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Information Assurance Publications

Publications

Books and Book Chapters

Performance Prediction Methodology for Multi-Biometric Systems, in Face Biometrics for Personal Identification
N. A. Schmid and J. A. O'Sullivan, Performance Prediction Methodology for Multi-Biometric Systems, in Face Biometrics for Personal Identification. Multi-Sensory Multi-Modal Systems, Springer-Verlag, Berlin, Ch. 13, pp.213-230, 2007.
Abstract
In the selection of biometrics for use in a recognition system and in the subsequent design of the system, the predicted performance is a key consideration. The realizations of the biometric signatures or vectors of features extracted from the signatures can be modeled as realizations of random processes. These random processes and the resulting distributions on the measurements determine bounds on the performance regardless of the implementation of the recognition system. Given the underlying random processes, two techniques are applied to determine performance bounds. First, large deviations analysis is applied to bound performance in (M+1)-ary hypothesis testing problems where the number of hypotheses is fixed as a measure of the fidelity of the measurements increases. Second, the capacity of a recognition system as a function of the desired error rate is explored. The recognition system is directly analogous to a communication problem with random coding. Examples where signatures are modeled to be Gaussian distributed are considered in detail.



SVM based adaptive biometric image enhancement using quality assessment
R. Singh, M. Vatsa, and A. Noore, " SVM based adaptive biometric image enhancement using quality assessment ", in Speech, Audio, Image and Biomedical Signal Processing using Neural Networks, B. Prasad and M. Prasanna (editors), Springer-Verlag Publishers, accepted (accepted 2007).



Computational Intelligence Methods in Software Reliability Prediction
L. Tian, and A. Noore, " Computational Intelligence Methods in Software Reliability Prediction ", in Computational Intelligence in Reliability Engineering, G. Levitin (editor), Springer-Verlag Publishers, vol. 39, pp. 375-398, 2007.



Handbook of Multibiometrics
A. Ross, K. Nandakumar and A. K. Jain, "Handbook of Multibiometrics", Springer Publishers, 1st edition, 2006. ISBN: 0-3872-2296-0.
Abstract
Reliable human authentication schemes are of paramount importance in our highly networked society. Advances in biometrics help address the myriad of problems associated with traditional human recognition methods. The performance and benefits of a biometric system can be significantly enhanced by consolidating the evidence presented by multiple biometric sources. Multibiometric systems are expected to meet the stringent performance requirements imposed by large-scale authentication systems. The Handbook of Multibiometrics, a professional book, introduces multibiometric systems, and demonstrates the noteworthy advantages of these systems over their unimodal counterparts. In addition, this book describes in detail the various scenarios possible when fusing biometric evidence from multiple information sources. This comprehensive volume on multibiometric systems, also outlines with examples the different fusion methodologies that have been proposed by researchers to integrate multiple biometric traits.



Intelligent Biometric Information Fusion using Support Vector Machine
R. Singh, M. Vatsa, and A. Noore, " Intelligent Biometric Information Fusion using Support Vector Machine ", in Soft Computing in Image Processing: Recent Advances, M. Nachtegael, D. Weken, E. Kerre, and W. Philips (editors), Springer-Verlag Publishers, Chapter 12, pp. 327-350, 2006.



Handbook of Biometrics
A. K. Jain, P. J. Flynn and A. Ross (Editors), "Handbook of Biometrics", Springer Publishers. ISBN: 978-0-387-71040-2.
Abstract
Biometric recognition, or simply biometrics, is a rapidly evolving field with applications ranging from accessing one's computer, to gaining entry into a country. Biometric systems rely on the use of physical or behavioral traits, such as fingerprints, face, voice and hand geometry, to establish the identity of an individual. The deployment of large-scale biometric systems in both commercial (e.g., grocery stores, amusement parks, airports) and government (e.g., US-VISIT) applications, increases the public's awareness of this technology. This rapid growth also highlights the challenges associated with designing and deploying biometric systems. Indeed, the problem of biometric recognition is a grand challenge in its own right. The past five years have seen a significant growth in biometric research resulting in the development of innovative sensors, robust and efficient algorithms for feature extraction and matching, enhanced test methodologies and novel applications. These advances have resulted in robust, accurate, secure and cost effective biometric systems. The Handbook of Biometrics describes the fundamentals as well as the latest advancements in the burgeoning field of biometrics. It is designed for professionals, practitioners and researchers in biometrics, pattern recognition and computer security. The Handbook of Biometrics can be used as a primary textbook for an undergraduate biometrics class. This book is also suitable as a secondary textbook or reference for advanced-level students in computer science.

Journal Publications

A Mosaicing Scheme for Pose Invariant Face Recognition
R. Singh, M. Vatsa, A. Ross and A. Noore, "A Mosaicing Scheme for Pose Invariant Face Recognition," IEEE Transactions on Systems, Mans and Cybernetics - B, Special Issue on Biometrics, Volo. 37, Issue 5, pp. 1212- 1225, October 2007.



From Template to Image: Reconstructing Fingerprints From Minutiae Points
A. Ross, J. Shah and A. K. Jain, "From Template to Image: Reconstructing Fingerprints From Minutiae Points," IEEE Transactions on Pattern Analysis and Machine Intelligence, Special Issue on Biometrics, Vol. 29, No. 4, pp. 544-560, April 2007.



