JP2007156870A - System and program for authentication - Google Patents

Abstract

<P>PROBLEM TO BE SOLVED: To provide a system and programs for authentication, which prevent an attempt of illegal authentication in any of client apparatuses by a person who attempts the illegal authentication in the past. <P>SOLUTION: When determining that inputted biological pattern data dose not have a high similarity to normal person detection biological pattern data 12 (S106; NO), the client apparatus 10 transmits the biological pattern data to a server apparatus 20 as biological pattern data of an unauthorized person to be stored (S112). When determining that inputted biological pattern data has a high similarity to suspicious person detection biological pattern data 13 (S104; NO), the client apparatus 10 determines that a suspicious person is detected and starts defense functions, such as report, lock and evidence collection (S114). <P>COPYRIGHT: (C)2007,JPO&INPIT

Description

  The present invention relates to an authentication system for determining whether or not usage restrictions can be released, and an authentication program for realizing on a computer a function for determining whether or not usage restrictions can be released.

  As is well known, it is generally performed that an access restriction is provided for a terminal or an application and the restriction is released by authentication. When a conventional authentication device matches information with each other when the information entered as a user identifier or personal identification information is collated with a regular user identifier or personal identification information stored in advance. Only the above-mentioned access restriction is released.

  Recently, some authentication processing is performed using biometric pattern information such as fingerprints, irises, vein patterns, and face creations instead of user identifiers and password information. In this case, when the information is input as the biometric pattern information, the authentication device uses each characteristic of the normal biometric pattern information stored in advance and the input information based on a well-known pattern recognition technique. The access restriction is canceled only when the amount is obtained, the similarity is calculated from the feature amounts, and the similarity exceeds a threshold value.

JP 2001-092783 A

  By the way, some conventional authentication devices can challenge authentication many times. However, if this type of authentication device performs authentication processing with biometric pattern information, even if the normal biometric pattern information is normally read, even if biometric pattern information whose similarity between feature quantities does not exceed the threshold value Since the similarity may be determined to exceed the threshold due to a malfunction in the reading operation, access may be accidentally canceled while a person trying to use it illegally tries to authenticate many times. was there.

  Also, some conventional authentication devices can challenge authentication as many times as set in advance. In this type of authentication apparatus, the terminal and the application are locked when the authentication is unsuccessful for a set number of times. However, if the lock is released by a regular procedure, the person who tries to use it illegally can try authentication again. There was a problem that the access could be canceled accidentally.

  Furthermore, in a conventional authentication device, the time when authentication is performed is recorded as a log, and when the authentication is unsuccessful, there is an electronic processing that indicates that there was an unsuccessful authentication process. There is a method of notifying an administrator or the like by e-mail or the like. However, since information such as the time accumulated as a log and information related to the authentication result notified to the administrator cannot be used to prevent an attempt to illegally authenticate, Even with a simple log storage function and authentication result notification function, there is still a problem that a re-challenge of authentication by a person who desires unauthorized use cannot be prevented.

  Because of these problems, developers in this technical field have made it possible for multiple authentication devices to share information on people who have attempted unauthorized authentication in the past, and in any authentication device such a person It was proposed that it would be possible to deter the attempt.

  The present invention has been made on the basis of the above-mentioned proposal, and the problem is that any of a plurality of client devices that perform authentication processing separately is connected to a server device via a network. It is intended to allow each client device to share information regarding a person who has attempted unauthorized authentication with the client device, so that any client device can prevent such a person's attempt.

