Neural Networks and Rules-based Systems used to Find Rational and Scientific Correlations between being Here and Now with Afterlife Conditions
Neural Networks and Rules-based Systems used to Find Rational and
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Large centralized biometric databases, accessible over networks in real time are especially used for identification purposes. Multimodal biometric systems which are more robust and accurate in human identification require multiple templates storage of the same user analogous to individual biometric sources. This may raises concern about their usage and security when these stored templates are compromised since each person is believed to have a unique biometric trait. Unlike passwords, the biometric templates cannot be revoked and switch to another set of uncompromised identifiers when compromised. Therefore, fool-proof techniques satisfying the requirements of diversity, revocability, security and performance are required to protect stored templates such that both the security of the application and the users’ privacy are not compromised by the impostor attacks. Thus, this paper proposes a template protection scheme coined as random rectangular hashing to strengthen the multimodal biometric system. The performance of the proposed template protection scheme is measured using the fingerprint FVC2004 and PolyU palmprint databases.
Madhavi Gudavalli. 2014. \u201cIntegrated Biometric Template Security using Random Rectangular Hashing\u201d. Global Journal of Computer Science and Technology - E: Network, Web & Security GJCST-E Volume 14 (GJCST Volume 14 Issue E7): .
Crossref Journal DOI 10.17406/gjcst
Print ISSN 0975-4350
e-ISSN 0975-4172
The methods for personal identification and authentication are no exception.
The methods for personal identification and authentication are no exception.
Total Score: 113
Country: India
Subject: Global Journal of Computer Science and Technology - E: Network, Web & Security
Authors: Madhavi Gudavalli, Dr. D.Srinivasa Kumar, Dr. S.Viswanadha Raju (PhD/Dr. count: 2)
View Count (all-time): 236
Total Views (Real + Logic): 8323
Total Downloads (simulated): 2214
Publish Date: 2014 11, Wed
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Large centralized biometric databases, accessible over networks in real time are especially used for identification purposes. Multimodal biometric systems which are more robust and accurate in human identification require multiple templates storage of the same user analogous to individual biometric sources. This may raises concern about their usage and security when these stored templates are compromised since each person is believed to have a unique biometric trait. Unlike passwords, the biometric templates cannot be revoked and switch to another set of uncompromised identifiers when compromised. Therefore, fool-proof techniques satisfying the requirements of diversity, revocability, security and performance are required to protect stored templates such that both the security of the application and the users’ privacy are not compromised by the impostor attacks. Thus, this paper proposes a template protection scheme coined as random rectangular hashing to strengthen the multimodal biometric system. The performance of the proposed template protection scheme is measured using the fingerprint FVC2004 and PolyU palmprint databases.
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