On Generation and Analysis of Synthetic Iris Images
J. Zuo, N. A. Schmid, X. Chen, " On Generation and Analysis of Synthetic Iris Images, " in IEEE Trans. on Information Forensics and Security, vol. 2, no. 1, pp. 77-90, March 2007.
Abstract
The popularity of iris biometric has grown considerably over the past two to three years. It has resulted in the development of a large number of new iris encoding and processing algorithms. Since there are no publicly available large-scale and even medium-size data bases, neither of the newly designed algorithms has undergone extensive testing. The designers claim exclusively high recognition performance when the algorithms are tested on a small amount of data. In a large-scale setting, systems are yet to be tested. Since the issues of security and privacy slow down the speed of collecting and publishing iris data, an optional solution to the problem of algorithm testing is to synthetically generate a large scale data base of iris images. In this work, we describe a model-based method to generate iris images and evaluate the performance of synthetic irises by using a traditional Gabor filter-based iris recognition system. A comprehensive comparison of synthetic and real data is performed at three levels of processing: 1) image level, 2) texture level, and 3) decision level. A sensitivity analysis is performed to conclude on the importance of various parameters involved in generating iris images



Human Recognition Using Biometrics: An Overview
A. Ross and A. K. Jain, "Human Recognition Using Biometrics: An Overview," Annals of Telecommunications, Vol. 62, No. 1/2, pp. 11-35, January/February 2007.



On Techniques for Angle Compensation in Nonideal Iris Recognition
S. A. C. Schuckers, N. A. Schmid, A. Abhyankar, V. Dorairaj, C. Boyce, L. A. Hornak, " On Techniques for Angle Compensation in Nonideal Iris Recognition, " IEEE Trans. on System, Man, and Cybernetics, Part B, vol. 37, no. 5, pp. 1176-1190, 2007.
Abstract
The popularity of the iris biometric has grown considerably over the past two to three years. Most research has been focused on the development of new iris processing and recognition algorithms for frontal view iris images. However, a few challenging directions in iris research have been identified, including processing of a nonideal iris and iris at a distance. In this paper, we describe two nonideal iris recognition systems and analyze their performance. The word ldquononidealrdquo is used in the sense of compensating for off-angle occluded iris images. The system is designed to process nonideal iris images in two steps: 1) compensation for off-angle gaze direction and 2) processing and encoding of the rotated iris image. Two approaches are presented to account for angular variations in the iris images. In the first approach, we use Daugman's integrodifferential operator as an objective function to estimate the gaze direction. After the angle is estimated, the off-angle iris image undergoes geometric transformations involving the estimated angle and is further processed as if it were a frontal view image. The encoding technique developed for a frontal image is based on the application of the global independent component analysis. The second approach uses an angular deformation calibration model. The angular deformations are modeled, and calibration parameters are calculated. The proposed method consists of a closed-form solution, followed by an iterative optimization procedure. The images are projected on the plane closest to the base calibrated plane. Biorthogonal wavelets are used for encoding to perform iris recognition. We use a special dataset of the off-angle iris images to quantify the performance of the designed systems. A series of receiver operating characteristics demonstrate various effects on the performance of the nonideal-iris-based recognition system.



Improving Long Range and High Magnification Face Recognition: Database Acquisition, Evaluation and Enhancement
Y. Yao, B. R. Abidi, N. D. Kalka, N. A. Schmid, and M. A. Abidi, " Improving Long Range and High Magnification Face Recognition: Database Acquisition, Evaluation and Enhancement, " in Computer Vision and Image Understanding, Elsevier, 2007, in press
Abstract
In this paper, we describe a face video database, UTK-LRHM, acquired from long distances and with high magnifications. Both indoor and outdoor sequences are collected under uncontrolled surveillance conditions. To our knowledge, it is the first database to provide face images from long distances (indoor: 10-16 m and outdoor: 50-300 m). The corresponding system magnifications range from 3x to 20x for indoor and up to 284x for outdoor. This database has applications in experimentations with human identification and authentication in long range surveillance and wide area monitoring. Deteriorations unique to long range and high magnification face images are investigated in terms of face recognition rates based on the UTK-LRHM database. Magnification blur is shown to be a major degradation source, the effect of which is quantified using a novel blur assessment measure and alleviated via adaptive deblurring algorithms. A comprehensive processing algorithm, including frame selection, enhancement, and super-resolution is introduced for long range and high magnification face images with a large variety of resolutions. Experimental results using face images of the UTK-LRHM database demonstrate a significant improvement in recognition rates after assessment and enhancement of degradations.



Biometrics: A Tool For Information Security
A. K. Jain, A. Ross and S. Pankanti, "Biometrics: A Tool For Information Security", IEEE Transactions on Information Forensics and Security, Vol 1, No. 2, pp. 125-143, June 2006.



Performance Analysis of Iris-Based Identification System at the Matching Score Level
N. A. Schmid, M. V. Ketkar, H. Singh, B. Cukic, Performance Analysis of Iris-Based Identification System at the Matching Score Level, IEEE Transactions on Information Forensics and Security, Vol. 1, No. 2, June 2006, pp 154-168.
Abstract
Practical iris-based identification systems are easily accessible for data collection at the matching score level. In a typical setting, a video camera is used to collect a single frontal view image of good quality. The image is then preprocessed, encoded, and compared with all entries in the biometric database resulting in a single highest matching score. In this paper, we assume that multiple scans from the same iris are available and design the decision rules based on this assumption. We consider the cases where vectors of matching scores may be described by a Gaussian model with dependent components under both genuine and imposter hypotheses. Two test statistics: the plug-in loglikelihood ratio and the average Hamming distance are designed. We further analyze the performance of filter-based iris recognition systems. The model fit is verified using the Shapiro-Wilk test for normality. We show that the loglikelihood ratio with well-estimated maximum-likelihood parameters in it often outperforms the average Hamming distance statistic. The problem of identification with M iris classes is further stated as an (M+1)ary hypothesis testing problem. We use empirical approach, Chernoff bound, and Large Deviations approach to predict the performance of the iris-based identification system. The bound on the probability of error is evaluated as a function of the number of classes and the number of iris scans per class.



