NSF Workshop on Fundamental Research Challenges for Trustworthy Biometrics: Panel Summary Slides

1. NSF Workshop on Fundamental Research Challenges for Trustworthy Biometrics:Panel Summary Slides Co-Chairs: Stephanie Schuckers, Clarkson University Lenore Zuck, National Science Foundation, Christopher Miles, Department of Homeland Security This workshop is supported by the National Science Foundation under Grant No. 1048975 . Any opinions, findings, and conclusions or recommendations expressed in this material are those of the author(s) and do not necessarily reflect the views of the National Science Foundation.

2. Special Thanks to: Organizing Committee: Karl Levitt, UC-Davis, Lawrence Hornak, WVU/NSF, Fabian Monrose, University of North Carolina-Chapel Hill, BojanCukic, West Virginia University, Susanne Wetzel, Stevens Institute of TechnologyAdvisory Committee: Michael Yura, BIMA/DoD, Jeff Dunn, NSA, Kelly Faddis, Scott Swann, FBI, Patrick Grother, NIST, John Savage, Department of State, Carl Landwehr, NSF, Michael Benardo, FDIC

3. Workshop Charge To establish the fundamental research challenges for trustworthy biometric systems in identity management

4. Motivation • Transactions (security, health, financial, social, etc) rely on establishment of trust • Need for linkage between biological identity and our digital persona in order to establish trust • Biometrics (measured identity) is one means to establish that linkage • Need to establish levels of trust • Privacy preserving components • Provides for anonymity • Scales in the information content (uniqueness) • Scientific basis (aging, medical, etc.) • Usability, performance, reliability, etc.

5. Need for Fundamental Research • Government funding • focused on biometric capture (sensors and systems) • application oriented (e.g. border security, wartime detainment) • concentrate on advanced signal and image processing techniques to add robustness • Recent reports highlight need: • “National Strategy for Trusted Identities in Cyberspace” • National Academies Report on “Biometric Recognition: Challenges and Opportunities”

6. Research Needs • Algorithms/approaches/models that address privacy, acceptability, usability, and security of stored and transmitted biometric information • Need to establish scientific fundamentals of identity science, as well as research at the intersection of identity management and cyberspace

7. Keynote Lectures and Discussion • Summary of the NRC Report “Biometric Recognition: Challenges and Opportunities” • Lynette I. Millett, Senior Program Officer and Study Director, Computer Science and Telecommunications Board, National Research Council of the National Academies • Biometric Recognition’s Role in Identity Management • Dr. Elisa Bertino, Professor, Purdue University • Advances in Molecular Processing and Analysis—Future Directions in Identity Science • Dr. James Landers, Professor, University of Virginia • Dr. Joan Bienvenue, Chief Scientist, Lockheed Martin Corporation

8. Panel Talks and Discussion • Foundations in Biometrics—Privacy, Security and Identity • Panel Leads: Susanne Wetzel, Fabian Monrose • Panelists: Colin Soutar, NaliniRatha, Adam Smith, Elaine Newton • Fundamentals of Identity Science • Panel Leads: Chris Miles, Stephanie Schuckers • Panelists:Peter Vallone, Arun Ross • Future Directions in Identity Science • Panel Leads: Jeff Salyards, Jeff Palmer • Panelists: Jeff Salyards, Jeff Palmer, Brigitte Rolfe

9. Foundations in Biometrics—Privacy, Security and IdentityPanel Summary Slides Panel Leads: Dr. Fabian Monrose, UNC Dr. Susanne Wetzel, Stevens Institute of Technology Panelists: Dr. Colin Soutar, CSC Dr. NaliniRatha, IBM TJ Watson Research Center Dr. Adam Smith, Pennsylvania State University Dr. Elaine Newton, NIST

