(2002) Graduate Course Development in Biometrics

Graduate Course Development in Biometrics

Dr. Stephen J. Elliott, Dr. Mathias J. Sutton Department of Industrial Technology

School of Technology West Lafayette, IN, 47906

Abstract This paper accounts the development of a graduate course in biometrics at Purdue University. The course has been developed in conjunction with the inauguration of an applied biometrics research laboratory. The laboratory represents a Purdue-industry partnership through sponsored projects, advisory relationships, and financial support, industry partners assure that the laboratory achieves its potential in preparing students to perform effectively in the quickly evolving biometrics environment. The laboratory also serves as an educational resource for industry. Introduction TECH 581S Biometric Technology and Applications, is a class intended for upper-level undergraduates in a number of disciplines, including aviation technology, industrial technology, computer information systems technology, and management, as well as graduate students in technology. The course is limited to 20 students per semester for two primary reasons: first to enable a small number of undergraduate students to interact with graduate students who perform a mentoring role in research. Secondly, the development of small research teams allows several projects to be completed and gives the students a tangible research experience to accompany the lectures that span the various biometric technologies. A number of factors have driven the demand for the course: an expansion of current classes, an increase in the awareness of biometric technologies in multiple applications, and the demand from students, especially post 9/11, to learn more about biometric technologies.

The purpose of the course is to examine biometric technologies from the viewpoint of systems integrator, purchaser, and evaluator. Success of the biometrics system is important; therefore, this course examines the fundamentals of testing and evaluation, writing technical reports, presenting research, understanding the process of establishing biometrics standards, and understanding the individual technologies.

The course is consistent with the mission of the School of Technology and the Department of Industrial Technology to “assess the existing curricula and programs; develop new curricula/programs to make them relevant to the life and careers of students, attractive in terms of content, and connected to the needs of business and industry.”

Proceedings of the 2002 ASEE/SEFI/TUB Colloquium Copyright 2002, American Society for Engineering Education

Prerequisite Courses TECH 581S has no prerequisites, as it is intended to attract students from a number of disciplines into the biometrics arena, as these technologies themselves enter different applied environments. However, a number of undergraduate students that are participating in the first run of the course have had prior experience in biometric technologies in IT 345 Automatic Identification and Data Capture.

Course Description The course is a three-hour, three-credit course that meets once a week for 16 weeks with an independent lab research component. The research activities are a major component of the class. As such research activities make up 50% of the course grade. Upon successful completion of the course, each student will be able to:

a) Classify biometric applications. b) Identify techniques for testing biometric devices. c) Apply “best practice” techniques for biometric project management and

implementation. d) Understand which biometrics technology is best for a given application. e) Understand the ethics of biometric technologies. f) Understand the fundamentals of fingerprinting, iris scanning, speaker verification,

hand geometry, dynamic signature recognition, facial recognition, and multi biometrics – voice, lip and facial recognition.

e) Understand the limitations of biometric technologies.

Semester activities are divided into nine different sessions (see Table 1), which follow the main lecture topics. A few of the sessions span more than one week.

Table 1 Session Schedule for TECH 581S

Session Lecture Topic

1 Course Introduction and Pre-Test 2 Biometrics - An Introduction 3 Biometric Testing and Evaluation 4 Dynamic Signature Verification 5 Hand Geometry 6 Fingerprint 7 Facial, Iris and Retinal Identification 8 Voice Recognition 9 Biometric Applications and Implementation