Fingerprint Warping Using Ridge Curve Correspondences
A. Ross, S. Dass and A. K. Jain, "Fingerprint Warping Using Ridge Curve Correspondences", IEEE Transactions on Pattern Analysis and Machine Intelligence, Vol. 28, No. 1, pp. 19-30, January 2006.



Verification and Validation of a Fingerprint Image Registration Software
D. Desovski, V. Gandikota, Y. Liu, Y. Jiang, B. Cukic, Verification and Validation of a Fingerprint Image Registration Software, EURASIP Journal on Applied Signal Processing, Vol. 2006, Article ID 15940, pp. 1-9.
Abstract
The need for reliable identification and authentication is driving the increased use of biometric devices and systems. Verification and validation techniques applicable to these systems are rather immature and ad hoc, yet the consequences of the wide deployment of biometric systems could be significant. In this paper we discuss an approach towards validation and reliability estimation of a fingerprint registration software. Our validation approach includes the following three steps: (a) the validation of the source code with respect to the system requirements specification; (b) the validation of the optimization algorithm, which is in the core of the registration system; and c) the automation of testing. Since the optimization algorithm is heuristic in nature, mathematical analysis and test results are used to estimate the reliability and perform failure analysis of the image registration module.



Score Normalization in Multimodal Biometric Systems
A. K. Jain, K. Nandakumar and A. Ross, "Score Normalization in Multimodal Biometric Systems", Pattern Recognition, Vol. 38, No. 12, pp. 2270-2285, December 2005.



Face Detection Using Statistical and Multiresolution Texture Features
V. Manian and A. Ross, "Face Detection Using Statistical and Multiresolution Texture Features", Multimedia Cyberscape Journal, Special Issue on Pattern Recognition in Biometrics and Bioinformatics, Vol. 3, No. 3, pp. 1-9, 2005.



A Deformable Model for Fingerprint Matching
A. Ross, S. Dass and A. K. Jain, "A Deformable Model for Fingerprint Matching", Pattern Recognition, Vol. 38, No. 1, pp. 95-103, Jan 2005.



Performance Prediction Methodology for Biometric Systems Using a Large Deviations Approach
N. A. Schmid, J. A. O'Sullivan, " Performance Prediction Methodology for Biometric Systems Using a Large Deviations Approach, " IEEE Trans. on Signal Processing, Supplement on Secure Media, vol. 52, no. 10, Oct. 2004, pp. 3036 - 3045.
Abstract
In the selection of biometrics for use in a recognition system and in the subsequent design of the system, the predicted performance is a key consideration. The realizations of the biometric signatures or vectors of features extracted from the signatures can be modeled as realizations of random processes. These random processes and the resulting distributions on the measurements determine bounds on the performance, regardless of the implementation of the recognition system. Given the underlying random processes, two techniques are applied to determine performance bounds. First, large deviation analysis is applied to bound performance in (M+1)-ary hypothesis testing problems, where the number of hypotheses is fixed as a measure of the fidelity of the measurements increases. Second, the capacity of a recognition system as a function of the desired error rate is explored. The recognition system is directly analogous to a communication problem with random coding. The recognition reliability function then determines the error rate as a function of the exponential growth rate of the number of hypotheses. Gaussian and binary examples are considered in detail. Performance prediction in the binary example is compared with performance prediction results for iris recognition systems using Daugman's IrisCode.



Modeling and Quantification of Security Attributes of Software Systems
B.B.Madan, K.Goseva - Popstojanova, K. Vaidyanathan, K.S.Trivedi, " Modeling and Quantification of Security Attributes of Software Systems ", in Proceedings of the 2002 International Conference on Dependable Systems & Networks, IEEE International Performance and Dependability Symposium (IPDS 2002) track, Washington, DC, June 2002, pp. 505-514. (Selected among papers which have strong archival value. Its expanded version is accepted for publication in the special issue of Performance Evaluation Journal).
Abstract
Quite often failures in network based services and server systems may not be accidental, but rather caused by deliberate security intrusions. We would like such systems to either completely preclude the possibility of a security intrusion or design them to be robust enough to continue functioning despite security attacks. Not only is it important to prevent or tolerate security intrusions, it is equally important to treat security as a QoS attribute at par with, if not more important than other QoS attributes such as availability and performability. This paper deals with various issues related to quantifying the security attribute of an intrusion tolerant system, such as the SITAR system. A security intrusion and the response of an intrusion tolerant system to the attack is modeled as a random process. This facilitates the use of stochastic modeling techniques to capture the attacker behavior as well as the system's response to a security intrusion. This model is used to analyze and quantify the security attributes of the system. The security quantification analysis is first carried out for steady-state behavior leading to measures like steady-state availability. By transforming this model to a model with absorbing states, we compute a security measure called the " mean time (or effort) to security failure " and also compute probabilities of security failure due to violations of different security attributes.



