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Biometric
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What is the AUC of the system? 10. What is the d-prime value for this system? 11. Summarize the rank-t identification rate for different values of t using the Cumulative Match Characteristic (CMC) curve.
The table contains raw match scores for 10 subjects with 3 samples for each subject. You may assume the system is symmetric. You may use the tool of your choice (R, Python, Excel, Matlab, etc) in the analysis of the data. But please indicate which tool is being used. 1. What does it mean when we refer to a biometric as symmetric? 2. What is the meaning of Determine the total number of scores that have been generated? 3. How many imposter scores can be generated? How many genuine? 4. Plot the genuine and imposter match score distributions. 5. Generate a set of 10 thresholds, determine the FAR and FRR at each threshold value. Plot the ROC Curve for your data (FAR vs. FRR and GAR vs. FRR). 6. Plot error rates relative to the threshold score and indicate the point where the EER occurs. What is the EER of the system? 7. What threshold value would you select for a high-security application? What are the implications of your selection? Provide a justification for your response. 8. What threshold value would you select for a forensic application? What are the implications of your selection? Provide a justification for your response. 9. What is the AUC of the system? 10. What is the d-prime value for this system? 11. Summarize the rank-t identification rate for different values of t using the Cumulative Match Characteristic (CMC) curve.