Research Activities

The purpose of the research activities is to provide students with an applied research experience that they can use in their specific disciplines. Overall, there are 13 different research projects, which include fake finger testing, testing and evaluating fingerprint sensors on mobile computers, impostor knowledge within dynamic signature verification, and replication of a voice telematics experiment. However, most of the research activities are focused in two main areas: digital fingerprint and dynamic signature technology. The digital fingerprint thrust evolved based on discussions in the biometric community listserv on the “gummy finger” debate [1]. This debate provided course developers with a unique opportunity to create a cross-disciplinary project team comprised researchers from the Schools of Management, Computer Science, and Technology to examine the research and to expand the body of knowledge in this topic. Furthermore, attacks (such as fake fingers on biometric sensors) discussed in the literature, enable students to examine research protocols, replicate the tests, and report those findings within a constrained 16-week semester. The research will provide vendors and industry partners with feedback on the performance of their sensors, given the attacks described. Initially, research activities will center on two biometric technologies – fingerprint and dynamic signature verification. There has been little work published on fingerprint sensor attacks. According to Matsumoto, Matsumoto, Yamada, and Hoshino [1], "security evaluation against attacks using such artificial fingers has rarely been disclosed." The second research focus is a continuation of work already started in dynamic signature verification technology. Within the realm of dynamic signature verification, forgery is discussed at length [2-19], but with conflicting definitions of a forgery.

Laboratory Equipment

Equipment donations to the laboratory, software, and hardware upgrades have provided the opportunity to offer a course in biometric technologies. This equipment includes a number of fingerprint sensors that use both pattern and minutiae based algorithms; a desktop iris recognition camera; several dynamic signature verification digitizers, and a hand geometry reader. Session Outline

As noted earlier, the course is divided into nine distinct sessions, designed to group a number of lectures together within a particular topic.

Session One – Course Introduction The first session introduces and outlines the course. A 100-item pre-test assesses students’ current knowledge across biometric technologies and their perceptions of the technology. At the completion of each session, a post-test will evaluate their knowledge on each specific technology and provide both student and instructor with useful information on the success of the instruction, as well as gaps in student knowledge. The first session also includes an on-line evaluation


component, where each student completes the National Institute of Health human subject tutorial. Each student will participate as subjects in fellow students’ research and as such must understand the requirements of the Purdue University Human Subjects Review Board. Session Two – Introduction to Biometrics The second session outlines biometric technologies and introduces students to biometric technologies. Students will learn common research methodologies, the classification of biometric technologies [20] and the fundamentals of biometric technology [21]. Also included in this session is a discussion of testing protocols for dynamic signature verification [22]. Session Three – Biometric Testing and Evaluation Session 3 discusses biometrics from a historical perspective [23]. This session also includes readings and discussion on testing and evaluation, based on the UK Best Practice Testing Document and biometric applications and taxonomy [24-25]. A discussion on the testing methodologies relating to each group’s project will be started. Students will arrive with a draft of their testing protocol. This session will have approximately two hours of lecture and one hour of testing protocol evaluation. After session 3, all the groups should have finalized their testing protocol for the research experiments. As the UK Biometric Best Practice document is central to the research protocol development, students will be expected to have a comprehensive understanding of the manuscript; which will be evaluated using an online test. To help students understand the UK Biometric Best Practice Document, they will critique the testing methodology related to a case study [3]. In preparation for the next session, the students will read the National Biometric Test Center Collected Works, specifically those sections related to testing and evaluation [21, 26-28]. As with all testing, discussion on imposters (important to understand in the context of the research being conducted in the class) centers on allowing good imposters to test [29]. Session Four – Dynamic Signature Verification The fourth session continues to discuss the role of the readings related to biometrics testing and evaluation [30].

The course shifts in this session to focus on specific technologies and their role in industry. The first experiment involves dynamic signature verification as it relates to the feedback from the digitizer. The following research question is posed: is there a statistical difference in the individual variables across visible and non-visible feedback devices? Several devices will be studied, including those that have ink visible, against those devices that do not have ink visible (but both use a stylus), compared with a digitizer that uses pen and paper. A comparison of the underlying dynamic traits of the signature across all of these digitizers will be studied. Another dynamic signature verification study will examine the differences between gender and handedness across devices.