Characterizing Intrusion Tolerant Systems Using a State Transition Model
K. Goseva - Popstojanova, F.Wang, R.Wang, F.Gong, K. Vaidyanathan, K.S.Trivedi, B.Muthusamy, " Characterizing Intrusion Tolerant Systems Using a State Transition Model ", in Proceedings of DARPA Information Survivability Conference and Exposition II (DISCEX II), Anaheim, California, June 2001, Vol.II, pp.211-221.
Abstract
Intrusion detection and response research has so far mostly concentrated on known and well-defined attacks. We believe that this narrow focus of attacks accounts for both the successes and limitation of commercial intrusion detection systems (IDS). Intrusion tolerance, on the other hand, is inherently tied to functions and services that require protection. This paper presents a state transition model to describe the dynamic behavior of intrusion tolerant systems. This model provides a framework from which we can define the vulnerability and the threat set to be addressed. We also show how this model helps us to describe both known and unknown security exploits by focusing on impacts rather than specific attack procedures. By going through the exercise of mapping known vulnerabilities to this transition model, we identify a reasonably complete fault space that should be considered in a general intrusion tolerant system.



A Method for Modeling and Quantifying the Security Attributes of Intrusion Tolerant Systems
B.B.Madan, K.Goseva - Popstojanova, K. Vaidyanathan, K.S.Trivedi, " A Method for Modeling and Quantifying the Security Attributes of Intrusion Tolerant Systems ", Performance Evaluation Journal, accepted for publication.
Abstract
Complex software and network based information server systems may exhibit failures. Quite often, such failures may not be accidental. Instead some failures may be caused by deliberate security intrusions with the intent ranging from simple mischief, theft of confidential information to loss of crucial and possibly life saving services. Not only is it important to prevent and/or tolerate security intrusions, it is equally important to treat security as a QoS attribute at par with other QoS attributes such as availability and performance. This paper deals with various issues related to quantifying the security attributes of an intrusion tolerant system, such as the SITAR system. A security intrusion and the response of an intrusion tolerant system to an attack is modeled as a random process. This facilitates the use of stochastic modeling techniques to capture the attacker behavior as well as the system's response to a security intrusion. This model is used to analyze and quantify the security attributes of the system. The security quantification analysis is first carried out for steady-state behavior leading to measures like steady-state availability. By transforming this model to a model with absorbing states, we compute a security measure called the " mean time (or effort) to security failure " and also compute probabilities of security failure due to violations of different security attributes.

Conferences and Presentations

Age Transformation for Improving Face Recognition Performance
R. Singh, M. Vatsa, A. Noore, and S. K. Singh, " Age Transformation for Improving Face Recognition Performance ", Second International Conference on Pattern Recognition and Machine Intelligence, December 2007.



On Iris Quality, Quality Based Segmentation and Quality of Large Biometric Databases
N. A. Schmid, " On Iris Quality, Quality Based Segmentation and Quality of Large Biometric Databases. " Sample Quality Workshop, Gaithersburg, MD, Nov.7-8, 2007.



Progress Report II: Quality Based Restitution of Iris Features in High Zoom Images for Less Constrained Iris Recognition System
N. A. Schmid, " Progress Report II: Quality Based Restitution of Iris Features in High Zoom Images for Less Constrained Iris Recognition System, " Tucson, AZ, November 2007.



Technical Working Group in Education for Digital Evidence
R. S. Nutter, "Technical Working Group in Education for Digital Evidence," TWGED-DE, National Institute of Justice, November 2007. http://www.ncjrs.gov/pdffiles1/nij/grants/219380.pdf



Education Panel: Academia's Response to Law Enforcement's Needs
R. S. Nutter, " Education Panel: Academia's Response to Law Enforcement's Needs, " NW3C Economic Crime Summit, Arlington, VA, October 23-26, 2007.



An Introduction to Multibiometrics
A. Ross, "An Introduction to Multibiometrics," Proc. of the 15th European Signal Processing Conference (EUSIPCO), (Poznan, Poland), September 2007.



Unification of Evidence Theoretic Fusion Algorithms: A case study in Level-2 and level-3 Fingerprint Features
M. Vatsa, R. Singh, and A. Noore, " Unification of Evidence Theoretic Fusion Algorithms: A case study in Level-2 and level-3 Fingerprint Features ", IEEE Conference on Biometrics: Theory, Applications and Systems, September, 2007. Received Best Paper Award.



Extended Evaluation of Simulated Wavefront Coding Technology for Iris Recognition
K. Smith, P. Pauca, A. Ross, T. Torgersen and M. King, "Extended Evaluation of Simulated Wavefront Coding Technology for Iris Recognition," Proc. of the First IEEE International Conference on Biometrics: Theory, Applications and Systems, (Washington DC, USA), September 2007.



Error Encoded PDE-Textons for face recognition
U. Kandaswamy, D. Adjeroh, N. A. Schmid, and S. Schuckers, " Error Encoded PDE-Textons for face recognition, " in Proc. of IEEE AutoID Conf., June 7-8, Alghere, Italy, pp. 57-62, 2007.



Face Recognition in Video: Adaptive Fusion of Multiple Matchers
U. Park, A. K. Jain and A. Ross, "Face Recognition in Video: Adaptive Fusion of Multiple Matchers," Proc. of IEEE Computer Society Workshop on Biometrics (CVPRW), (Minneapolis, USA), June 2007.



Protecting Iris Images through Asymmetric Digital Watermarking
N. Bartlow, N. Kalka, B. Cukic and A. Ross, "Protecting Iris Images through Asymmetric Digital Watermarking," Proc. of 5th IEEE Workshop on Automatic Identification Advanced Technologies (AutoID), (Alghero, Italy), pp. 191-197, June 2007.



On a Local Ordinal Binary Extension to Gabor Wavelet-Based Encoding for Improved Iris Recognition
J. Zuo and N. A. Schmid, On a Local Ordinal Binary Extension to Gabor Wavelet-Based Encoding for Improved Iris Recognition, in Proc.of the BSYM 2007, Baltimore, MD, 2007.