  An authentication system devised to solve the above problem is an authentication system in which a server device and one or more client devices are connected to each other through a network so that they can communicate with each other. Detect one or more dangerous person detection biometric pattern information for detecting a dangerous person who should take defensive measures, and a normal person who can release the access restriction applied to any function in the device A first storage unit for storing one or more normal person detection biometric pattern information for receiving the dangerous person detection biometric pattern information from the server device; A first storage unit stored in the first storage unit; a reading unit for reading a biometric pattern to generate biometric pattern information; and a biometric pattern generated by the reading unit Information and the biometric pattern information generated by the reading unit when the degree of similarity based on the dangerous person detection biometric pattern information in the first storage unit exceeds the first threshold And transmitting the biometric pattern information generated by the reading unit to the server device when the degree of similarity based on the normal memory biometric pattern information in the first storage unit does not exceed the second threshold value And when the degree of similarity based on the biometric pattern information generated by the reading unit and the biometric pattern information for normal person detection in the first storage unit exceeds the second threshold, A restriction release unit for releasing the access restriction for the restricted function, while the server device is a second storage unit for storing biometric pattern information; When biometric pattern information is sent from the client device, a second storage unit that stores the biometric pattern information in the second storage unit, and biometric pattern information in the second storage unit with respect to the biometric pattern information A counting unit that counts the number of other biological pattern information in the second storage unit in which the degree of similarity exceeds a third threshold, and the biological pattern information in which the number counted by the counting unit exceeds a predetermined upper limit Is provided with a distribution unit that distributes the biometric pattern information for dangerous person detection to each of the client devices.

  When configured in this way, in any one of the client devices, the biometric pattern information input by the user through the reading unit indicates that the degree of similarity with respect to the normal pattern biometric pattern information for detecting a normal person does not exceed the second threshold. Accumulated in the device. Further, in the server device, the accumulated biometric pattern information is obtained by counting the number of other biometric pattern information whose degree of similarity with respect to the self exceeds a third threshold value, and the number of biometric pattern information exceeds a predetermined upper limit. The information is distributed to each client device as biological pattern information of the dangerous person. In each client device, the biometric pattern information input by the user through the reading unit is collated with the biometric pattern information for normal person detection, and is also collated with the biometric pattern information for dangerous person detection. The biometric pattern information of the user does not exceed the second threshold for the degree of similarity to the biometric pattern information for normal person detection, and the degree of similarity to the biometric pattern information for dangerous person detection If the threshold value is exceeded, the user is considered a dangerous person, and a defense function for reporting, locking, collecting evidence, etc. is activated and a defensive measure is taken.

  As described above, according to the present invention, the dangerous person detection biometric pattern information distributed from the server device to each client device is used as information on a person who has attempted unauthorized authentication in the past by any client device. It can be shared by the apparatus, but the dangerous person detection biometric pattern information can prevent re-challenge of authentication by a person who desires unauthorized use.

  In addition, an authentication program devised to solve the above-described problem is a computer program that includes one or more dangerous person detection biometric pattern information for detecting a dangerous person who should take defensive measures, Storage means for storing one or more normal person detection biometric pattern information for detecting a normal person whose access restriction imposed on such a function may be released in a storage device, a server via a network When the dangerous person detection biometric pattern information is received from the server device through the communication device connected to the apparatus, the biometric pattern information is read by storing the biometric pattern information stored in the storage device. Acquisition means for acquiring biometric pattern information through a reading device for generating a biometric pattern obtained by the acquisition means Protection means for operating a defense function when the degree of similarity based on information and the dangerous person detection biometric pattern information in the storage device exceeds a first threshold, and biometric pattern information acquired by the acquisition means When the degree of similarity based on the normal person detection biometric pattern information in the storage device does not exceed the second threshold value, the biometric pattern information acquired by the acquisition unit is transmitted to the server device through the communication device. When the degree of similarity based on the biometric pattern information acquired by the acquisition means and the biometric pattern information acquired by the acquisition means and the biometric pattern information for normal person detection in the storage device exceeds the second threshold, It is characterized by functioning as a restriction releasing means for releasing the access restriction for the function to which the access restriction is applied.

  Therefore, according to this authentication program, the computer can be operated as a device that functions in the same manner as the client device in the authentication system of the present invention described above.

  As described above, according to the present invention, when a plurality of client devices that perform authentication processing separately are connected to a server device via a network, authentication is illegally performed by any one of the client devices in the past. The information regarding the person who attempted the authentication can be shared by each client apparatus, and any client apparatus can be prevented from attempting such an attempt.