Session Five – Hand Geometry

The lecture component of session five describes hand geometry and common applications such as immigration and access control systems. The research component of this session continues with a discussion on dynamic signature verification. The research focus in this session is to understand how the variables of the dynamic signature change when an impostor knows progressively more information about the genuine signature. A genuine signature is defined as a good faith attempt by a user to match his/her own stored template. An “imposter” transaction is a “zero-effort” attempt by a person unknown to the system to match a stored template. An imposter attempt is classed as “zero-effort” if the individual submits his/her own biometric feature as if attempting successful verification against his/her own template. The best practice document [30] acknowledges that with dynamic signature verification, an imposter would sign his/her own signature in a zero-effort attempt. Dynamic signature verification testing also poses additional problems, notwithstanding “zero-effort” attempts. Some dynamic signature verification studies use several methods to determine imposter distributions by forging a signature. Different levels of forgery exist, done by different individuals, with varying knowledge about the signature and under differing conditions, incentives, etc. Mettyear suggests that there are levels of information that the signer might have in order to make an attempt at a forgery. Session Six - Fingerprint Both the research and lecture components of this session deal with fingerprints and the concept of fingerprint identification. Several articles will be used to explain the concept of fingerprint identification. Aspects to be included in this session include fingerprint standards and methodologies and latent imaging [31-39]. The research focus of this session is to enroll users using the fingerprint devices selected for the studies on fake or artificial fingers. The second part of the fingerprint technology session will be to complete the research on fingerprinting and spoofing. Each semester the research objectives will change, depending on previous research, available grants, and resources. For the first run of the class, the fingerprint studies will examine spoofing the biometric device. There are several attacks that can be presented to a device [1]. These are using the registered finger under duress, using an impostor's finger (commonly called a zero-effort forgery), using a severed finger (liveness), a genetic clone of the finger, and using an artificial clone of the registered finger. The study will concentrate on the artificial clone of the registered finger. Several methodologies will be used to create an artificial clone of the registered finger, as established in prior research, as well as various accounts in the trade press[1,18-19]. Session Seven – Facial, Iris and Retinal Identification This session will describe the uses of facial recognition. Readings include discussions on facial recognition as they relate to applications [40--46]. There will also be a discussion on the facial recognition and testing [47], and the Facial Recognition Technology Test (FERET). Iris and retinal identification are also discussed in this session. As many enrolled students are in aviation technology, several of the application readings are from online discussions posted as a result of


September 11th, 2001 terrorist attacks [48-55]. Research components in this session relate to the continued evaluation of the fingerprint sensors as discussed earlier. Session Eight – Voice Recognition Although the majority of the course has centered on the identification of an individual, this session builds on a previous Masters degree directed project describing a telematics user interface [56]. A practical laboratory activity will be set up utilizing a limited command set for a touch sensitive entertainment system. The difference in time between voice and non-voice are measured. Session Nine - Biometric Applications and Implementations

The final session outlines biometric technologies and some of the pitfalls and criticisms of biometrics with regard to the media. A debate will be initiated in response to criticisms of how the technologies are used, within the context of [75-81]. In this session, other readings will be discussed including biometrics and privacy [82-88]. Finally, a discussion on what biometric is suitable for a specific application will be revisited [89]. At the conclusion of this session, students will receive a post-test evaluating their performance over the semester. Conclusion This paper was written to provide information to the reader on the development of a biometrics course for upper-level undergraduate and graduate students. The paper outlined information on the readings that are used in the class as well as the research activities that are proposed for the students. Further papers will be written to provide educators with lessons learned in the developments of the course and its research.

Bibliography [1] T. Matsumoto, H. Matsumoto, K. Yamada, S. Hoshino, "Impact of Artificial Gummy Fingers on

Fingerprint Systems," Proceedings of SPIE Vol. #4677, Optical Security and Counterfeit Deterrence Techniques IV, 2002.

[2] H. Dullink, van Daalen, B., Nijhuis, J., Spaanenburg, L., & Zuidhof, H., "Implementing a DSP Kernel for

Online Dynamic Handwritten Signature Verification Using the TMS320DSP Family," EFRIE, France SPRA304, 1996.

[3] S. J. Elliott, "A Comparison of On-Line Dynamic Signature Trait Variables vis-à-vis Mobile Computing

Devices and Table-Based Digitizers," presented at Automatic Identification Advanced Technologies (Auto ID 2002), New York, 2002.