2007 IEEE Workshop on Automatic Identification Advanced Technologies
N. Bartlow, N. Kalka, B. Cukic, A. Ross, Protecting Iris Images through Asymetric Digital Watermarking, 2007 IEEE Workshop on Automatic Identification Advanced Technologies, Alghero, Italy, June 2007.
Abstract
When biometric systems require raw images to be stored in centralized databases, it is imperative that appropriate measures are taken to secure these images. A combination of asymmetric digital watermarking and cryptography can serve as a powerful mechanism for facilitating such security needs. The combination of these techniques enables the system to handle many issues associated with storing and using raw biometric data. In this paper, we propose a framework that encodes voice feature descriptors in raw iris images thereby offering an example of a secure biometric system. The contributions of this work are as follows: application of biometric watermarking to iris images in order to provide an added level of authentication; a mechanism to validate the originating source of iris images; understanding levels in which watermarks can be compromised in a biometric system; and implementation of an asymmetric watermarking framework.



Iris Research Developments. Non-ideal Iris
N. A. Schmid, " Iris Research Developments. Non-ideal Iris. " i-Pira Biometric Series Conference on April 11-13, 2007 at the Westin Hotel in Washington, DC.



Augmenting Ridge Curves With Minutiae Triplets for Fingerprint Indexing
A. Ross and R. Mukherjee, "Augmenting Ridge Curves With Minutiae Triplets for Fingerprint Indexing," Proc. of SPIE Conference on Biometric Technology for Human Identification IV, (Orlando, USA), April 2007.



Progress Report I: Quality Based Restitution of Iris Features in High Zoom Images for Less Constrained Iris Recognition System
N. A. Schmid, " Progress Report I: Quality Based Restitution of Iris Features in High Zoom Images for Less Constrained Iris Recognition System, " Morgantown, WV, May 2007.



Super-Resolution for High Magnification Face Images
Y. Yao, N. D. Kalka, B. Abidi, N. A. Schmid, M. Abidi, Super-Resolution for High Magnification Face Images, in Proc. of the 2007 SPIE Symposium on Defense and Security, Conf. 6539, pp. 65390G1-65390G12.



Evaluating the Reliability of Credential Hardening through Keystroke Dynamics
N. Bartlow, B. Cukic, Evaluating the Reliability of Credential Hardening through Keystroke Dynamics, 17th IEEE Int`l Symposium on Software Reliability Engineering (ISSRE 2006), Raleigh, NC, Nov. 2006, pp. 117-126.
Abstract
Most computer systems rely on usernames and passwords as a mechanism for authentication and access control. These credential sets offer weak protection to a broad scope of applications with differing levels of sensitivity. Traditional physiological biometric systems such as fingerprint, face, and iris recognition are not readily deployable in remote authentication schemes. Keystroke dynamics provide the ability to combine the ease of use of username/password schemes with the increased trustworthiness associated with biometrics. Our research extends previous work on keystroke dynamics by incorporating shift-key patterns. The system is capable of operating at various points on a traditional ROC curve depending on application specific security needs. A 1% false accept rate is attainable at a 14% false reject rate. An equal error rate of 5% is suitable for systems requiring a relatively low security. As a username password authentication scheme, our approach decreases the system penetration rate associated with compromised passwords by 95%-99%. Said performance measures can be further improved through optimization of the classification algorithm on a user specific basis



A New Biometric Modality Based on Conjunctival Vasculature
R. Derakhshani, A. Ross and S. Crihalmeanu, "A New Biometric Modality Based on Conjunctival Vasculature," Proc. of Artificial Neural Networks in Engineering (ANNIE), (St. Louis, USA), November 2006.



Modeling the Performance of Border Inspections with Electronic Travel Documents
P. Bracchi, B. Cukic, V. Cortellessa, Modeling the Performance of Border Inspections with Electronic Travel Documents, 17th IEEE Int`l Symposium on Software Reliability Engineering (ISSRE 2006), Raleigh, NC, Nov. 2006, pp. 237-244.
Abstract
Increased security risk in international travel has resulted in the creation of new programs to determine the admissibility of foreign travelers at official ports of entry within a country. Primary program goals are improving border security and, at the same time, facilitating the flow of legitimate travelers. Major program requirements include the adoption of machine readable travel documents (i.e., passports, visas, etc.), the use of biometric identifiers, and the interoperability among multiple information systems for travelersy identity verification and background checks. Performance analysis of a border inspection system early in its development life-cycle is essential to predict its ability to meet established performance goals, to identify key performance drivers and potential bottlenecks and to suggest possible design improvements. This paper presents our experience with performance evaluation of a hypothetical inspection system. We adopt an analytical modeling technique based on layered queuing networks. Compared with similar studies which use extensive simulations, we observe that our methodology achieves comparably accurate results while being simpler and less costly



Generating Synthetic Irises By Feature Agglomeration
S. Shah and A. Ross, "Generating Synthetic Irises By Feature Agglomeration," Proc. of IEEE International Conference on Image Processing (ICIP), (Atlanta, USA), October 2006.



On Performance Comparison of Real and Synthetic Iris Images
J. Zuo, N. A. Schmid, and X. Chen, " On Performance Comparison of Real and Synthetic Iris Images, " in Proc. of 2006 Intern. Conf. on Image Processing, Atlanta GA, Oct. 11-14, pp. 305-308.



Non-Ideal Iris Recognition: Robust Segmentation and Algorithms (Final Report)
N.A. Schmid, S. Schuckers, G. Fahmy, X. Li, and L. Hornak, " Non-Ideal Iris Recognition: Robust Segmentation and Algorithms, " CITeR meeting, Morgantown, WV, October 11-12, 2006 (Final Report).



