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Understanding System Errors in Biometric Authentication: ROC and Error Trade-offs

This chapter explores system errors in biometric authentication, focusing on Receiver Operating Characteristics (ROC) and specific error conditions. It discusses matching scores, types of errors (false matches and false non-matches), and their implications for security and convenience. The chapter emphasizes the trade-offs between false acceptance rates (FAR) and false rejection rates (FRR), and how they affect the overall effectiveness of biometric systems. Additionally, the importance of understanding error rates in the context of user authentication is addressed, alongside potential solutions for minimizing risks.

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Understanding System Errors in Biometric Authentication: ROC and Error Trade-offs

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Presentation Transcript

  1. Chapter 5 Basic System Errors (Alireza Tavakkoli)

  2. Outline • Matching • The Receiver Operating Curves (ROC) • Error Conditions Specific to Biometrics • Negative Authentication • Trade-offs

  3. Matching • Definition • Notations: Biometric Uniqueness

  4. Similarity measure  Prob (B=B’) Higher match score  Higher Prob. Similarity  d(B’,B) [0,Inf.)  [0,1] Matching Scores

  5. The Tail of Two Errors • Hypothesis Test and Errors: • Two Errors: • False Match (Type I) • Flase Non-match (Type II)

  6. Score Distributions Hard Decision Reliability of s

  7. FMR and FNMR

  8. Estimating Error from Data • Access to G(y) & F(x) • Estimation: • Need to be studied more

  9. Error Rates of Match Engines • FM and FNM • Accept/Reject Object • FA and FR • Accept/Reject Null Hypothesis

  10. Positive Authentication • Errors in Pos. Authentication: • False Accept (FA) • False Reject (FR) • Problems: • FA  Security Breach • FR  Convenience Problems

  11. ROC - Design vs Application - Security vs Convenience FMR ↑ FNMR ↓

  12. Semi-log plots Log-log plot Variations of ROCs

  13. Using the ROC Curve • Comparing matchers • Tradeoff between FMR & FNMR. • Specific Threshold  FMR(T)/FNMR(T)

  14. Expressing Quality of ROC • The Equal Error Rate: • d-prime: • Expected Overall Error • Cost Function

  15. Expressing Quality of ROC • The Equal Error Rate:

  16. Expressing Quality of ROC • d-prime:

  17. Expressing Quality of ROC • Expected Overall Error

  18. Expressing Quality of ROC • Cost Function

  19. Error Conditions Specific to Biometrics • FTAFTEFTU Significant Cost. • FTA: • FTE: • Manual vs Automatic Authentication • CMC or RPM

  20. Negative Authentication • Negative Hypotheses: • The Two Errors: • Falsely missing B • Incorrectly matching B and B’.

  21. Negative Authentication • Detection Theory Terminology: • False Negative • False Positive

  22. Different Errors  Different Outcomes False Accept  Security Breach. False Reject  Inconvenience. Convenience vs Security Cost vs Security Cost of Negative Authentication Trade Offs

  23. Convenience vs Security • Convenience of a Biometric • Convenience of Implementation

  24. Cost vs Security in Pos. Auth. • Why it is important • FRR ↑ Service denial  Exception handling • Dynamic Authentication Protocol

  25. Cost of Negative Authentication • Screening: • Higher FPR&FNR  Inconvenient to all

  26. Neg. Vs Pos. Authentiocation

  27. Questions?

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