adversary to recover a certain fraction (Coverage) of the original biometric data. In addition to utilizing the feature distribution, the CE curve allows estimation of security against partial recovery of biometric features. We analyze the CE curves obtained using different instances of a mixture of Gaussians based feature transform for fingerprint templates. Our analysis shows that knowledge of the fingerprint minutiae distribution reduces the effort required to obtain a specified coverage.