Biohashing is a promising cancellable biometrics method. However, it suffers from a problem known as ‘stolen token scenario’. The performance of the biometric system drops significantly if the Biohashing private token is stolen. To solve this problem, this paper proposes a new method termed as Most Intensive Histogram Block Location (MIBL) to extract additional information of the p-th best gradient magnitude. Experimental analysis shows that the proposed method is able to solve the stolen token problem with error equal rates as low as 1.46% and 7.27% when the stolen token scenario occurred for both FVC2002 DB1 and DB2 respectively.
|Title of host publication||Neural Information Processing - 21st International Conference, ICONIP 2014, Proceedings|
|Editors||Chu Kiong Loo, Keem Siah Yap, Kok Wai Wong, Andrew Teoh, Kaizhu Huang|
|Number of pages||9|
|Publication status||Published - 2014|
|Name||Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)|
Bibliographical notePublisher Copyright:
© Springer International Publishing Switzerland 2014.
All Science Journal Classification (ASJC) codes
- Theoretical Computer Science
- Computer Science(all)