JP2005317049A - Personal authentication system and method - Google Patents

Abstract

<P>PROBLEM TO BE SOLVED: To provide a personal authentication method capable of selecting types of biological information used for authentication flexibly depending on the user and the environment. <P>SOLUTION: During registration, a plurality of types of biological information are acquired from the user, feature information is extracted from the acquired biological information, and authentication precision is estimated for each combination of pieces of feature information. During authentication, at least one type of biological information is acquired from the user, feature information is extracted from the acquired biological information, personal authentication is performed by comparing the acquired feature information with the feature information extracted from the biological information during registration, and operation of the person to be authenticated is controlled according to the authentication precision. <P>COPYRIGHT: (C)2006,JPO&NCIPI

Description

  The present invention relates to a technique for performing personal authentication using biometric information, and particularly belongs to a technique for performing integrated authentication from a plurality of types of biometric information.

  In recent years, personal authentication technology has attracted attention because of the development of electronic commerce using networks and the increasing importance of entrance / exit management for spaces that require physical security. Among personal authentication technologies, in particular, the method of performing individual identification (Biometrics) using information on human biometric features is in the limelight. Available biometric features include fingerprints, irises, vascular patterns on the retina, and faces. Voiceprints have been proposed.

However, when using various biometrics personal authentication alone,
(1) Limit of authentication performance (2) There is a problem that a specific user cannot use due to injury of a living body part used for authentication.

  With respect to the problem (1), several methods for integrating a plurality of pieces of biometric information to improve the authentication performance have been proposed (Japanese Patent Laid-Open Nos. 8-16788, 11-253426, 11-11). No. 306351, Japanese Patent Laid-Open No. 2000-242786, etc.).

  Japanese Patent Application Laid-Open No. 8-16788 acquires a plurality of pieces of biometric information from a person to be authenticated, divides the read feature parameters into a plurality of categories, and weights the divided categories according to the ease of appearance of the individual features. Are integrated, and the result of the integration is compared with a threshold value to confirm the identity.

  Japanese Patent Laid-Open No. 11-253426 generates a collation score vector with the number of collation scores for each biometric feature collation unit as the number of dimensions, and uses linear discrimination, secondary discrimination, neuro, and statistical probability in a vector space. , And “category” or “unfair” categories.

  Japanese Patent Laid-Open No. 11-306351 normalizes a plurality of matching scores for each biometric feature matching unit using probabilities, and integrates them using weighted sums and weighted products of the probabilities.

Japanese Patent Laid-Open No. 2000-242786 integrates a plurality of authentication results for each biometric feature matching unit corresponding to “valid” or “unfair” using logical sum and logical product.
JP-A-8-16788 JP-A-11-253426 JP-A-11-306351 JP 2000-242786 A

  All of the above-described conventional techniques focus on how to integrate authentication results determined from a plurality of pieces of biometric information. That is, although it is a technique related to so-called “multimodal authentication” that uses a plurality of biometric information together, the type of biometric information to be used is predetermined, and all biometric information can always be acquired at the time of authentication. It is assumed. In the example of Japanese Patent Application Laid-Open No. 8-16788, for a category in which personal features are difficult to appear, a mechanism is adopted that is not reflected in the authentication standard as a result of weighting. It is assumed that you enter it.

  Here, the above problem (2), that is, “a specific user cannot use some biological information” is considered.

  If the user has a finger that is not suitable for fingerprint authentication (for example, the fingerprint pattern is thin due to chemicals or friction, or the skin is not suitable for a semiconductor fingerprint sensor), The user is not informed that his / her fingerprint is not suitable for authentication, and must always input a plurality of pieces of biometric information including “fingerprints” determined by the authentication device at the time of authentication. This impairs user convenience.

  Also, if some types of biometric information are not suitable for authentication, or some biometric information is temporarily unavailable due to trauma, etc. Thus, the original effect of “multimodal authentication” for improving the authentication performance may be difficult to obtain, and the authentication performance may be deteriorated.

  Furthermore, when it is difficult to input biometric information in a specific environment such as “voice print” input under noise, the same problem occurs when the types of biometric information to be input are reduced, Authentication performance may be degraded.

  In view of the above problems, it is an object of the present invention to improve the convenience of the user and suppress the influence due to the deterioration of the authentication performance in personal authentication in which a plurality of types of biometric features can be used. .

  In order to solve the above-described problem, the solving means taken by the invention of claim 1 is an apparatus for performing personal authentication, wherein an input unit configured to be able to input information on a plurality of types of biometric features, and a user Information indicating the relationship between the combination of the biometric features and the authentication accuracy is stored in advance using the selection input unit for selecting the biometric features to which information is input from the input unit and the biometric feature combination selected by the selection input unit. An authentication accuracy determination unit that obtains the authentication accuracy in the authentication by searching the database, and a display unit that displays the authentication level by the authentication based on the authentication accuracy obtained by the authentication accuracy determination unit. is there.