A Robust Iris Procedure for Unconstrained Subject Presentation
J. Zuo, N. D. Kalka, and N. A. Schmid, " A Robust Iris Procedure for Unconstrained Subject Presentation " in Proc. Biometrics Consortium Conf., Baltimore, Maryland September 19-21 2006.



High Magnification and Long Distance Face Recognition: Database Acquisition, Evaluation, and Enhancement
Y. Yao, B. Abidi, N. D. Kalka, N. Schmid, and M. Abidi, " High Magnification and Long Distance Face Recognition: Database Acquisition, Evaluation, and Enhancement, " in Proc. Biometrics Consortium Conf., Baltimore, Maryland September 19-21 2006.



Automatic Tooth Segmentation Using Active Contour Without Edges
S. Shah, A. Abaza, A. Ross and H. Ammar, "Automatic Tooth Segmentation Using Active Contour Without Edges," Proc. of Biometrics Symposium (BSYM), (Baltimore, USA), September 2006.



Segmenting Non-ideal Irises Using Geodesic Active Contours
A. Ross and S. Shah, "Segmenting Non-ideal Irises Using Geodesic Active Contours," Proc. of Biometrics Symposium (BSYM), (Baltimore, USA), September 2006.



Multispectral Iris Analysis: A Preliminary Study
C. Boyce, A. Ross, M. Monaco, L. Hornak and X. Li, "Multispectral Iris Analysis: A Preliminary Study," Proc. of IEEE Computer Society Workshop on Biometrics, (New York, USA), June 2006.



Non-Ideal Iris Recognition: Robust Segmentation and Algorithms (Progress Report)
N.A. Schmid, S. Schuckers, G. Fahmy, X. Li, and L. Hornak, " Non-Ideal Iris Recognition: Robust Segmentation and Algorithms, " CITeR meeting, Morgantown, WV, May 10-11, 2006 (Progress Report).



Revisiting Doddington's Zoo: A Systematic Method to Assess User-dependent Variabilities
N. Poh, S. Bengio and A. Ross, "Revisiting Doddington's Zoo: A Systematic Method to Assess User-dependent Variabilities", Proc. of Second Workshop on Multimodal User Authentication (MMUA), (Toulose, France), May 2006.



Image Quality Assessment for Iris Biometrics
N. D. Kalka, J. Zuo, V. Dorairaj, N. A. Schmid, and B. Cukic, " Image Quality Assessment for Iris Biometrics, " in Proc. of 2006 SPIE Conf. on Biometric Technology for Human Identification III, 17-18 April, Orlando, vol. 6202, pp. 61020D-1-61020D-12.



Image Quality Assessment for Iris Biometric
N. D. Kalka, J. Zuo, V. Dorairaj, N. A. Schmid, and B. Cukic, " Image Quality Assessment for Iris Biometric, " Accepted for publication in the Proc. of the SPIE 2006, Orlando, April 17 - 21, 2006.



A Calibration Model for Fingerprint Sensor Interoperability
A. Ross and R. Nadgir, "A Calibration Model for Fingerprint Sensor Interoperability", Proc. of SPIE Conference on Biometric Technology for Human Identification III, (Orlando, USA), pp. 62020B-1 - 62020B-12, April 2006.



Image Versus Feature Mosaicing: A Case Study in Fingerprints
A. Ross, S. Shah and J. Shah, "Image Versus Feature Mosaicing: A Case Study in Fingerprints", Proc. of SPIE Conference on Biometric Technology for Human Identification III, (Orlando, USA), pp. 620208-1 - 620208-12, April 2006.



Performance Analysis of Individual and Combined Quality Effects for Iris Biometrics
N. A. Schmid, " Performance Analysis of Individual and Combined Quality Effects for Iris Biometrics, " Workshop on Biometric Quality, NIST, March 8-9, 2006.
Dempster Shafer Theory based Classifier Fusion for Improved Fingerprint Verification Performance
R. Singh, M. Vatsa, A. Noore and S. K. Singh, " Dempster Shafer Theory based Classifier Fusion for Improved Fingerprint Verification Performance ", Computer Vision, Graphics and Image Processing Conference, LNCS 4338, pp. 941-949, 2006.
Non-Ideal Iris Recognition: Robust Segmentation and Algorithms (Progress Report)
N.A. Schmid, S. Schuckers, G. Fahmy, X. Li, and L. Hornak, " Non-Ideal Iris Recognition: Robust Segmentation and Algorithms, " CITeR meeting, Morgantown, WV, Nov. 8 - 9, 2005 (Progress Report).



Generation of Synthetic Irises (Final Report)
N. A. Schmid, A. Ross, and B. Cukic, " Generation of Synthetic Irises, " CITeR meeting, Morgantown, WV, Nov. 8 - 9, 2005 (Final Report).



Guidelines for Appropriate Use of Simulated Data for Bio-Authentication Research
Y. Ma, M. Schuckers, B. Cukic, Guidelines for Appropriate Use of Simulated Data for Bio-Authentication Research, 4th IEEE Workshop on Automatic Identification Advanced Technologies (AUTO ID), Buffalo, NY, October 2005, pp. 251-256.
Abstract
In this paper, we outline a framework for appropriate and proper usage of simulated data for biometric authentication research. Currently, there are no formal guidelines concerning the use of simulated data in the biometric authentication literature. Some have suggested the usage of simulated or synthetic data while others have advised against it. Our position is that there is a place for simulation data in biometrics research but that such implementations need to meet certain requirements. To that end, we describe conditions under which it is reasonable to use such data, as well as criteria for evaluating the appropriateness of a data generation methodology. This criteria is that models for generation of artificial data should be flexible, consistent and parsimonious. Along with justifying these criteria, we illustrate how simulated data might be used to evaluate a classifier.



