A Theoretical Framework for Constructing Matching Algorithms Secure against Wolf Attack

Manabu INUMA; Akira OTSUKA; Hideki IMAI

doi:10.1587/transinf.E96.D.357

A Theoretical Framework for Constructing Matching Algorithms Secure against Wolf Attack

Manabu INUMA, Akira OTSUKA, Hideki IMAI

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The security of biometric authentication systems against impersonation attack is usually evaluated by the false accept rate, FAR. The false accept rate FAR is a metric for zero-effort impersonation attack assuming that the attacker attempts to impersonate a user by presenting his own biometric sample to the system. However, when the attacker has some information about algorithms in the biometric authentication system, he might be able to find a “strange” sample (called a wolf) which shows high similarity to many templates and attempt to impersonate a user by presenting a wolf. Une, Otsuka, Imai [22],[23] formulated such a stronger impersonation attack (called it wolf attack), defined a new security metric (called wolf attack probability, WAP), and showed that WAP is extremely higher than FAR in a fingerprint-minutiae matching algorithm proposed by Ratha et al. [19] and in a finger-vein-patterns matching algorithm proposed by Miura et al. [15]. Previously, we constructed secure matching algorithms based on a feature-dependent threshold approach [8] and showed that if the score distribution is perfectly estimated for each input feature data, then the proposed algorithms can lower WAP to a small value almost the same as FAR. In this paper, in addition to reintroducing the results of our previous work [8], we show that the proposed matching algorithm can keep the false reject rate (FRR) low enough without degrading security, if the score distribution is normal for each feature data.

Publication: IEICE TRANSACTIONS on Information Vol.E96-D No.2 pp.357-364

Publication Date: 2013/02/01

Publicized

Online ISSN: 1745-1361

DOI: 10.1587/transinf.E96.D.357

Type of Manuscript: PAPER

Category: Image Recognition, Computer Vision

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Manabu INUMA, Akira OTSUKA, Hideki IMAI, "A Theoretical Framework for Constructing Matching Algorithms Secure against Wolf Attack" in IEICE TRANSACTIONS on Information, vol. E96-D, no. 2, pp. 357-364, February 2013, doi: 10.1587/transinf.E96.D.357.
Abstract: The security of biometric authentication systems against impersonation attack is usually evaluated by the false accept rate, FAR. The false accept rate FAR is a metric for zero-effort impersonation attack assuming that the attacker attempts to impersonate a user by presenting his own biometric sample to the system. However, when the attacker has some information about algorithms in the biometric authentication system, he might be able to find a “strange” sample (called a wolf) which shows high similarity to many templates and attempt to impersonate a user by presenting a wolf. Une, Otsuka, Imai [22],[23] formulated such a stronger impersonation attack (called it wolf attack), defined a new security metric (called wolf attack probability, WAP), and showed that WAP is extremely higher than FAR in a fingerprint-minutiae matching algorithm proposed by Ratha et al. [19] and in a finger-vein-patterns matching algorithm proposed by Miura et al. [15]. Previously, we constructed secure matching algorithms based on a feature-dependent threshold approach [8] and showed that if the score distribution is perfectly estimated for each input feature data, then the proposed algorithms can lower WAP to a small value almost the same as FAR. In this paper, in addition to reintroducing the results of our previous work [8], we show that the proposed matching algorithm can keep the false reject rate (FRR) low enough without degrading security, if the score distribution is normal for each feature data.
URL: https://global.ieice.org/en_transactions/information/10.1587/transinf.E96.D.357/_p

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@ARTICLE{e96-d_2_357,
author={Manabu INUMA, Akira OTSUKA, Hideki IMAI, },
journal={IEICE TRANSACTIONS on Information},
title={A Theoretical Framework for Constructing Matching Algorithms Secure against Wolf Attack},
year={2013},
volume={E96-D},
number={2},
pages={357-364},
abstract={The security of biometric authentication systems against impersonation attack is usually evaluated by the false accept rate, FAR. The false accept rate FAR is a metric for zero-effort impersonation attack assuming that the attacker attempts to impersonate a user by presenting his own biometric sample to the system. However, when the attacker has some information about algorithms in the biometric authentication system, he might be able to find a “strange” sample (called a wolf) which shows high similarity to many templates and attempt to impersonate a user by presenting a wolf. Une, Otsuka, Imai [22],[23] formulated such a stronger impersonation attack (called it wolf attack), defined a new security metric (called wolf attack probability, WAP), and showed that WAP is extremely higher than FAR in a fingerprint-minutiae matching algorithm proposed by Ratha et al. [19] and in a finger-vein-patterns matching algorithm proposed by Miura et al. [15]. Previously, we constructed secure matching algorithms based on a feature-dependent threshold approach [8] and showed that if the score distribution is perfectly estimated for each input feature data, then the proposed algorithms can lower WAP to a small value almost the same as FAR. In this paper, in addition to reintroducing the results of our previous work [8], we show that the proposed matching algorithm can keep the false reject rate (FRR) low enough without degrading security, if the score distribution is normal for each feature data.},
keywords={},
doi={10.1587/transinf.E96.D.357},
ISSN={1745-1361},
month={February},}

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TY - JOUR
TI - A Theoretical Framework for Constructing Matching Algorithms Secure against Wolf Attack
T2 - IEICE TRANSACTIONS on Information
SP - 357
EP - 364
AU - Manabu INUMA
AU - Akira OTSUKA
AU - Hideki IMAI
PY - 2013
DO - 10.1587/transinf.E96.D.357
JO - IEICE TRANSACTIONS on Information
SN - 1745-1361
VL - E96-D
IS - 2
JA - IEICE TRANSACTIONS on Information
Y1 - February 2013
AB - The security of biometric authentication systems against impersonation attack is usually evaluated by the false accept rate, FAR. The false accept rate FAR is a metric for zero-effort impersonation attack assuming that the attacker attempts to impersonate a user by presenting his own biometric sample to the system. However, when the attacker has some information about algorithms in the biometric authentication system, he might be able to find a “strange” sample (called a wolf) which shows high similarity to many templates and attempt to impersonate a user by presenting a wolf. Une, Otsuka, Imai [22],[23] formulated such a stronger impersonation attack (called it wolf attack), defined a new security metric (called wolf attack probability, WAP), and showed that WAP is extremely higher than FAR in a fingerprint-minutiae matching algorithm proposed by Ratha et al. [19] and in a finger-vein-patterns matching algorithm proposed by Miura et al. [15]. Previously, we constructed secure matching algorithms based on a feature-dependent threshold approach [8] and showed that if the score distribution is perfectly estimated for each input feature data, then the proposed algorithms can lower WAP to a small value almost the same as FAR. In this paper, in addition to reintroducing the results of our previous work [8], we show that the proposed matching algorithm can keep the false reject rate (FRR) low enough without degrading security, if the score distribution is normal for each feature data.
ER -