DocumentCode :
2589609
Title :
A Reproducible Performance Evaluation Method for Forged Fingerprint Detection Algorithm
Author :
Shin, Yong-Nyuo ; Chun, Myung Geun ; Shin, Woochang
Author_Institution :
Bank of Korea, Seoul, South Korea
fYear :
2010
fDate :
21-23 April 2010
Firstpage :
1
Lastpage :
8
Abstract :
As biometric technologies such as fingerprint recognition technology become more widespread, the danger posed by security attacks using forged fingerprints is increasing. To counter this threat, diverse technologies are being developed to detect fingerprint forgery. However, thus far there has no method of evaluating the performance of forged fingerprint detection algorithms that has been confirmed to be reliable by achieving reproducible performance test results. This paper proposes a method for objective performance evaluation of forged fingerprint technology. Unlike previous methods of evaluating the performance of forged fingerprint detection algorithms, the proposed performance evaluation method can reproduce evaluation results, and can be used for technology evaluation. To eliminate the ambiguity of the method and express it in a formal manner, the Evaluation Model of Forged Fingerprint Detection (EMFFD) has been developed. In addition, various metrics have been defined to measure the performance evaluation of forged fingerprints.
Keywords :
fingerprint identification; formal verification; performance evaluation; biometric technologies; evaluation model of forged fingerprint detection; formal method; reproducible performance evaluation; security attacks; Biometrics; Computer security; Counting circuits; Data structures; Detection algorithms; Face recognition; Fingerprint recognition; Forgery; Manufacturing; National security;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Information Science and Applications (ICISA), 2010 International Conference on
Conference_Location :
Seoul
Print_ISBN :
978-1-4244-5941-4
Electronic_ISBN :
978-1-4244-5943-8
Type :
conf
DOI :
10.1109/ICISA.2010.5480344
Filename :
5480344
Link To Document :
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