  EMBODIMENT OF THE INVENTION Below, the form for implementing this invention is demonstrated in detail, referring an accompanying drawing.

≪Configuration≫
First, the hardware configuration and software configuration of the authentication system of this embodiment will be described.

  FIG. 1 is a configuration diagram of an authentication system according to the present embodiment.

  The authentication system of the present embodiment includes one or more client devices 10 and a server device 20, and the devices 10 and 20 are connected to each other via a network N.

  The client device 10 is a device that realizes an authentication function by installing a program group and a data group for controlling whether or not to restrict access to a personal computer.

  FIG. 2 is a configuration diagram of the client device 10.

  A personal computer constituting the client device 10 includes a CPU [Central Processing Unit] 10a, a DRAM [Dynamic Random Access Memory] 10b, a display device 10c such as a liquid crystal display, an input device 10d such as a keyboard and a mouse, a communication adapter 10e, and an MDD. It is equipped with well-known hardware such as [Multi Disk Drive] 10f and HDD [Hard Disk Drive] 10h, and also generates biometric pattern data by reading fingerprints, irises, vein patterns, face creation, etc. A biological pattern reading device 10g is provided. The biometric pattern reading device 10g corresponds to the reading unit described above.

  Among these, the HDD 10 h stores basic software 11. The basic software 11 controls input / output in the display device 10c and the input device 10d, and storage areas (memory elements, CD [Compact Disk], DVD [Digital Versatile Disk], HD [Hard] of the DRAM 10b, MDD 10f, and HDD 10h. Disk] is a software that provides basic functions such as read / write control to a large number of application software.

  Further, the normal person detecting biometric pattern data 12, the dangerous person detecting biometric pattern data 13, the dangerous person information management table 14, the authentication program 15, and the dangerous person information receiving program 16 are installed in the HDD 10h. .

  Of these, the normal person detection biometric pattern data 12 is biometric pattern data used to determine whether or not the user who intends to use the client device 10 is a normal person. Here, the normal person means a person who may release the access restriction. When there are a plurality of legitimate users for the client device 10, a plurality of normal person detection biometric pattern data 12 are installed in advance in the HDD 10h. In addition, since the normal person detection biometric pattern data 12 is recorded in the client device 10, the authentication method of the present embodiment is a so-called client authentication method.

  The dangerous person detection biometric pattern data 13 is biometric pattern data used for determining whether or not the user who intends to use the client device 10 is a dangerous person. Here, the dangerous person is a person who should impose the above access restriction, and also requires a person who needs to take action such as reporting to an organization such as the police or a security company, locking or video shooting. Note that only one dangerous person detection biometric pattern data 13 is not prepared for each dangerous person, but two or more of the same dangerous persons may be prepared. The dangerous person detection biometric pattern data 13 is sent from the server device 20 as described later.

  The HDD 10h that stores the normal person detection biometric pattern data 12 and the dangerous person detection biometric pattern data 13 corresponds to the first storage unit described above, and the client that stores the biometric pattern data 12 and 13 in the HDD 10h. The device 10 corresponds to the storage means described above.

  The dangerous person information management table 14 is a table used for managing the dangerous person detection biometric pattern data 13.

  FIG. 3 is a diagram illustrating an example of the data structure of the dangerous person information management table 14.

  The dangerous person information management table 14 of FIG. 3 has the same number of records as the dangerous person in which the dangerous person detection biometric pattern data 13 is recorded in the HDD 10h. Each record has fields of “dangerous person identifier”, “expiration date”, “data path 1”, “data path 2”,.

