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.

System and method for multi-party validation, authentication and/or authorization via biometrics

Abstract: A system and method for multi-party authentication is described. The multi-party authentication process uses synchronous and persistent biometrics signals received from parties to a transaction, based on a policy, to approve a transaction request. The biometrics signals preferably are expressed as compressed video signals having steganographically inserted challenge response data. Several business applications are described that are based on the multi-party authentication engine.

Diversity in Faces.

Abstract: Face recognition is a long standing challenge in the field of Artificial Intelligence (AI). The goal is to create systems that accurately detect, recognize, verify, and understand human faces. There are significant technical hurdles in making these systems accurate, particularly in unconstrained settings due to confounding factors related to pose, resolution, illumination, occlusion, and viewpoint. However, with recent advances in neural networks, face recognition has achieved unprecedented accuracy, largely built on data-driven deep learning methods. While this is encouraging, a critical aspect that is limiting facial recognition accuracy and fairness is inherent facial diversity. Every face is different. Every face reflects something unique about us. Aspects of our heritage - including race, ethnicity, culture, geography - and our individual identify - age, gender, and other visible manifestations of self-expression, are reflected in our faces. We expect face recognition to work equally accurately for every face. Face recognition needs to be fair. As we rely on data-driven methods to create face recognition technology, we need to ensure necessary balance and coverage in training data. However, there are still scientific questions about how to represent and extract pertinent facial features and quantitatively measure facial diversity. Towards this goal, Diversity in Faces (DiF) provides a data set of one million annotated human face images for advancing the study of facial diversity. The annotations are generated using ten well-established facial coding schemes from the scientific literature. The facial coding schemes provide human-interpretable quantitative measures of facial features. We believe that by making the extracted coding schemes available on a large set of faces, we can accelerate research and development towards creating more fair and accurate facial recognition systems.

Secure data hiding in wavelet compressed fingerprint images

Abstract: With the rapid growth of the Internet, electronic commerce revenue now amounts to several billion US dollars. To avoid fraud and misuse, buyers and sellers desire more secure methods of authentication than today's userid and password combinations. Automated biometrics technology in general, and fingerprints in particular, provide an accurate and reliable authentication method. However, fingerprint-based authentication requires accessing fingerprint images scanned remotely at the user's workstation, a potentially weak point in the security system. Stored or synthetic fingerprint images might be fraudulently transmitted, even if the communication channel itself is encrypted. In this paper we describe an algorithm for secure data hiding in wavelet compressed fingerprint images to alleviate this problem. Assuming the image capture device is secure, then only the decompressor on the server can locate the embedded message and thereby validate the submitted image.

Sectored Random Projections for Cancelable Iris Biometrics

Abstract: Privacy and security are essential requirements in practical biometric systems. In order to prevent the theft of biometric patterns, it is desired to modify them through revocable and non invertible transformations called Cancelable Biometrics. In this paper, we propose an efficient algorithm for generating a Cancelable Iris Biometric based on Sectored Random Projections. Our algorithm can generate a new pattern if the existing one is stolen, retain the original recognition performance and prevent extraction of useful information from the transformed patterns. Our method also addresses some of the drawbacks of existing techniques and is robust to degradations due to eyelids and eyelashes.

Business system and method using a distorted biometrics

Abstract: A method of doing business is disclosed that transforms a biometric used by a user in a transaction. The transformation creates a distorted biometric. The distorted biometric is used to identify the user to another party without requiring the user to provide actual physical or behavioral characteristics about himself to the other party.

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.