  According to the first aspect of the present invention, since the authentication level corresponding to the selected combination of biometric features is displayed on the display unit, the convenience for the user can be greatly improved.

  According to a second aspect of the present invention, there is provided a solving means comprising: an input unit configured to be able to input information on a plurality of types of biometric features as a device for performing personal authentication; and a biometric feature capable of inputting information from the input unit. Authentication accuracy determination for obtaining authentication accuracy for each biometric feature combination that can be input from the input unit by searching a database that stores information indicating a relationship between the biometric feature combination and authentication accuracy in advance using the combination An authentication level determining unit that determines an authentication level for each combination of biometric features that can be input from the input unit based on the authentication accuracy obtained by the authentication accuracy determining unit, and a biometric that is capable of inputting information from the input unit And a display unit that displays information indicating a relationship between the combination of features and the authentication level determined by the authentication level determination unit.

  According to the second aspect of the present invention, information indicating the relationship between the combination of biometric features into which information can be input and the authentication level is displayed on the display unit, so that the convenience for the user can be greatly improved.

  According to a third aspect of the present invention, in the personal authentication apparatus according to the first or second aspect of the present invention, the authentication level is selected from a room that can be entered, an upper limit amount of electronic commerce, or an available command or site. It shall be either.

  According to the present invention, a user can flexibly select biometric information to be used at the time of authentication, for example, in accordance with the status of his / her biometric features and the surrounding environment. Further, since the authentication accuracy based on the input biometric information is required, it becomes possible to control the operation of the person to be authenticated in accordance with the authentication accuracy, and the deterioration of the authentication performance can be suppressed in advance.

  Hereinafter, embodiments of the present invention will be described with reference to the drawings.

  FIG. 1 is a diagram conceptually showing technical features of personal authentication according to the present invention. As shown in FIG. 1, in the present invention, at the time of registration, feature information is extracted from information on a plurality of types of biometric features for each person to be registered. At this time, “authentication accuracy” is estimated for each combination of feature information extracted from each biological information, and the “authentication accuracy” is held. Here, “authentication accuracy” is an index that indicates how stable a person can be distinguished from others when using a certain feature information (combination). Will be described later.

  On the other hand, at the time of authentication, feature information is extracted from the biometric information that can be acquired at the time of authentication, and personal authentication is performed by comparing with the feature information at the time of registration. At this time, the authentication accuracy estimated at the time of registration for the combination of biometric features to be used is used to control the operation of the person to be authenticated. As a result, even if there are few biometric features that can be used at the time of authentication and the authentication accuracy is low, it is possible to suppress the effects of a decrease in authentication performance, and to minimize the damage caused by incorrect authentication. Can do.

(First embodiment)
FIG. 2 is a schematic configuration diagram of the personal authentication system according to the first embodiment of the present invention. In FIG. 2, a personal authentication server 11 as a personal authentication device has a biometric feature database (DB) 12 that stores biometric feature data of a plurality of persons, and is connected to a network 13 such as the Internet, a dedicated line, or a public line. ing. A biometric feature registration device 14 for inputting biometric feature information at the time of registration and a personal authentication terminal 15 for inputting biometric feature information at the time of authentication are connected to the network 13.

  A plurality of personal authentication servers 11 may be provided for each area or organization to be used, or a plurality of personal authentication servers 11 may be provided including a mirror server for distributing the load. The biometric feature DB 12 may be connected to the personal authentication server 11 via the network 13. Furthermore, the function of the biometric feature registration device 14 may be built in the personal authentication server 11, or the personal authentication terminal 15 may have both functions of registration and authentication. Further, when there are a plurality of personal authentication terminals 15, their specifications (types of built-in input devices, etc.) are not necessarily the same.

  3 and 4 are flowcharts showing the flow of processing at the time of registration and at the time of authentication in the personal authentication method according to the present embodiment. Hereinafter, the flow of personal authentication processing according to the present embodiment will be described separately for registration and authentication.

<During registration>
As shown in FIG. 3, at the time of registration, the biometric feature registration device 14 first inputs information on a plurality of types of biometric features of the registrant (SA01). In the present embodiment, it is assumed that information on five types of biometric features “fingerprint”, “iris”, “face”, “voiceprint”, and “handwriting” is input. The biometric feature registration apparatus 14 is provided with an input device for each biometric feature in advance. For example, a semiconductor (or optical) fingerprint scanner is used for “fingerprint”. Similarly, illumination and camera are used for “iris” and “face”, a microphone is used for “voiceprint”, and “handwriting” is used. For example, a tablet is used.