  Among these, the “dangerous person identifier” field is a field in which a dangerous person identifier which is identification information assigned to the dangerous person in order to identify the dangerous person from other dangerous persons is recorded. In addition, the “expiration date” field is a field in which an expiration date in which the dangerous person detection biometric pattern data 13 for determining the dangerous person can be used for the dangerous person determination is recorded. The “data path n” field is a field in which path information, which is location information indicating the location of the dangerous person detection biometric pattern data 13 of the dangerous person, is recorded. In the “data path n” field of each record, a field having an n value larger than the number of dangerous person detection biometric pattern data 13 for the dangerous person is blank.

  The authentication program 15 is a program for discriminating a normal person or a dangerous person by using the biometric pattern data 12 and 13 described above. The contents of processing executed by the CPU 10a according to the authentication program 15 will be described later.

  The dangerous person information receiving program 16 is a program for realizing a function of receiving the dangerous person detection biometric pattern data 13 from the server device 20. The contents of the process executed by the CPU 10a according to the dangerous person information receiving program 16 will be described later.

  On the other hand, the server device 20 is a device that realizes the function by installing a program group and a data group for realizing the function of distributing the dangerous person detection biometric pattern data 13 to each client device 10 in a general-purpose computer. It is.

  FIG. 4 is a configuration diagram of the server device 20.

  A general-purpose computer constituting the server device 20 includes well-known hardware such as a CPU 20a, a DRAM 20b, a communication adapter 20c, and a storage unit 20d. Among these, the storage unit 20 d stores basic software 21 that functions in the same manner as the basic software 11 of the client device 10.

  Furthermore, normal person detecting biometric pattern data 22, client information management table 23, unauthorized person biometric pattern data 24, unauthorized person information management table 25, and unauthorized person information receiving program 26 are installed in the storage unit 20d. Yes.

  Among these, the biometric pattern data 22 for normal person detection is the same as that installed in all the client devices 20. That is, the server device 20 possesses all the normal person detection biometric pattern data 22 installed in all the client devices 20.

  The client information management table 23 is a table for storing information related to each client device 10. Specifically, the client information management table 23 is a client identifier that is identification information assigned to each client device 20 in order to identify the client device from other client devices. , The IP [Internet Protocol] address of the device 10, personal information such as the name of the normal person in the device 10, and path information of the normal pattern biometric data 22 for detecting the normal person of the normal person are stored.

  The unauthorized person biometric pattern data 24 is biometric pattern data of an unauthorized person. Here, an unauthorized person refers to a user who has performed authentication procedures described later in an attempt to use each client device 10 and has failed to succeed in authentication for a predetermined number of times. Note that only one unauthorized person biometric pattern data 24 exists for each unauthorized person, and there may be two or more unauthorized persons. The unauthorized person biometric pattern data 24 is sent from the client device 10 as will be described later.

  The storage unit 20d that stores the unauthorized person biometric pattern data 24 corresponds to the second storage unit described above.

  The unauthorized person information management table 25 is a table for storing information related to unauthorized persons.

  FIG. 5 is a diagram showing an example of the data structure of the unauthorized person information management table 25.

  The unauthorized person information management table 25 in FIG. 5 has the same number of records as unauthorized persons. Each record has fields of “illegal person identifier”, “expiration date”, “client identifier”, and “data management”. Among these, the “illegal person identifier” field is a field in which an unauthorized person identifier which is identification information assigned to the unauthorized person in order to identify the unauthorized person from other unauthorized persons is recorded. The “expiration date” field is a field in which an expiration date in which the unauthorized person biometric pattern data 24 of the unauthorized person can be used is recorded. The “client identifier” field is a field in which the client identifier of the client device 10 that has sent the unauthorized person biometric pattern data 24 of the unauthorized person is recorded. The “data management” field is a field in which path information, which is location information indicating the location of the data management table 22a for managing all of the unauthorized person biometric pattern data 24, is recorded.