[4] F. D. Greiss, "On-Line Signature Verification." Michigan State University, East Lansing, MI May, 2000. [5] D. J. Hamilton, Whelan, J., McLaren, A., & MacIntyre, I., "Low Cost Dynamic Signature Verification

System.," presented at European Convention on Security and Detention, London, United Kingdom, 1995.


[6] J. P. Holmes, "A Performance Evaluation of Biometric Identification Devices," Sandia National Laboratory SANDIA91-0276, 1991.

[7] Y. Komiya, Matsumoto, T., "On-line Pen Input Signature Verification PPI (Pen-Position / Pen-Pressure /

Pen-Inclination)," IEEE, 1999. [8] F. Leclerc, Plamondon, R., "Automatic Signature Verification: The State of the Art - 1989-1993," in

Progress in Automatic Signature Verification. Singapore: World Scientific Publishing Company, 1994, pp. 3-21.

[9] L. Lee, Berger, T., "Reliable Online Human Signature Verification System for Point-of-Sales

Applications," Proceedings of the 12th IAPR International Conference on Computer Vision and Image Processing, Conference B, vol. 2, pp. 19-32, 1994.

[10] X. Li, Parizeau, M., Plamondon, R, "Segmentation and Reconstruction of On-Line Handwritten Script.,"

IEEE Pattern Recognition, pp. 675-684, 1998. [11] R. Martens, Claesen, L, "On-Line Signature Verification: Discrimination Emphasized," IEEE, 1997. [12] M. Mingming, Wijesoma, W, "Automatic On-Line Signature Verification Based on Multiple Models,"

presented at CIFEr'01: Computational Intelligence in Financial Engineering Conference, 2000. [13] N. Mohankrishnan, Lee, W.S., Paulik, M., "Improved Segmentation through Dynamic Time Warping For

Signature Verification using a Neural Network Classifier," presented at Signal Processing Society International Conference on Image Processing, 1998.

[14] R. Plamondon, "The Design of an On-Line Signature Verification System: From Theory to Practice," in

Progress in Automatic Signature Verification. New York: World Scientific Publishing Company, 1994. [15] C. Schmidt, & Kraiss, K. F, "Establishment of Personalized Templates for Automatic Signature

Verification," IEEE, pp. 263-267, 1997. [16] Q. Z. Wu, Jou, I. C., & Lee, S. Y, "On-Line Signature Verification using LPC Cepstrum and Neural

Networks," IEEE Transactions on Systems, Man, and Cybernetics, pp. 148-153, 1997. [17] Y. Yamazaki, Mizutani, Y., & Komatsu, N., "Extraction of Personal Features from Stroke Shape, Writing

Pressure and Pen Inclination in Ordinary Characters.," presented at Fifth International Conference on Document Analysis and Recognition, 1998.

[18] Tekey, "Trick an Optical Sensor," vol. 2002: Tekey Group, 2002. [19] T. van der Putte, Keuning, J, "Biometric Fingerprint Recognition: Don’t Get Your Fingers Burned,"

presented at IFIP TC8/WG8.8 Fourth Working Conference on Smart Card Research and Advanced Applications, 2000.

[20] P. Philips, Martin, A., Wilson, C., Przybocki, M., "An Introduction to Evaluating Biometric Systems," in

IEEE Computer, 2000, pp. 56-63. [21] J. L. Wayman, "Fundamentals of Biometric Authentication Technologies," in National Biometric Test

Center Collected Works, vol. 1, J. L. Wayman, Ed. San Jose, CA: National Biometric Test Center, 1999. [22] S. J. Elliott, "Development of a Biometric Testing Protocol for Dynamic Signature Verification," presented

at ICARCV, 2002, Singapore, 2002. [23] J. Ashborne, Biometrics: Advanced Identity Verification. New York: Springer-Verlag, 2000.


[24] N. Mansfield, Wayman, J. L., "U.K. Biometric Working Group Best Practice Document," National Physical Laboratory, Teddington, England February 12 2002.

