Multi-instance iris remote authentication using private multi-class perceptron on malicious cloud server
In recent years, biometric authentication system ( BAS ) has become the most promising and popular authentication system in identity management. Due to its capability to solve the limitations of unimodal systems, multi-biometric systems ( MBS ) have been extensively accepted in various fields. The m...
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| Vydáno v: | Applied intelligence (Dordrecht, Netherlands) Ročník 50; číslo 9; s. 2848 - 2866 |
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| Hlavní autoři: | , , , |
| Médium: | Journal Article |
| Jazyk: | angličtina |
| Vydáno: |
New York
Springer US
01.09.2020
Springer Nature B.V |
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| ISSN: | 0924-669X, 1573-7497 |
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| Abstract | In recent years, biometric authentication system (
BAS
) has become the most promising and popular authentication system in identity management. Due to its capability to solve the limitations of unimodal systems, multi-biometric systems (
MBS
) have been extensively accepted in various fields. The main step in
MBS
is information fusion. On the other hand, directly storing the fused templates into a centralized server leads to privacy concerns. Recently, many
BAS
based on homomorphic encryption has been introduced to provide confidentiality for the fused templates. However, most of the existing solutions rely on an implication of the assumption that the server is “Honest-but-Curious”. As a result, the compromise of such server results into entire system vulnerability. To address this, we propose a novel
P
rivacy
P
reserving (
PP
) multi-instance iris remote authentication system to accord with attacks at the malicious server and over the transmission channel. Our scheme uses
F
ully
H
omomorphic
E
ncryption (
FHE
) to achieve the confidentiality of the fused iris templates and polynomial factorization algorithm to achieve the integrity of the matching result. We propose a
PP
iris authentication system using
P
rivate
M
ulti-
C
lass
P
erceptron (
PMCP
) by using the properties of
FHE
. Moreover, we propose
C
ontradistinguish
S
imilarity
A
nalysis (
CSA
), a feature level fusion technique that minimizes the between-class correlations and maximizes the pair-wise correlations. Our method has experimented on IITD and CASIA-V3-Interval iris databases to check the effectiveness and robustness. Experimental results show that our method provides improved accuracy, and eliminates the need to trust the cloud server when compared to the state-of-the-art approaches. |
|---|---|
| AbstractList | In recent years, biometric authentication system (
BAS
) has become the most promising and popular authentication system in identity management. Due to its capability to solve the limitations of unimodal systems, multi-biometric systems (
MBS
) have been extensively accepted in various fields. The main step in
MBS
is information fusion. On the other hand, directly storing the fused templates into a centralized server leads to privacy concerns. Recently, many
BAS
based on homomorphic encryption has been introduced to provide confidentiality for the fused templates. However, most of the existing solutions rely on an implication of the assumption that the server is “Honest-but-Curious”. As a result, the compromise of such server results into entire system vulnerability. To address this, we propose a novel
P
rivacy
P
reserving (
PP
) multi-instance iris remote authentication system to accord with attacks at the malicious server and over the transmission channel. Our scheme uses
F
ully
H
omomorphic
E
ncryption (
FHE
) to achieve the confidentiality of the fused iris templates and polynomial factorization algorithm to achieve the integrity of the matching result. We propose a
PP
iris authentication system using
P
rivate
M
ulti-
C
lass
P
erceptron (
PMCP
) by using the properties of
FHE
. Moreover, we propose
C
ontradistinguish
S
imilarity
A
nalysis (
CSA
), a feature level fusion technique that minimizes the between-class correlations and maximizes the pair-wise correlations. Our method has experimented on IITD and CASIA-V3-Interval iris databases to check the effectiveness and robustness. Experimental results show that our method provides improved accuracy, and eliminates the need to trust the cloud server when compared to the state-of-the-art approaches. In recent years, biometric authentication system (BAS) has become the most promising and popular authentication system in identity management. Due to its capability to solve the limitations of unimodal systems, multi-biometric systems (MBS) have been extensively accepted in various fields. The main step in MBS is information fusion. On the other hand, directly storing the fused templates into a centralized server leads to privacy concerns. Recently, many BAS based on homomorphic encryption has been introduced to provide confidentiality for the fused templates. However, most of the existing solutions rely on an implication of the assumption that the server is “Honest-but-Curious”. As a result, the compromise of such server results into entire system vulnerability. To address this, we propose a novel P rivacy P reserving (PP) multi-instance iris remote authentication system to accord with attacks at the malicious server and over the transmission channel. Our scheme uses F ully H omomorphic E ncryption (FHE) to achieve the confidentiality of the fused iris templates and polynomial factorization algorithm to achieve the integrity of the matching result. We propose a PP iris authentication system using P rivate M ulti-C lass P erceptron (PMCP) by using the properties of FHE. Moreover, we propose C ontradistinguish S imilarity A nalysis (CSA), a feature level fusion technique that minimizes the between-class correlations and maximizes the pair-wise correlations. Our method has experimented on IITD and CASIA-V3-Interval iris databases to check the effectiveness and robustness. Experimental results show that our method provides improved accuracy, and eliminates the need to trust the cloud server when compared to the state-of-the-art approaches. |
| Author | Morampudi, Mahesh Kumar Raju, U. S. N. Prasad, Munaga V. N. K. Veldandi, Sowmya |
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| Cites_doi | 10.1109/TIFS.2016.2569061 10.1186/1687-417X-2011-3 10.1109/MSP.2018.3761723 10.1016/j.patcog.2009.08.016 10.1016/j.patcog.2004.12.013 10.1109/MSECP.2003.1193209 10.1109/MSP.2015.2434151 10.1002/sec.1164 10.1109/TCSVT.2003.818350 10.1109/MSP.2015.2437652 10.1016/j.patcog.2017.01.024 10.1007/s10623-012-9720-4 10.1186/s13635-016-0049-9 10.1007/s10623-015-0079-1 10.1016/j.eswa.2019.01.010 10.1186/1687-417X-2007-037343 10.1109/TIFS.2015.2416688 10.1016/S0031-3203(02)00262-5 10.1109/TIFS.2011.2108650 10.1109/83.913594 10.1155/2008/579416 10.1109/TIFS.2014.2384735 10.1016/j.patcog.2019.04.010 10.1016/j.asoc.2018.02.047 10.1109/TIFS.2011.2108288 10.1098/rspb.2001.1696 10.1108/IJPCC-02-2015-0012 10.1007/s11042-017-4668-z 10.1145/581571.581573 10.1007/s10044-017-0656-1 10.1007/3-540-48910-X_16 10.1109/CCC.2010.26 10.1007/978-3-642-36362-7_1 10.1109/TETC.2018.2794611 10.1109/ICCUBEA.2018.8697811 10.1007/978-3-642-13190-5_1 10.1109/CCST.2006.313444 10.1007/978-3-642-14623-7_25 10.1145/1101149.1101236 10.1007/978-3-642-42045-0_16 10.1007/978-1-4471-6784-6_16 10.1007/978-3-642-29011-4_28 10.1007/s10462-019-09776-7 10.1007/978-3-642-23822-2_11 |
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| Keywords | Fully homomorphic encryption Contradistinguish similarity analysis Correlation analysis Private multi-class perceptron Multi-biometric systems |
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| Title | Multi-instance iris remote authentication using private multi-class perceptron on malicious cloud server |
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