  Here, the data management table 22a is a table having the same number of records as all the unauthorized person biometric pattern data 24 of the unauthorized person. Each record has fields of “data path”, “acquisition date / time”, and “number of similarities”. The “data path” field is a field in which path information, which is location information indicating the location of each unauthorized person biometric pattern data 24, is recorded. The “acquisition date / time” field is a field in which the date / time when the unauthorized person biometric pattern data 24 is acquired by the client device 10 is recorded. The “similar number” field is a field in which the number of the illegitimate biometric pattern data 24 determined to be similar to the self in the later-described process among the illegitimate biometric pattern data 24 of other illegitimate persons is recorded as the similarity number. .

  The unauthorized person information receiving program 26 is a program for realizing a function of receiving the unauthorized person biometric pattern data 24 from the client device 10. The contents of processing executed by the CPU 20a in accordance with the unauthorized person information receiving program 26 will be described later.

<< Process >>
Next, processing performed in the authentication system of the present embodiment will be described.

<Authentication process>
First, the client device 10 cannot use each application just by turning on the power. That is, access restriction is applied to the application of the client device 10. When an operator who intends to use the client device 10 performs a predetermined operation through the input device 10d, the CPU 10a reads the authentication program 15 and starts an authentication process.

  FIG. 6 shows the flow of this authentication process.

  After starting the authentication process, the CPU 10a first substitutes zero for the variable R (step S101), and waits until the biometric pattern is read by the biometric pattern reading device 10g and biometric pattern data is generated (step S102; NO). The CPU 10a that executes step S102 corresponds to the acquisition unit described above.

  Thereafter, when the biometric pattern data is acquired through the biometric pattern reading device 10g (step S102; YES), the CPU 10a has a high similarity to the biometric pattern data acquired in step S102 from the biometric pattern data 13 for dangerous person detection. (Step S103) is performed to detect the dangerous person detection biometric pattern data 13 having a similarity (the degree of similarity exceeds the first threshold). Here, the similarity is calculated based on a well-known pattern recognition technique. More specifically, after obtaining the feature amounts of the biometric pattern data to be compared, the feature amounts are calculated from each other. It is a calculated value.

  As a result, when the dangerous person detection biometric pattern data 13 having a high degree of similarity (the degree of similarity exceeds the first threshold) with respect to the biometric pattern data acquired in step S102 cannot be detected (step S104; YES). Subsequently, the CPU 10a has a high degree of similarity to the biological pattern data acquired in step S102 from the normal person detection biological pattern data 12 (the degree of similarity exceeds the second threshold value). A process for searching for biometric pattern data for detection is performed (step S105).

  As a result, when the normal pattern biometric pattern data 12 having a high similarity (the degree of similarity exceeds the second threshold) with respect to the biometric pattern data acquired in step S102 cannot be detected (step S106; NO) The CPU 10a stores the biometric pattern data itself acquired in step S102 and the acquisition date and time in the DRAM 10b (step S107), increments the value of the variable R by 1 (step S108), and the value of the variable R is a predetermined upper limit. It is determined whether or not (for example, 3) has been reached (step S109).

  If the value of the variable R has not reached the predetermined upper limit (step S109; NO), the CPU 10a returns to a standby state until the biometric pattern data is input (step S102; NO). As a result, the CPU 10a continues until the input biometric pattern data matches either the dangerous person detection biometric pattern data 13 or the normal person detection biometric pattern data 12, or the value of the variable R reaches the upper limit. Steps S102 to S109 are repeatedly executed as a processing loop.

  In the processing loop of steps S102 to S109, before the value of the variable R reaches the upper limit, the biometric pattern data acquired in step S102 has a high similarity (the degree of similarity exceeds the second threshold). When the normal person detection biometric pattern data 12 is detected (step S106; YES), the CPU 10a performs a process of releasing the access restriction in the client device 10 (step S110), and ends the authentication process according to FIG. To do. The CPU 10a that executes this processing loop and step S110 corresponds to the above-described restriction release unit and restriction release means.

  Further, in the processing loop of steps S102 to S109, when the value of the variable R has reached the upper limit (step S109; YES), the CPU 10a determines that the authentication is unsuccessful because the operator has failed in the authentication. A process for displaying the authentication failure notification screen describing the fact that it has become is performed on the display device 10c (step S111), and a process for transmitting information related to the authentication failure to the server device 20 is performed (step S112).