Performance Enhancement of 2D Face Recognition via Mosaicking
R. Singh, M. Vatsa, A. Ross, and A. Noore, " Performance Enhancement of 2D Face Recognition via Mosaicking ", Proc. Fourth IEEE Workshop on Automatic Identification Advanced Technologies (AUTOID), October 2005. Received Best Paper Award.



Performance Enhancement of 2D Face Recognition via Mosaicing
R. Singh, M. Vatsa, A. Ross and A. Noore, "Performance Enhancement of 2D Face Recognition via Mosaicing", Proc. of 4th IEEE Workshop on Automatic Identification Advanced Technologies (AutoID), (Buffalo, USA), pp. 63-68, October 2005. Best Student Paper Award (Singh, Vatsa).



Generation of Synthetic Irises
N. A. Schmid and Jinyu Zuo, " Generation of Synthetic Irises " The Biometrics Consortium Conference, Crystal City, Arlington, VA, Sept. 19 - 21, 2005 (Oral).



Image Quality Assessment for Iris Biometric (Poster)
N. Kalka, J. Zuo, V. Dorairaj, N. A. Schmid, and B. Cukic, " Image Quality Assessment for Iris Biometric, " The Biometrics Consortium Conference, Crystal City, Arlington, VA, Sept. 19 - 21, 2005 (Poster).



Performance Evaluation of Non-Ideal Iris Based Recognition System Implementing Global ICA Technique
V. Dorairaj, N. A. Schmid, and G. Fahmy, " Performance Evaluation of Non-Ideal Iris Based Recognition System Implementing Global ICA Technique, " in Proc. of ICIP 2005, Genoa, Italy, vol. 3, Sept. 11-14, 2005, pp. 285-288.



Biometric Template Security: Challenges and Solutions
A. K. Jain, A. Ross and U. Uludag, "Biometric Template Security: Challenges and Solutions", Proc. of 13th European Signal Processing Conference (EUSIPCO), (Antalya, Turkey), September 2005.



Synthesis of Iris Images using Markov Random Fields
S. Makthal and A. Ross, "Synthesis of Iris Images using Markov Random Fields", Proc. of 13th European Signal Processing Conference (EUSIPCO), (Antalya, Turkey), September 2005.



Cell Phone Forensics
R. S. Nutter,"Cell Phone Forensics," Forensic Accounting Summer Program, WVU, July, 2005.



Secure Fingerprint Matching With External Registration
J. Reisman, U. Uludag and A. Ross, "Secure Fingerprint Matching With External Registration", Proc. of Audio- and Video-based Biometric Person Authentication (AVBPA), (Rye Brook, New York), pp. 720-729, July 2005.



A Classification Approach to Multi-biometric Score Fusion
Y. Ma, B. Cukic, H. Singh, A Classification Approach to Multi-biometric Score Fusion, 5th Int`l Conference on Audio and Video- Based Biometric Person Authentication, AVBPA 2005, Rye Town, NY, July 2005, Lecture Notes in Computer Science, Vol 3546, Springer, pp. 484-493, 2005.
Abstract
The use of biometrics for identity verification of an individual is increasing in many application areas such as border/port entry/exit, access control, civil identification and network security. Multi-biometric systems use more than one biometric of an individual. These systems are known to help in reducing false match and false non-match errors compared to a single biometric device. Several algorithms have been used in literature for combining results of more than one biometric device. In this paper we discuss a novel application of random forest algorithm in combining matching scores of several biometric devices for identity verification of an individual. Application of random forest algorithm is illustrated using matching scores data on three biometric devices: fingerprint, face and hand geometry. To investigate the performance of the random forest algorithm, we conducted experiments on different subsets of the original data set. The results of all the experiments are exceptionally encouraging.



Enhancing Accuracy and Security of Multi-biometric Template using RDWT Watermarking
M. Vatsa, R. Singh, and A. Noore, " Enhancing Accuracy and Security of Multi-biometric Template using RDWT Watermarking ", Proc. Summer School on Biometric Authentication: Multimodality and System Integration, Italy, June 2005. Received Best Paper Award.



Recognition of Faces with Variations in Disguise
R. Singh, M. Vatsa, and A. Noore, " Recognition of Faces with Variations in Disguise ", Proc. Summer School on Biometric Authentication: Multimodality and System Integration, Italy, June 2005. Received Best Paper Award.



Feature Level Fusion and Face Indexing
Y. Shah and N. Schmid, " Feature Level Fusion and Face Indexing, " poster presentation at the spring meeting of CITeR, May 3 - 4, 2005.



Performance Evaluation of Iris Based Recognition System Implementing PCA and ICA Techniques
V. Dorairaj and N. A. Schmid, " Performance Evaluation of Iris Based Recognition System Implementing PCA and ICA Techniques, " poster presentation at the spring meeting of CITeR, May 3 - 4, 2005.



Feature Level Fusion and Face Indexing
Y. Shah and N. Schmid, " Feature Level Fusion and Face Indexing, " poster presentation at the spring meeting of CITeR, May 3 - 4, 2005.



Non-Ideal Iris Recognition: Robust Segmentation and Algorithms (New Proposal)
N.A. Schmid, S. Schuckers, G. Fahmy, X. Li, and L. Hornak, " Non-Ideal Iris Recognition: Robust Segmentation and Algorithms, " CITeR meeting, Morgantown, WV, May 3 - 4, 2005 (New Proposal).