[25] S. J. Elliott, "Addendum to the U. K. Biometric Best Practice Document," Purdue University, West

Lafayette, IN August 10 2001. [26] J. L. Wayman, "The Functions of Biometric Identification Devices," vol. 2000. San Jose, CA: National

Biometric Test Center, 2000. [27] J. L. Wayman, "Technical Testing and Evaluation of Biometric Identification Devices," in National

Biometric Test Center Collected Works, vol. 1, J. L. Wayman, Ed. San Jose, CA: National Biometric Test Center, 2000, pp. 65-87.

[28] J. L. Wayman, "Confidence Interval and Test Size Estimation for Biometric Data," presented at Automatic

Identification Advanced Technologies (Auto ID 1999), Summit, NJ, 1999. [29] J. M. Colombi, Reider, J. S., Cambell, J. P., "Allowing Good Imposters to Test," Conference Record of the

Thirty-First Asilomar Conference on Signals, Systems and Computers, vol. 1, pp. 296-300, 1997. [30] N. Mansfield, "A Review of Test Protocol for Scenario Evaluation of SMARTpen." Teddington, United

Kingdom, 2000. [31] A. Jain, Bolle, R., & Pankanti, S., Biometrics: Personal Identification in Networked Society. Norwell, MA:

Klewer Academic Publishers Group, 2001. [32] The Science of Fingerprints. Classifications and Uses, Rev 12-84 Ed: United States Department of Justice,

Federal Bureau of Investigation, 1984. [33] A. Jain, Hong, L., & Bolle, R., "On-line Fingerprint Verification," IEEE Transactions on Pattern Analysis

and Machine Intelligence, vol. 19, pp. 302-314, 1997. [34] A. K. Jain, Prabhakaran, S., Hong, L., Pankanti, S., "Filterbank-based Fingerprint Matching," IEEE

Transactions on Image Processing, vol. 9, pp. 846-859, 2000. [35] J. K. Schneider, Gojevic. S. M.,, "Ultrasonic Imaging Systems for Personal Identification," IEEE 2001

Ultrasonics Symposium, vol. 1, pp. 595-601, 2001. [36] M. Jiangto, Shaojun, W, "Automatic Fingerprint Identification System for Small Sized Database," Proc.

4th International Conference on ASIC, 2001, pp. 386-389, 2001. [37] D. Maio, Maltoni, D., Cappelli, R., Wayman, J. L., Jain, A. K, "FCV2000: Fingerprint Verification

Competition," IEEE Transactions on Pattern Analysis and Machine Intelligence, vol. 24, pp. 402-412, 2002.

[38] A. K. Jain, Ross, A., Prabhakaran, S, "Fingerprint Matching Using Minutiae and Texture Features,"

presented at Proc International Conference on Image Processing (ICIP), Greece, 2001. [39] U. Halici, Jain, L. C., Erol, A., "Introduction to Fingerprinting," in Intelligent Biometric Techniques in

Fingerprint and Face Recognition, L. C. Jain, Halici, U. Hayashi, I., Lee, S. B., Tsutsui, S., Ed. Boca Raton, FL: CRC Press, 1999, pp. 1-35.

[40] ACLU, "ACLU Opposes Use of Face Recognition Software in Airports Due To Ineffectiveness and

Privacy Concerns," vol. 2002: ACLU. [41] P. E. Agre, "Your Face is not a Bar Code: Arguments against Automatic Face Recognition in Public

Places," University of California, Los Angeles, Los Angeles, CA January 28 2002.


[42] G. Barber, "Living on the Wrong Side of a One-Way Mirror: Face Recognition Technology and Video

Surveillance," vol. 2002, 2001. [43] D. McGuire, "ACLU Warns of Face Recognition Pitfalls," vol. 2002: Newsbytes, 2001. [44] S. L. Olsen, R., "Can Face Recognition Keep Airports Safe," vol. 2002: ZDNet News, 2001. [45] Visionics, "Visionics FaceIt ARGUS Pilots Go Live At Dallas Fort-Worth and Palm Beach International

Airports," vol. 2002: Visionics Inc, 2002. [46] R. Windman, "Your Face is Good Enough," vol. 2002: eWeek, 2001. [47] W. A. Barrett, "A Survey of Face Recognition Algorithms and Testing Results," Conference Record of the