  Next, the biometric feature registration device 14 extracts feature information used for authentication from each input biometric information (SA02). The feature extraction here may use a method generally known for each piece of biological information. Of course, in order to improve the performance of the entire authentication system, it is desirable to use a feature extraction method that can obtain higher authentication performance when each biometric feature is used alone.

The number of dimensions of the extracted feature information is d1, d2, d3, d4, and d5 for “fingerprint”, “iris”, “face”, “voiceprint”, and “handwriting”, respectively. At this time, the total number of dimensions da is
da = d1 + d2 + d3 + d4 + d5
It becomes. In addition, regarding these feature information, when different representation formats such as a floating-point format such as double and float and an integer type are mixed, all of them are unified into the same representation format. Here, it is assumed that all are converted to an integer type of N gradations. At this time, normalization is performed so that the variance is constant for all dimensions. The reason for normalizing the feature information is to equalize all the influences of each dimension on the overall identification performance in each feature information.

  Such input of biometric information and feature extraction (SA01, SA02) are performed for all persons to be registered. The extracted feature information is transmitted to the personal authentication server 11. Note that the personal authentication server 11 may execute the process SA02 for extracting feature information from the biometric information. In this case, the biometric information input to the biometric feature registration device 14 is transmitted to the personal authentication server 11.

  Next, the personal authentication server 11 estimates the authentication accuracy for each combination of biometric features related to the transmitted feature information (including single use of each feature information) (SA03). The authentication accuracy is estimated as follows.

  FIG. 5 is a diagram conceptually illustrating the authentication distance distribution D1 between the same persons and the authentication distance distribution D2 between other persons regarding certain feature information. Since the distribution of FIG. 5 is created for each person, when referring to the person P, the distribution D1 is the distribution of the authentication distance between the persons P, and the distribution D2 is the distribution of the authentication distance between the person P and all the persons other than the person P. It is. The “authentication distance” here is a comparison between feature information extracted from biometric information using some distance scale. For example, if the total number of dimensions of the combination of feature information is D-dimension and the distance scale is Euclidean distance, the Euclidean distance in the D-dimensional space is the authentication distance. The authentication distance is small between the feature information of the principals, and the authentication distance is large between the feature information of the other people. Further, when each dimension of the feature information is expressed in binary, the Hamming distance of a da-dimensional binary vector obtained by simply combining all bits may be used as the authentication distance.

  Note that when similarity or correlation value is used instead of distance, it becomes a large value between the feature information of the principals, and a small value between the feature information of the other people.

  Moreover, a neural network that separates the person from the other person in the da-dimensional space is learned, and the reliability of the determination result of the person and the other person is expressed from the neuro output value when each data used for learning is input. A numerical value may be calculated and the numerical value (reliability) may be used as the authentication distance.

  Similarly, in the da-dimensional space, a linear discriminant function or a quadratic discriminant function that distinguishes the person from others is calculated, and each data used for calculating the function and the distance from the discriminant plane (hyperplane) are authenticated. It may be used as a distance. With a simple Euclidean distance, all dimensions are handled with the same weight, but if a discriminant function is defined, a dimension that is effective for discrimination and a dimension that is not so can be distinguished and treated by the coefficient of the discriminant function. Convenient for identification.

  In the present embodiment, a new feature information is created by combining feature information extracted from each piece of biological information, and the person is identified from another person using the feature information. On the other hand, identification is performed for each biometric feature (identification may be performed by a different method), and the authentication distance obtained by each identification (value according to) is normalized and then normalized. An authentication distance vector having each dimension as a later authentication distance may be created, and a distance scale may be defined in the authentication distance vector space to further distinguish the person from the other person, and the distance scale may be used as the authentication distance. .

  In addition, when the threshold TH for identifying the person and the other person is determined as shown in FIG. 5, the part of the other person's distribution D2 that has an authentication distance smaller than the threshold TH (shaded part A1) is the other person's person. This is equivalent to the case of false acceptance (False Acceptance). Therefore, the probability that another person is erroneously accepted (false acceptance rate: FAR) can be “estimated” to some extent from the distribution shown in FIG.

  On the other hand, a portion (shaded portion A2) having an authentication distance larger than the threshold TH in the distribution D1 of the principal corresponds to a case where the principal is mistakenly rejected by another person (False Rejection). Like the other person acceptance rate FAR, the probability that the person is mistakenly rejected by another person (person rejection rate: FRR) can also be “estimated” from the distribution shown in FIG.

  Here, the expression “trial calculation” is used because FAR and FRR that can be calculated by the above-described method are calculated from the distribution of feature information obtained at the time of registration. What is FAR and FRR at the time of authentication? (Of course, the larger the number of feature information at the time of registration, the closer the distribution created at the time of registration becomes to the distribution at the time of authentication, and the calculated FAR and FRR are the FAR and FRR at the time of authentication. It ’s a good estimate).

