Citation

Munalih, Ahmad Syarif and Ong, Thian Song and Tee, Connie (2014) Improved biohashing method based on most intensive histogram block location. In: Neural Information Processing. Lecture Notes in Computer Science . Springer International Publishing, pp. 644-652. ISBN 978-3-319-12643-2

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Abstract

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.

Item Type:	Book Section
Additional Information:	Book Subtitle: 21st International Conference, ICONIP 2014, Kuching, Malaysia, November 3-6, 2014. Proceedings, Part III
Subjects:	Q Science > QA Mathematics > QA71-90 Instruments and machines > QA75.5-76.95 Electronic computers. Computer science
Divisions:	Faculty of Information Science and Technology (FIST)
Depositing User:	Ms Nurul Iqtiani Ahmad
Date Deposited:	23 Jan 2015 06:23
Last Modified:	23 Jan 2015 06:23
URII:	http://shdl.mmu.edu.my/id/eprint/5944

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