Generation of Synthetic Irises (Project Progress Report)
N. A. Schmid, A. Ross, and B. Cukic, " Generation of Synthetic Irises, " CITeR meeting, Morgantown, WV, May 3 - 4, 2005 (Project Progress Report).



Acquisition and Understanding of Non-Ideal Iris Imagery (Final Report)
N.A. Schmid, S. Schuckers, G. Fahmy, X. Li, and L. Hornak, " Acquisition and Understanding of Non-Ideal Iris Imagery, " CITeR meeting, Morgantown, WV, May 3 - 4, 2005 (Final Report).



Iris Image Quality Assessment
N. A. Schmid, " Iris Image Quality Assessment, " meeting at Biometric Fusion Center, Clarksburg, May 3, 2005.



Performance Analysis of Iris Based Identification System at the Matching Score Level
N. A. Schmid, " Performance Analysis of Iris Based Identification System at the Matching Score Level, " ICASSP'05, March 21, 2005.



Performance Analysis of Iris-Based Identification System at the Matching Score Level
N. A. Schmid, M. Ketkar, H. Singh, and B. Cukic, " Performance Analysis of Iris-Based Identification System at the Matching Score Level, " in Proc. of ICASSP 2005, Pennsylvania Convention Center, Philadelphia, PA, March 18-23, pp. II-93-II-96.



Performance Evaluation of Iris Based Recognition System Implementing PCA and ICA Techniques
V. Dorairaj and N. Schmid, and G. Fahmy, " Performance Evaluation of Iris Based Recognition System Implementing PCA and ICA Techniques, " in Proc. of the SPIE 2005 Symp. on Defense and Security, Conf. 5779:Biometric Technology for Human Identification II, March 28-29, Orlando, FL



Feature Level Fusion Using Hand and Face Biometrics
A. Ross and R. Govindarajan, "Feature Level Fusion Using Hand and Face Biometrics", Proc. of SPIE Conference on Biometric Technology for Human Identification II, (Orlando, USA), pp. 196-204, March 2005.



Towards Reconstructing Fingerprints from Minutiae Points
A. Ross, J. Shah, and A. K. Jain, "Towards Reconstructing Fingerprints from Minutiae Points", Proc. of SPIE Conference on Biometric Technology for Human Identification II, (Orlando, USA), pp. 68-80, March 2005.



Forensic Analysis of Digital Evidence from Palm PDAs
Christopher M. McNemar and Roy S. Nutter, Jr., "Forensic Analysis of Digital Evidence from Palm PDAs," IFIP Workshop, Orlando, FL, March 2005.



Modeling, Processing, and Analyzing Iris Data
N. A. Schmid, " Modeling, Processing, and Analyzing Iris Data, " Workshop on Iris Recognition, MITRE, McLean, VA, Jan. 27, 2005.



Fingerprint Deformation Models Using Minutiae Locations and Orientations
Y. Chen, S. Dass, A. Ross and A. K. Jain, "Fingerprint Deformation Models Using Minutiae Locations and Orientations", Proc. of IEEE Workshop on Applications of Computer Vision (WACV), (Colorado, USA), pp. 150-155, January 2005.



WVU Computer Forensics Program
R. S. Nutter, "WVU Computer Forensics Program", NIST TWGED-DE Core Group, Washington, DC, January 2005.



Digital Watermarking based Secure Multimodal Biometric System
M. Vatsa, R. Singh, P. Mitra and A. Noore, "Digital Watermarking based Secure Multimodal Biometric System", IEEE International Conference on Systems, Man and Cybernetics, October 10-13, 2004, The Hague, Netherlands.



Short-term load forecasting using optimized neural network with genetic algorithm
L. Tian and A. Noore, " Short-term load forecasting using optimized neural network with genetic algorithm, " 8th International Conference on Probabilistic Methods Applied to Power Systems, Ames, IA, Sept. 2004.



Computer Forensics
R. S. Nutter, "Computer Forensics," all day educational presentation for the Information Assurance Capacity Building Workshop. CMU, July 22, 2004.



Computer Forensics Education Working Group
R. S. Nutter, Computer Forensics Education Working Group, Washington, DC, August 8-10, 2004.



Digital Forensics Research Workshop
R. S. Nutter, Digital Forensics Research Workshop, Washington, DC, August 10-12, 2004.



TWGED-DE (Technical Working Group Education- Digital Evidence)
R. S. Nutter, TWGED-DE (Technical Working Group Education- Digital Evidence), chaired the “Planning Group.” Washington, DC, Dec 1-3, 2004



Homeland Security Training CERT workshop
R. S. Nutter, Homeland Security Training CERT workshop, Morgantown, WV, June 9-10, 2004.



Computer Forensics Education Working group
R. S. Nutter, Computer Forensics Education Working group, Orlando, March 17-20, 2004.



Comparing Robustness of Watermarking Algorithms on Biometrics Data
M. Vatsa, R. Singh, P. Mitra and A. Noore, " Comparing Robustness of Watermarking Algorithms on Biometrics Data ", Workshop on Biometric Challenges from Theory to Practice, 2004.



Signature Verification using Static and Dynamic Features
M. Vatsa, R. Singh, P. Mitra and A. Noore, " Signature Verification using Static and Dynamic Features ", International Conference on Neural and Information Processing, 2004.



Introduction to Computer Forensics Education in Engineering
Nutter, RS, "Introduction to Computer Forensics Education in Engineering.", ASEE Annual Meeting, Nashville, TN, June 20-24, 2003.