  Note that FAR and FRR depend on how the threshold value TH is determined, and the threshold value TH can be intentionally determined depending on the purpose of authentication. For example, when it is absolutely desired to exclude others, the rejection rate FRR may be somewhat large, so the threshold value TH may be set to a smaller value (shifted to the left in FIG. 5), and the user interface is rejected when the person is rejected. If it becomes very difficult to use from the point of view, the threshold TH may be set larger at the expense of the other-person acceptance rate FAR (shifted to the right in FIG. 5).

  In the present embodiment, in the distribution as shown in FIG. 5, the threshold value TH is determined so that the calculated FAR and FRR are equal (the area of A1 is equal to the area of A2). Of course, the threshold value TH may be determined by other methods. For example, the threshold value TH may be set at a position where the distribution D1 of the principal person and the distribution D2 of the other person intersect, or FRR or FAR may be a predetermined value. The position may be set.

  If the number of data registered in the biometric feature DB 12 is not sufficiently large, the two distributions D1 and D2 may not overlap as shown in FIG. In this case, the threshold TH may be determined after approximating both distributions with an appropriate function such as a Gaussian function to create an overlapping portion.

  Here, it is assumed that the distribution D1 between the users is available. Therefore, there must be a plurality of pieces of personal characteristic information. When a camera is used as an input device in order to efficiently obtain a plurality of feature information, the following method can be used.

  For example, in the case of “face”, a face image is taken as a moving image for several seconds, and each frame image of the moving image is extracted and used as a registered image. For example, in the case of shooting for 3 seconds using a progressive scan camera of 30 frames / second, a total of 90 face images are obtained. These images can be used as registration images, except for images that have problems such as blinking moments. In this case, a face image obtained under various conditions can be obtained by taking a moving image while changing the position and brightness of the illumination or slightly moving the position of the camera.

  In contrast, “voiceprint” using a microphone and “handwriting” using a tablet have to input biometric information a plurality of times in order to obtain a plurality of feature information.

  In addition, each time authentication is performed, the distribution D1 of the person can be updated by additionally registering the feature information that has been authenticated as the person in the biometric feature DB 12.

  In this embodiment, for each target user, a distribution as shown in FIG. 5 is created for each combination of feature information extracted from biometric information, and authentication accuracy is estimated. In this embodiment, the value “1-FAR”, that is, the probability that another person is not accepted as the principal is employed as the authentication accuracy. As described above, since the threshold value TH is set so that FAR and FRR are equal, the authentication accuracy is substantially “1-FRR”.

  A biometric feature such as a combination of “fingerprint” and “iris” (feature information is (d1 + d2) dimension) and a combination of three types of biometric features of “fingerprint”, “iris”, and “face” (feature information is (d1 + d2 + d3) dimension) For all the combinations, the distribution of authentication distance as shown in FIG. 5 is obtained, and the authentication accuracy (1-FAR) is estimated.

  In this way, since the authentication accuracy is estimated for each combination of biometric features for each user, for example, a person whose fingerprint has become thin due to medicine or friction is a combination including “fingerprint” (for example, “fingerprint” When using “iris” and “face”), the authentication accuracy is lower than when using a combination not including “fingerprint” (for example, “iris” and “face”). This decrease in authentication accuracy is caused by the fact that the fingerprint pattern cannot be stably extracted, and thus the distribution width of the personal distribution D1 in FIG. 5 is widened and the FRR is increased.

  Even if there are many others who have a fingerprint similar to the person by chance, the combination including “fingerprint” is lower in authentication accuracy than the combination not including “fingerprint” as in the above example. there is a possibility. This is because there are many others who have fingerprints similar to the principal, and the distance between the principal distribution D1 and the stranger distribution D2 in FIG.

  That is, according to this embodiment, it is possible to easily know which combination of biometric features is appropriate for the user from the authentication accuracy of each combination of biometric features.

  Then, the personal authentication server 11 stores the calculated authentication accuracy in the biometric feature DB 12 (SA04). FIG. 6 is an example of authentication accuracy information stored in the biometric feature DB 12. In FIG. 6, the relationship between the combination of biometric features and the authentication accuracy is shown in a table format for a certain person P (in FIG. 6, not only the authentication accuracy “1-FAR” but also the FAR value for reference). Also shown). Basically, it is considered that the combination of many biometric features improves the authentication accuracy. However, in the example of FIG. 6, since the person P happens to have a fingerprint that is not suitable for authentication, authentication of “fingerprint” alone The accuracy is low. For this reason, if there is a “fingerprint” in the combination of biometric features, the authentication accuracy is reduced.