  Note that the information relating to the authentication failure person is, specifically, several pieces of biometric pattern data stored in the DRAM 10b in step S107 (exactly the same number as the upper limit value of the variable R), acquisition date and time information, and The client identifier of the client device 10 is included. Therefore, the CPU 10a that executes this processing loop and step S112 corresponds to the transmission unit and the transmission unit described above.

  And after performing the process which transmits the information which concerns on the authentication failure person to the server apparatus 20 (step S112), CPU10a deletes the biometric data and acquisition date information which were memorize | stored in DRAM10b from the DRAM10b. (Step S113), the authentication process according to FIG. 6 ends.

  Further, in the processing loop of steps S102 to S109, before the value of the variable R reaches the upper limit, the biometric pattern data acquired in step S102 has a high similarity (the degree of similarity is the first threshold value). When the dangerous person detection biometric pattern data 13 is detected (step S104; NO), the CPU 10a assumes that the operator is a dangerous person and operates the defense function (step S114). 6 is performed on the display device 10c (step S115), and the authentication process shown in FIG. 6 is terminated.

  Note that as one of the processes performed by the defense function, there is a notification process for transmitting the biometric pattern data input in step S102 to the server device 20. Thereby, the biological pattern data of the dangerous person is notified to the operator of the server device 20. Further, the biometric pattern data may be transmitted directly to an organization such as the police or a security company.

  In addition, as one of the processes performed by the defense function, there is a locking process for electronically locking the client device 10. As a result, the client device 10 can be forcibly made unavailable to anyone.

  Further, when a camera device (not shown) is mounted on the client device 10, an evidence collection process may be included as one of the processes performed by the defense function. In this evidence collection process, the CPU 10a captures a dangerous person with the camera device and acquires video data. As a result, not only the biometric pattern data of the dangerous person, but also images and images in which the face, the appearance, the clothes, etc. are reflected can be stored as evidence.

  Therefore, the CPU 10a that executes the processing loop and step S114 corresponds to the above-described defense unit and defense means.

<Injustice information receipt processing>
While the above authentication process is performed by the client device 10, when the server device 20 receives a communication request for sending information related to the authentication failure person based on the above-described step S112, the CPU 20a causes the unauthorized person information receiving program 26 to receive the communication request. To start the illegal person information receiving process.

  7 and 8 are diagrams showing the flow of this unauthorized person information receiving process.

  After starting the unauthorized person information receiving process, the CPU 20a first performs a process of receiving information relating to the authentication failure person (step S201). Specifically, the CPU 20a establishes communication with the client device 10 in response to a communication request from the client device 10, and then receives information on the authentication failure person from the client device 10, and then Block communication.

  Subsequently, the CPU 20a gives some information to the received information related to the authentication failure person, and registers them as unauthorized person information in the unauthorized person information management table 25 (step S202). Information to be added to the information related to the authentication failure person includes a new unauthorized person identifier and an expiration date. Further, a similarity number with an initial value of zero is assigned to each of all the biometric pattern data 24 included in the information related to the authentication failure person (see FIG. 5).

  In addition, CPU20a which performs step S201 and S202 is equivalent to the 2nd storage part mentioned above.

  Then, after registering the unauthorized person information, the CPU 20a performs a process of deleting a record whose expiration date has passed from the unauthorized person information management table 25 (step S203), and the following first to third processing loops L1 Perform ~ L3.

  In the first processing loop L1, the CPU 20a performs the second processing for each of all the records (old fraudulent information) other than the record (new fraudulent information) newly registered in the fraudulent information management table 25 in step S202. A processing loop L2 and steps S221 to S229 are performed.

  In the second processing loop L2, the CPU 20a executes the third processing loop L3 for each of all the biometric pattern data 24 included in the old illegal person information to be processed.

