Conventionally, as a technique to check identification without human intervention at the time of entering and leaving a facility and the like, personal authentication using biological information such as the fingerprint, face, veins, iris and the like (biometrics authentication) has been used. Unlike personal authentication using a magnetic card or PIN (Personal Identification Number), the personal authentication using biological information has advantages that there is no concern for losing a card, forgetting the PIN or fraudulent use of the card and PIN.
Here, with an example of a case using veins as biological information, an explanation about the personal authentication technique is made. FIG. 1 illustrates a configuration example of a personal authentication apparatus, and FIG. 2 is a flowchart illustrating an example of an authentication process that the personal authentication apparatus in FIG. 1 performs. The personal authentication apparatus in FIG. 1 includes an irradiating unit 101, an image capturing unit 102, an extracting unit 103, a storing unit 104, a collating unit 105, and a judging unit 106.
First, the irradiation unit 101 irradiates a part of the human body such as a palm 111 where it is easy to capture veins with near-infrared light (step 201), and the image capturing unit 102 obtains an image by capturing image of the intensity distribution of the reflected or transmitted light (step 202).
Next, the extracting unit 104 performs a feature extraction process to extract the vein image from the image (step 203). The storing unit 104 stores the vein image of each individual registered in advance. Feature information such as the vein image and the like obtained by image capturing at the time of authentication is called collation data, and the registered feature information is called registered data or registered template.
The collating unit 105 collates the collation data and the registered data (step 204), and the judging unit 106 judges whether or not they match (step 205), and outputs an authentication result 112 (step 206). When a judgment is made that the collation data and registered data match, a positive authentication result indicating the registered person is output, and when a judgment is made that the collation data and the registered data do not match, a negative authentication result is output.
Since biological information change to some extent even for the same person, it is desirable that variation to some extent is allowed in the matching judgment of the vein images. For example, the similarity between the collation data and the registered data is expressed by a measure called a collation distance, and when the collation distance is smaller than a given threshold, the judgment is made that the two match.
The collation data is, usually, stores in a storage apparatus such as the Integrated Circuit (IC) card owned by the user, a database of the server and the like, and the collation process is executed in a computer close to the user, a server under central control and the like. The server-type authentication in which the storage of registered data and the collation process are performed on a server has advantages of effectiveness by the centralization of computer resources and ease of management of registered data, enabling shared use among a plurality of places.
On the other hand, a problem of the server-type authentication is the risk that, due to a malicious intention or lack of care of the administrator and the like, biological information (registered data and collation data) may be leaked and used fraudulently. Unlike the PIN, it is impossible to change biological information itself of each individual, the influence is significant when leakage happens.
Therefore, to protect biological information, the encryption technique has been used conventionally. A method to extract feature information after performing a prescribed transformation process for biological information, and to collate the feature information and registered information has also been known. At this time, to prevent degradation of the authentication accuracy, a method to limit the transformation process to a line-symmetric transformation and rotation, and a method to limit the collation process to a special one have also been proposed.
In addition, to protect biological information, a method to quantize biological information as a discrete value and to apply the error correction code technique has also been known, and a secret calculation technique to perform an arbitrary calculation while keeping input data encrypted has also been known.
Furthermore, a method to perform an independent transformation process for each feature point extracted from fingerprint information, and a method to detect the position correction amount of a feature amount for authentication against a registered feature amount and to correct the feature amount for authentication have also been known.
Patent Document 1: Japanese Laid-open Patent Publication No. 2000-11176
Patent Document 2: Japanese Laid-open Patent Publication No. 2008-129743
Patent Document 3: Japanese Laid-open Patent Publication No. 2007-293807
Patent Document 4: Japanese Laid-open Patent Publication No. 2006-154033
Patent Document 5: Japanese Laid-open Patent Publication No. 2007-328502
Patent Document 6: Japanese Laid-open Patent Publication No. 2010-108365
Non-Patent Document
Non-Patent Document 1: A. Juels and M. Sudan, “A Fuzzy Vault Scheme”, Proceedings of IEEE International Symposium on Information Theory, 2002, p. 408.