  The processes SA03 to SA04 are processes performed at the time of registration. However, when new feature information is added to the biometric feature DB 12 or when registered feature information of a certain person is updated, processing is performed on data of all persons. If SA03 to SA04 are re-executed, the authentication accuracy reflecting the new feature information can always be maintained. In addition, if it is not preferable to execute it every registration / update because of an increase in calculation load, it may be executed periodically such as once a week or once a month.

  Also, for example, at the time of initial registration, five types of biometric information “fingerprint”, “iris”, “face”, “voiceprint”, and “handwriting” are registered, but another biometric feature registration device 14 is equipped with a palm-shaped input device. In this case, it is also possible to register the “palm shape” through the biometric feature registration device 14 at a later date. In this case, biometric information is input only for the “palm” (SA01), and feature information is extracted (SA02). Then, in addition to all the conventional combinations, all the authentication accuracy in the case of the combination of “palm shape” is estimated (SA03), and the estimated authentication accuracy is stored (SA04).

  In addition, when the authentication accuracy X that should be guaranteed at least is determined in advance, a combination whose estimated authentication accuracy is smaller than X may not be used for authentication.

  Also, at the end of registration, it is possible to notify the registrant of a combination of biometric features that does not satisfy the authentication accuracy that should be guaranteed at the minimum, so that the biometric features suitable for each user to be authenticated can be notified. Conversely, a combination of biometric features with high authentication accuracy may be notified as a combination suitable for the user. In the example of FIG. 6, “iris”, “face”, “voiceprint”, and “handwriting” are notified as the most effective combination of biometric features for the person P. In addition, a combination of biometric features having high authentication accuracy and suitable for the user can be set in advance as a password.

<At the time of authentication>
Next, processing at the time of authentication will be described with reference to the flowchart of FIG.

  At the time of authentication, first, a user (authenticated person) who wants to be authenticated performs input of his / her personal ID and selection of biometric features for which information is to be input from the personal authentication terminal 15 (SB01). . The input personal ID and the selected biometric feature type are transmitted from the personal authentication terminal 15 to the personal authentication server 11.

  Here, it is assumed that the most suitable combination of biometric features notified to each user at the time of registration is selected. In this case, for example, at the time of registration, a biometric feature combination with high authentication accuracy is set in advance as a password, and whether or not the biometric feature combination selected at the time of authentication matches the combination set as the password for the personal ID If they do not match, authentication may not be performed.

  In addition, the user may select a biometric feature that is currently available. For example, if the user happens to be authenticated and happens to have a finger injured, the biometric feature may be selected excluding “fingerprint”.

  Further, the personal authentication terminal 15 may limit biometric features according to the surrounding environment. For example, when a surrounding sound immediately before authentication is measured by a microphone provided in the personal authentication terminal 15 and it is determined that the surrounding noise level is high, the “voice print” is excluded from the biometric feature selection candidates. Or similarly, when the ambient brightness is measured by a camera or illuminance sensor provided in the personal authentication terminal 15, and the measured brightness exceeds a predetermined threshold, it is determined that the influence of outside light such as sunlight is large, “Face” and “Iris” may be excluded from the selection candidates.

  Further, the biometric feature may be limited according to the type of sensor built in the personal authentication terminal 15. For example, when the personal authentication terminal 15 is a mobile phone type and includes a camera, a fingerprint sensor, and a microphone, but does not include a tablet, “handwriting” is excluded from the biometric feature selection candidates.

  Next, when the personal authentication server 11 receives the personal ID and the type of biometric feature transmitted from the personal authentication terminal 15, the authentication accuracy when this biometric feature is used is stored in the biometric feature DB 12 in FIG. The information is obtained by referring to the information as shown (SB02). The obtained authentication accuracy is transmitted to the personal authentication terminal 15 and presented to the user. At this time, if the level (threshold value) of authentication accuracy necessary for the authentication purpose is determined in advance, the personal authentication server 11 determines whether or not the authentication accuracy exceeds the threshold value, and does not exceed it. At this time, the biometric feature reselection request is notified to the user via the personal authentication terminal 15.

  For example, because the surrounding noise level is high, biometric features are selected except for “voice prints”, but if “voice prints” are not included and authentication accuracy required for authentication purposes cannot be obtained, authentication in a quieter place To the user. In addition, because the environment is greatly affected by external light, biometric features were selected except for “face” and “iris”. However, if at least one of “face” and “iris” is not included, the authentication accuracy required for authentication purposes can be obtained. If not, prompt users to authenticate in the shade. In addition, since the personal authentication terminal 15 does not incorporate a tablet, biometric features are selected except for “handwriting”. However, if the authentication accuracy required for authentication purposes cannot be obtained unless “handwriting” is included, The user is instructed to authenticate with another built-in personal authentication terminal 15.

