Notice: RCIS was reformed into RISEC on April 1, 2012.
It has been further merged into new Information Technology Research Institute on April 1, 2015.

Research Topics
AIST > RCIS > Research Topics > Biometrics security

Biometrics security

Abstract

A biometric authentication system automatically authenticates an individual by using her/his physiological or behavioral characteristics. For example, fingerprint, face, iris, and vascular patterns are included in the physiological characteristics. Recently, the use of the biometric authentication systems has spread in various services such as the access control for a mobile phone and PC, the customer's authentication at a bank's ATM (automated tellers machine) terminal, the immigration control at an airport, and so on.

Unfortunately, a security evaluation method for a biometric authentication system has not been sufficiently established so far. In order to realize a reliable biometric authentication system with high security, it is necessary to develop the security evaluation method as the priority issue.

Our main research objective is to develop such a rigourous security method and, on the basis of our method, propose a new biometric authentication technique that is verifiable by a third party as one not only with high security but also with high usability (e.g. low FRR, high speed processing). Especially, we are now focusing on how to develop a quantative security measure against impersonation attacks. Moreover, we are also studying the security of template protection schemes or cancelable biometric authentication systems.

As a recent result, we proposed an important security measure, ``the wolf attack probability (WAP)''. WAP is a maximum success probability of a wolf attack, which is an attempt to impersonate a victim using wolves (i.e. input samples that show high similarity to most of templates). WAP can be used as the theoretical measure to evaluate a lower bound of a security level in a biometric authentication system. We applied the wolf attack to a finger-vein-pattern matching algorithm, a typical fingerprint-minutiae matching algorithm and an iris recognition algorithm, and computed WAP in their algorithms. Moreover, we proposed a theoretical framework for constructing matching algorithms secure against the wolf attack and evaluated previous algorithms in our proposed framework. We are now developing efficient and secure matching algorithms.

Members

  • Manabu Inuma
  • Akira Otsuka
  • Rie Shigetomi

Selected Results

  • M. Inuma, A. Otsuka, H. Imai, ``Theoretical framework for constructing matching algorithms in biometric authentication systems,'' Proceedings of 3rd International Conference on Biometrics (ICB 2009), June 2009
  • M. Une, A. Otsuka, H. Imai, ``Wolf Attack Probability: A Theoretical Security Measure in Biometrics-Based Authentication Systems,'' IEICE, Trans. on Info. and Sys. 2008, E91-D(5)