Nalini K. Ratha

Bio: Nalini K. Ratha is an academic researcher from IBM. The author has contributed to research in topics: Biometrics & Fingerprint recognition. The author has an hindex of 50, co-authored 216 publications receiving 12290 citations. Previous affiliations of Nalini K. Ratha include Michigan State University & University at Buffalo.

The relation between the ROC curve and the CMC

Abstract: The cumulative match curve (CMC) is used as a measure of 1: m identification system performance. It judges the ranking capabilities of an identification system. The receiver operating characteristic curve (ROC curve) of a verification system, on the other hand, expresses the quality of a 1:1 matcher. The ROC plots the false accept rate (FAR) of a 1:1 matcher versus the false reject rate (FRR) of the matcher. We show that the CMC is also related to the FAR and FRR of a 1:1 matcher, i.e., the matcher that is used to rank the candidates by sorting the scores. This has as a consequence that when a 1:1 matcher is used for identification, that is, for sorting match scores from high to low, the CMC does not offer any additional information beyond the FAR and FRR curves. The CMC is just another way of displaying the data and can be computed from the FAR and FRR.

Cancelable Biometrics: A Case Study in Fingerprints

Abstract: Biometrics offers usability advantages over traditional token and password based authentication schemes, but raises privacy and security concerns. When compromised, credit cards and passwords can be revoked or replaced while biometrics are permanently associated with a user and cannot be replaced. Cancelable biometrics attempt to solve this by constructing revocable biometric templates. We present several constructs for cancelable templates us- ing feature domain transformations and empirically exam- ine their efficacy. We also present a method for accurate registration which is a key step in building cancelable trans- forms. The overall approach has been tested using large databases and our results demonstrate that without losing much accuracy, we can build a large number of cancelable transforms for fingerprints.

Cancelable iris biometric

Abstract: A person only has two irises - if his pattern is stolen he quickly runs out of alternatives. Thus methods that protect the true iris pattern need to be adopted in practical biometric applications. In particular, it is desirable to have a system that can generate a new unique pattern if the one being used is lost, or generate different unique patterns for different applications to prevent cross-matching. For backwards compatibility, these patterns should look like plausible irises so they can be handled with the same processing tools. However, they should also non-invertibly hide the true biometric so it is never exposed, or even stored. In this paper four such ldquocancelablerdquo biometric methods are proposed that work with conventional iris recognition systems, either at the unwrapped image level or at the binary iris code level.

Anonymous and Revocable Fingerprint Recognition

Abstract: Biometric identification has numerous advantages over conventional ID and password systems; however, the lack of anonymity and revocability of biometric templates is of concern. Several methods have been proposed to address these problems. Many of the approaches require a precise registration before matching in the anonymous domain. We introduce binary string representations of fingerprints that obviates the need for registration and can be directly matched. We describe several techniques for creating anonymous and revocable representations using these binary string representations. The match performance of these representations is evaluated using a large database of fingerprint images. We prove that given an anonymous representation, it is computationally infeasible to invert it to the original fingerprint, thereby preserving privacy. To the best of our knowledge, this is the first linear, anonymous and revocable fingerprint representation that is implicitly registered.

System and method for distorting a biometric for transactions with enhanced security and privacy

Abstract: Authentication methods are very important in several applications. Existing methods of authentication based on possessions or knowledge have several problems that can be overcome by using biometrics. Unfortunately biometrics-based authentication is unrevocable today and has many privacy concerns in users' minds. The proposed technique employs signal scrambling and morphing techniques to intentionally distort the original biometrics signal in a non-invertible fashion. If the security is compromised, the system can cancel a particular distortion and reacquire the signal with a new distortion function. This provides functionality as good as non-biometric authentication methods in terms of their power of revocation.

Data clustering: a review

Abstract: Clustering is the unsupervised classification of patterns (observations, data items, or feature vectors) into groups (clusters). The clustering problem has been addressed in many contexts and by researchers in many disciplines; this reflects its broad appeal and usefulness as one of the steps in exploratory data analysis. However, clustering is a difficult problem combinatorially, and differences in assumptions and contexts in different communities has made the transfer of useful generic concepts and methodologies slow to occur. This paper presents an overview of pattern clustering methods from a statistical pattern recognition perspective, with a goal of providing useful advice and references to fundamental concepts accessible to the broad community of clustering practitioners. We present a taxonomy of clustering techniques, and identify cross-cutting themes and recent advances. We also describe some important applications of clustering algorithms such as image segmentation, object recognition, and information retrieval.

Handbook of Fingerprint Recognition

Abstract: A major new professional reference work on fingerprint security systems and technology from leading international researchers in the field Handbook provides authoritative and comprehensive coverage of all major topics, concepts, and methods for fingerprint security systems This unique reference work is an absolutely essential resource for all biometric security professionals, researchers, and systems administrators

Fingerprint image enhancement: algorithm and performance evaluation

Abstract: In order to ensure that the performance of an automatic fingerprint identification/verification system will be robust with respect to the quality of input fingerprint images, it is essential to incorporate a fingerprint enhancement algorithm in the minutiae extraction module. We present a fast fingerprint enhancement algorithm, which can adaptively improve the clarity of ridge and valley structures of input fingerprint images based on the estimated local ridge orientation and frequency. We have evaluated the performance of the image enhancement algorithm using the goodness index of the extracted minutiae and the accuracy of an online fingerprint verification system. Experimental results show that incorporating the enhancement algorithm improves both the goodness index and the verification accuracy.

[서평]「Applied Cryptography」

Abstract: The objective of this paper is to give a comprehensive introduction to applied cryptography with an engineer or computer scientist in mind. The emphasis is on the knowledge needed to create practical systems which supports integrity, confidentiality, or authenticity. Topics covered includes an introduction to the concepts in cryptography, attacks against cryptographic systems, key use and handling, random bit generation, encryption modes, and message authentication codes. Recommendations on algorithms and further reading is given in the end of the paper. This paper should make the reader able to build, understand and evaluate system descriptions and designs based on the cryptographic components described in the paper.