  Further, if the obtained authentication accuracy does not exceed a threshold necessary for authentication purposes, the user's authentication itself may be simply rejected.

  Further, the authority granted to the user after authentication, that is, the “authentication level” can be presented to the user according to the obtained authentication accuracy.

  For example, when the authentication purpose is identification of electronic commerce, an upper limit of the transaction amount may be determined according to the obtained authentication accuracy, and the upper limit amount may be notified to the user. In addition, when the authentication purpose is entrance / exit management, a room that can be entered may be determined according to the authentication accuracy and notified, or when the authentication purpose is logging in to a PC or the like A command that can be executed according to the authentication accuracy (only browsing, rewritable, erasable, etc.) or an accessible site or directory may be determined and presented to the user.

  Next, the person to be authenticated actually inputs each selected biometric information from the personal authentication terminal 15 (SB03). The personal authentication terminal 15 extracts feature information for each biometric information of the input person to be authenticated (SB04). The extracted feature information is transmitted from the personal authentication terminal 15 to the personal authentication server 11.

  The personal authentication server 11 performs authentication using the transmitted feature information and the feature information of the corresponding biometric information stored in the biometric feature DB 12 (SB05). For example, the transmitted feature information is combined, and whether the person is the person or not is identified in the feature space of the combined feature information. Alternatively, authentication is performed by comparing each transmitted feature information with the corresponding registered feature information. At the same time, based on the combination of biometric features related to the acquired feature information, the biometric feature DB 12 is referred to determine the authentication accuracy in the authentication (SB06). For example, the authentication accuracy is obtained by referring to information indicating the relationship between each combination of biometric features and the authentication accuracy as shown in FIG.

  When it is determined that the person to be authenticated is the person, the personal authentication server 11 determines the authentication level based on the authentication accuracy, for example, the upper limit amount of electronic commerce, usable commands and sites, Or, a room that can be entered is determined (SB07). After that, authority after authentication is granted. For example, a key corresponding to the determined upper limit amount is issued to the EC server 16.

  As described above, according to the present embodiment, at the time of authentication, it is not always necessary to input all biometric information at the time of registration, and some biometric information may be input. For this reason, the user can flexibly select the biometric information to be used, for example, according to the status of his / her biometric features, the surrounding environment, and the like. Further, even when only a part of biometric information is input, authentication accuracy is required for the combination of input biometric features. And since an authentication level is defined according to this authentication precision, the influence by the fall of authentication performance can be suppressed beforehand, and the damage at the time of incorrect authentication can be suppressed to the minimum.

  Note that the process SB01 for selecting a biometric feature to be used and the process SB02 for presenting the authentication accuracy and the authentication level according to the selected combination of biometric information may be omitted.

  Further, the process SB04 for extracting the feature information of the biometric information is executed by the personal authentication terminal 15, but may be executed by the personal authentication server 11. In this case, the biological information is transmitted from the terminal 15 to the server 11.

(Second Embodiment)
FIG. 7 is a schematic configuration diagram of a personal authentication device according to the second embodiment of the present invention. The personal authentication device 20 shown in FIG. 7 is functionally equivalent to an integrated function of the personal authentication server 11, the biometric feature DB 12, the biometric feature registration device 14, and the personal authentication terminal 15 in FIG.

  In the present embodiment, the personal authentication device 20 of FIG. 7 will be described as being used for entrance / exit management of a facility such as a building. That is, personal authentication is performed using information on a plurality of types of biometric features, and entry / exit management (unlocking / locking operation) for each room of the facility is performed according to the authentication result. Here, as in the first embodiment, it is assumed that five types of biometric features such as “fingerprint”, “iris”, “face”, “voiceprint”, and “handwriting” can be used.

  That is, the personal authentication device 20 includes a fingerprint sensor 21, an iris camera 22a and an iris illumination 22b, a face camera 23a and a face illumination 23b, a voice print microphone 24, and a handwriting tablet 25 as input units. Yes. Further, a monitor 26 as a display unit, a keyboard 28, and a biological information selection button 27 as a selection input unit are further provided.

  Hereinafter, the flow of personal authentication processing according to the present embodiment will be described separately for registration and authentication. The rough processing flow is substantially the same as in the first embodiment.

<During registration>
At the time of registration, the administrator of the personal authentication device 20 performs a registration operation to register a user. The administrator itself is authenticated by inputting a password using the keyboard 28 or authenticating using biometric information using the personal authentication device 20. After the administrator performs the registration procedure and the user ID input using the keyboard 28, the user inputs a plurality of types of biological information.

  Next, feature information used for authentication is extracted from each input biometric information. The feature extraction method is the same as in the first embodiment. Such biometric information input and feature extraction are performed for all registered users.