Thirty-First Asilomar Conference on Signals, Systems & Computers, vol. 1, pp. 301-305, 1997. [48] Eye Ticket, "Eye Pass," vol. 2001, 2001. [49] D. Sieberg, "Iris recognition at airports uses eye-catching technology," vol. 2001, 2000. [50] R. P. Wildes, "Iris Recognition Technology," Proceedings of IEEE, vol. 85, pp. 1348-1363, 1997. [51] R. P. Wildes, Asmuth, J. C., Green, G. L., Hsu, S. C., Kolczynski, R. J., Matey, J. R., McBride., S. E., "A

System for Automated Iris Recognition," Proceedings of the Second IEEE Workshop on Applications of Computer Vision, pp. 121-128, 1994.

[52] S. Weicheng, Kjanna, R, "Prolog to Iris Recognition: An Emerging Biometric Technology," Proceedings of

IEEE, vol. 85, pp. 1347-1347, 1997. [53] G. O. Williams, "Iris Recognition Technology," IEEE Aerospace and Electronics Systems Magazine, vol.

12, pp. 23-29, 1997. [54] R. Sanchez-Reillo, Sanchez-Avila, C., and Martin-Pereda, J. A., "Minimal Template Size for Iris-

Recognition," Proceedings of the First Joint BMES/EMBS Conference, vol. 2, pp. 972, 1999. [55] J. Daugman, "High confidence visual recognition of persons by a test of statistical independence," IEEE

Transactions on Pattern Analysis and Machine Intelligence, vol. 15, pp. 1148-1161, 1993. [56] R. Louks., “A Design and Testing Methodology for an Automotive Telematic User Interface,” Purdue

University, West Lafayette, IN [57] 666soon.com, "Benefits and Limitations of Biometrics," vol. 2002: 666soon.com, 2002. [58] M. Andress, "Biometrics at Work? Scanning the human body is starting to see limited enterprise use, but

don't expect to give up a fingertip soon," vol. 2002: InfoWorld, 2001. [59] D. Birch, "A World Away From Reality: Biometrics is the Wrong Way to Track Terrorists," vol. 2002:

Guardian, 2002. [60] T. Bracco, "Biometrics suites earn thumbs up," vol. 2002: Network World, 2000. [61] J. Evers, "Dutch Government uses Biometrics to ID immigrants," vol. 2002: CNN, 2001. [62] B. Forseca, "High-tech Biometrics May Offer The Solution To Authentication and Security Demands," vol.

2002: InfoWorld, 2001.



[63] H. Harreld, "Biometrics points to greater security," vol. 2002: Federal Computer Week, 1999. [64] "Consumer Biometric Applications: A discussion paper," Information and Privacy Commissioner / Ontario,

Toronto, Canada September 1999. [65] R. Clarke, "Interview on Privacy and Biometrics with Roger Clarke," vol. 2002: Biomet.org, 2000. [66] M. Cobb, "Privacy vs. Security," vol. 2002: E-Business Advisor Magazine, 2002. [67] B. Foran, "Privacy in the Electronic World Panel: Access and Privacy "Meeting the Challenges of Change:"

Smartcards and Biometrics: The Privacy Implications," Privacy Commissioner of Canada, Toronto, Canada September 26 1996.

[68] R. Norton, "IBIA Privacy Principles," vol. 2000: International Biometric Industry Association, 2000. [69] N. K. Ratha, Connell, J. H & Bolle, R. M, "Enhancing security and privacy in biometric based

authentication systems," IBM Systems Journal, vol. 40, pp. 1-17, 2001. [70] G. Tomko, "Biometrics as a Privacy-Enhancing Technology: Friend of Foe or Privacy?," presented at

Privacy Laws and Business 9th Privacy Commissioners' / Data Protection Authorities Workshop, Santiago de Compostela, Spain, 1998.

[71] J. L. Wayman, Alyea, L., "Picking the Best Biometric for Your Application," in National Biometric Test

Center Collected Works, vol. 1, J. L. Wayman, Ed. San Jose, CA: National Biometric Test Center, 2000, pp. 269 - 275.