10. Privacy, Security and IdentityPanel Summary Slides Develop and assess systems which preserve secrecy/privacy of biometrics e.g., biometric cryptosystems, biometrics as keys, template protection, revokable biometrics, etc. Taxonomyof systems Evaluation of strengths/vulnerabilities of stored biometric templates Modeling data and attacks Metricsto evaluate systems Development of advanced methods Theoretical models of classes of similarity/distance measures beyond vector norms (e.g., for minutiae, face images, ...) Error-correctiontechniques for complex similarity/distance measures Apply homomorphic encryption to biometrics Anonymous search capabilities “No effort” re-enrollment

11. Develop and assess systems which preserve secrecy/privacy of biometrics (continued) Hardware: extending the biometric matching capability in trusted environment such as secure hardware co-processors, smart cards Quantify the use of biometrics on diverse platforms, such as cell phones and laptops Quantify use of biometrics within multi-factor assurance context Quantifiable and commensurable biometric strength of authentication when combined with other factors Develop methodologies for end-to-end security evaluations Define evaluation methods for anti-spoofing/liveness testing for each major modality Privacy, Security and IdentityPanel Summary Slides

12. Strengthen collaboration between different disciplines (cryptography, signal processing, security) Harmonize language and terminology Need for common large data sets, well-defined challenge problems Encourage cross-disciplinary events/funding opportunities Design systems subject to privacy constraints, public perceptions, and legal regulations – incorporate legitimate concerns How to responsibly collect/store/share operational or research data Design to limit function creep, clarify functional requirements Education on biometrics benefit society, privacy laws, etc. Privacy, Security and IdentityPanel Summary Slides

13. Fundamentals in Identity SciencePanel Summary Slides Panel Leads: Chris Miles, Department of Homeland Security Dr. Stephanie Schuckers, Clarkson University Panelists: Dr. Peter Vallone, National Institute of Standards and Technology Dr. Arun Ross, West Virginia University

14. Fundamentals in Identity SciencePanel Summary Slides • Develop models for individuality (uniqueness) • Biological models • To understand the biological basis of a trait; level of detail observed (e.g., Level I, II or III for fingerprint) • Feature and score models • To utilize feature and score distributions to deduce capacity of a template, or information entropy • Error Rate models • To model error rates based on empirical evaluation of algorithms; understand the notion of uncertainty • Establish basis to assess impact of age on biometrics • Methods to estimate biological age of an individual from biometric • Models to understand how biometric traits age with time; impact of disease on biometric traits • Face, Iris, Fingerprint • Automatic template aging and update schemes

15. Fundamentals in Identity SciencePanel Summary Slides • Understand impact of fusionon scalability and security • Methods to increase the capacity of a template • Estimating scalability of individual biometric traits • Methods to incorporate adversary attacks in a biometric fusion framework

16. Future Directions in Identity SciencePanel Summary Slides Panel Leads: Dr. Jeff Salyards, US Army Criminal Investigation Laboratory Dr. Jeff Palmer, MIT-Lincoln Laboratory Panelists: Dr. Jeff Salyards, US Army Criminal Investigation Laboratory Dr. Jeff Palmer, MIT-Lincoln Laboratory Brigitte Rolfe, MITRE

17. Future Directions in Identity SciencePanel Summary Slides • Extend methods for validation of forensic science • Measures of uncertainty, accuracy, reliability, treat as “pattern recognition”, relationship with biometric performance metrics • Peer reviewed research on human observer bias • Expand definition usage of biometrics beyond “recognition” • Intent? Medical? Group? Levels of identity? • Establish science for assessment of new/novel biometrics • e.g. odor, cardiovascular, vein, etc., • Extend application spaces • Stand-off, unconstrained, non-cooperative, covert, etc.

18. Fundamentals and Future Directions in Identity SciencePanel Summary Slides From Both Panels • Advance rapid DNA as a biometric • e.g. automated rapid DNA systems based on digital microfluidics, bio-material science • System improvements • Reduce costand time, automate, increase portability • Improve samplemethods of DNA, best recovery, non-invasive • New markers • Automated analysis and searching algorithms, secure and private communications, database management • Scientific understanding • Effect of aging • Countermeasures • Broader considerations • Identify applications (kinship, identity, other) • Keep DNA ‘in the loop’ with established biometrics, lessons can be learned from both areas • DNA training, tactics, procedures