  Next, the authentication accuracy is estimated for each combination of feature information extracted from biometric information (including single use of each feature information). The authentication accuracy estimation method is the same as that in the first embodiment. The authentication accuracy estimated here is stored in a storage device (not shown) in the personal authentication device 20 of FIG. 7 as in the biometric feature DB 12 of the first embodiment.

  FIG. 8 is an example of information stored in the storage device and indicating the relationship between the combination of biometric features used for authentication and the authentication accuracy. In the information of FIG. 8, rooms that can be entered are shown as the authentication level together with the authentication accuracy.

<At the time of authentication>
At the time of authentication, a user who wants to authenticate inputs his / her ID using the keyboard 28 and selects biometric information to be input using the biometric information selection button 27. FIG. 9 is an enlarged view of the biological information selection button 27 shown in FIG. When the user presses the selection button 27b corresponding to the biometric information to be selected, the indicator 27a is turned on, and thereby the selected biometric information can be confirmed. In the example of FIG. 9, “iris”, “face”, and “voiceprint” are selected. By making biometric information selectable in this way, for example, if a user who is going to be authenticated happens to be injured by a finger that has registered a fingerprint, other biometric information is removed except for the fingerprint. Can be selected.

  When the biometric information is selected, the personal authentication device 20 refers to the information shown in FIG. 8 stored at the time of registration, obtains the authentication level when using the selected biometric information, and displays it on the monitor 26. And present it to the user. Here, since “iris”, “face”, and “voiceprint” are selected, the information in FIG. 8 indicates that there are four rooms B, C, D, and E that can be entered.

  The user who has confirmed the authentication level on the monitor 26 actually inputs the selected biological information. Here, the user inputs the “iris” information using the iris camera 22a and the iris illumination 22b, inputs the “face” information using the face camera 23a and the face illumination 23b, and further, the voiceprint. “Voiceprint” information is input through the microphone 24. If the authentication level displayed on the monitor 26 is insufficient, the biometric information may be selected again.

  When the biometric information is input, the personal authentication device 20 extracts the feature information of each input biometric information and compares it with the already registered feature information to authenticate whether or not the user is the user. Do.

  When the user is authenticated as the user, the user's operation is controlled according to the authentication level. In this case, the locks of the rooms B, C, D, and E are released.

  Note that each user may select a combination of biometric features notified at the time of registration and most suitable for the user. In this case, the notified combination of biometric features is set in advance in the personal authentication device 20 as a password, and if the selected combination of biometric features and the combination set as the password do not match, authentication is not performed. It is also possible to make it.

  Further, the personal authentication device 20 may limit usable biometric features according to the surrounding environment. For example, when the ambient sound immediately before authentication is measured by the microphone 24 and it is determined that the ambient noise level is high, the “voice print” may be excluded from the biometric feature selection candidates. Similarly, if the brightness measured by the cameras 22a, 23a or the illuminance sensor (not shown) exceeds a predetermined threshold, it is determined that the influence of outside light such as sunlight is large, and the “iris” and “face” are It may be excluded from information selection candidates. In this case, it is possible to make the user confirm the types of biometric features that can be selected by turning on the indicator 27a.

  In addition, information indicating a relationship between a combination of biometric features that can be input with an authentication level may be displayed on a display unit such as the monitor 26. For example, in this embodiment, since the authentication purpose is entry / exit management, information as shown in FIG. 8 may be displayed on the monitor 26 to notify the user of rooms that can be entered. In this case, the authentication accuracy may not be displayed.

  In addition, when the purpose of authentication is to confirm the identity of electronic commerce, the relationship between the combination of biometric features and the upper limit of the commerce as shown in FIG. 10 can be displayed on the monitor 26 to notify the user. It is. Further, when the purpose of authentication is to log in to a PC or the like, the relationship between the combination of biometric features and available commands or sites may be displayed on the monitor 26.

  The display unit may be configured by means other than the monitor 26, for example, an indicator, or the selection input unit may be configured by means other than the selection button 27, such as a touch panel.

  As described above, according to the present embodiment, the same effect as that of the first embodiment can be obtained by the integrated personal authentication device. In addition, the convenience of the user is greatly improved by displaying an authentication level corresponding to the selected combination of biometric features and information indicating the relationship between the combination of biometric features capable of inputting information and the authentication level on the display unit. Can be improved.

  Further, by providing the display unit and the selection input unit according to the present embodiment in the personal authentication terminal 15 as shown in the first embodiment, the convenience of the person to be authenticated is greatly increased as in the present embodiment. Can be improved.

  In each of the above-described embodiments, the above-described five types of biological features are used. However, of course, other biological features such as the retina, vein pattern, palm shape, palm print, finger shape, auricle, and DNA are used. Information may be used, or in addition to biometric information, non-biometric authentication formats such as IC cards and passwords may be used together.

  According to the personal authentication device and method of the present invention, the user can flexibly select biometric information used at the time of authentication according to, for example, the status of his or her own biometric features, the surrounding environment, and the like. Since authentication accuracy based on information is required, it becomes possible to control the operation of the person to be authenticated in accordance with the authentication accuracy, and it is possible to suppress a decrease in authentication performance. It is useful as a technique for performing personal authentication using information, particularly as a technique for performing integrated authentication from a plurality of types of biological information.

It is a figure which shows notionally the technical feature of the personal authentication which concerns on this invention 1 is a schematic configuration diagram of a personal authentication system according to a first embodiment of the present invention. It is a flowchart which shows the flow of the process at the time of registration in the personal authentication method which concerns on the 1st Embodiment of this invention. It is a flowchart which shows the flow of the process at the time of the authentication in the personal authentication method which concerns on the 1st Embodiment of this invention. It is a figure which shows notionally the distribution of the authentication distance of the same persons regarding certain characteristic information, and the distribution of the authentication distance of others. It is an example of the information which shows the relationship between the combination of a biometric feature, and authentication precision. It is an external view of the personal authentication apparatus which concerns on the 2nd Embodiment of this invention. It is an example of the information which shows the relationship between the combination of biometric information and the room which can enter. It is a figure which shows the detail of the biometric information selection button of the personal authentication apparatus shown in FIG. It is an example of the information which shows the relationship between the combination of biometric information and the upper limit amount of electronic commerce.

Explanation of symbols

11 Personal Authentication Server 12 Biometric Database 15 Personal Authentication Terminal 20 Personal Authentication Device 21 Fingerprint Sensor 22a Iris Camera 22b Iris Lighting 23a Facial Camera 23b Facial Lighting 24 Voiceprint Microphone 25 Handwriting Tablet 26 Monitor (Display Unit)
27 Biometric information selection button (selection input section)

Claims (6)

An apparatus for performing personal authentication,
An input unit configured to be able to input information on multiple types of biometric features;
A selection input unit for a user to select a biometric feature for inputting information from the input unit;
Using the combination of biometric features selected by the selection input unit, the authentication accuracy determination for obtaining the authentication accuracy in the authentication is performed by searching a database in which information indicating the relationship between the biometric feature combination and the authentication accuracy is stored in advance. And
A personal authentication device comprising: a display unit that displays an authentication level based on the authentication based on the authentication accuracy determined by the authentication accuracy determination unit. A device for performing personal authentication,
An input unit configured to be able to input information on multiple types of biometric features;
By using a combination of biometric features capable of inputting information from the input unit, a biometric feature capable of inputting information from the input unit is searched by searching a database in which information indicating a relationship between the biometric feature combination and authentication accuracy is stored in advance. An authentication accuracy determination unit for obtaining authentication accuracy for each combination of
Based on the authentication accuracy obtained by the authentication accuracy determination unit, an authentication level determination unit that determines an authentication level for each combination of biometric features that can be input from the input unit;
A personal authentication apparatus, comprising: a display unit that displays information indicating a relationship between a combination of biometric features capable of inputting information from the input unit and an authentication level determined by the authentication level determination unit. In claim 1 or 2,
Depending on the authentication level,
A personal authentication device, wherein a room that can be entered, an upper limit amount of electronic commerce, or an available command or site is set. A method of performing personal authentication using a personal authentication device,
An input step for receiving input of information on a plurality of types of biometric features;
A selection input step for accepting selection by the user of the biometric feature whose information is input in the input step;
Using the combination of biometric features selected in the selection input step, the authentication accuracy determination for obtaining the authentication accuracy in the authentication is performed by searching a database that stores in advance information indicating the relationship between the biometric feature combination and the authentication accuracy. Steps,
A personal authentication method comprising: a display step for displaying an authentication level based on the authentication based on the authentication accuracy determined in the authentication accuracy determination step. A method of performing personal authentication using a personal authentication device,
An input step for receiving input of information on a plurality of types of biometric features;
By using a combination of biometric features in which information can be input in the input step, a biometric feature in which information can be input in the input step is searched by searching a database in which information indicating the relationship between the biometric feature combination and authentication accuracy is stored in advance. Authentication accuracy determination step for obtaining authentication accuracy for each combination of
Based on the authentication accuracy obtained in the authentication accuracy determination step, an authentication level determination step for determining an authentication level for each combination of biometric features capable of inputting information in the input step;
A personal authentication method comprising: a display step for displaying information indicating a relationship between a combination of biometric features into which information can be input in the input step and an authentication level determined in the authentication level determination step. In claim 4 or 5,
Depending on the authentication level,
A personal authentication method characterized by setting a room that can be entered, an upper limit amount of electronic commerce, or an available command or site.

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