  In the third processing loop L3, the CPU 20a executes steps S211 and S212 for each of all the biological pattern data 24 included in the new unauthorized person information.

  In step S211, the CPU 20a determines that the biological pattern data to be processed in the second processing loop L2 (biological pattern data of the old unauthorized person information) is the biological pattern data to be processed in the third processing loop L3 (new unauthorized person information). Whether or not it has a high degree of similarity (the degree of similarity exceeds the third threshold value).

  Then, when the processing target biological pattern data does not have a high degree of similarity (the degree of similarity does not exceed the third threshold value) (step S211; NO), the CPU 20a does nothing and sets the processing target. When the biometric pattern data has a high degree of similarity (the degree of similarity exceeds the third threshold) (step S211; YES), the biometric pattern data to be processed in the second processing loop L2 (old) The value of the “number of similarities” field of the biometric pattern data of the unauthorized person information) is incremented by 1 (step S212).

  The CPU 20a executes the second and third processing loops L2 and L3, thereby performing the first processing loop for all the biometric pattern data 24 related to the record newly registered in the unauthorized person information management table 25 in step S202. The similarity with all the biometric pattern data 24 of the old unauthorized person information to be processed in L1 is determined.

  After the execution of the first and second processing loops L2 and L3, the CPU 20a has a predetermined number of similarities among the biometric pattern data 24 related to the old unauthorized person information to be processed in the first processing loop L1. The biometric pattern data 24 that exceeds the upper limit is searched (step S221).

  When the biometric pattern data 24 whose similarity number exceeds the predetermined upper limit is not detected from the biometric pattern data 24 related to the old unauthorized person information to be processed (step S222; NO), the CPU 20a performs this process. The process for the target old unauthorized person information is terminated.

  On the other hand, when the biometric pattern data 24 in which the number of similarities exceeds a predetermined upper limit is detected from the biometric pattern data 24 related to the old unauthorized person information to be processed (step S222; YES), the CPU 20a has the number of similarities. The number of biometric pattern data 24 exceeding the predetermined upper limit is counted (step S223). In addition, CPU20a which performs this step S223 and step S211 and S212 is equivalent to the counting part mentioned above.

  After the counting, the CPU 20a determines whether or not the number exceeds a predetermined upper limit (step S224).

  If the number of the biometric pattern data 24 whose similarity number exceeds the predetermined upper limit does not exceed the predetermined upper limit (step S224; NO), the CPU 20a performs the process for the processing target old unauthorized person information. finish.

  On the other hand, if the number of biometric data whose number of similarities exceeds a predetermined upper limit exceeds the predetermined upper limit (step S224; YES), the CPU 20a notifies the unauthorized person related to the processing target old unauthorized person information or the like. Therefore, a new dangerous person identifier and expiration date information are generated (step S225).

  Thereafter, the CPU 20a searches the normal pattern biometric pattern data 22 using the biometric pattern data having the number of similarities exceeding a predetermined upper limit as a search condition (step S227), and if it can be detected (step S227; YES), A process of transmitting the dangerous person information to all the client apparatuses 10 other than the client apparatus 10 using the normal person detecting biometric pattern data 22 is performed (step S228), and when it cannot be detected (step S227; NO) Then, the process of transmitting the dangerous person information to all the client devices 10 is performed (step S229). Here, the dangerous person information includes the biological pattern data 24 in which the number of similarities exceeds a predetermined upper limit among the biological pattern data 24 related to the old fraudulent information to be processed, the dangerous person identifier generated in step S225, and the valid person information. The deadline information is included. The CPU 20a that executes steps S224 to S229 corresponds to the distribution unit described above.

  The CPU 20a performs the second and third processing loops L2 and L3 and steps S221 to S229 as described above for each of the old fraudulent information registered in the past in the fraudulent information management table 25. What should be dangerous person information is extracted from the unauthorized person information, and the extracted dangerous person information is distributed to the client device 10.

  Then, after performing the second and third processing loops L2 and L3 and steps S221 to S229 for all the old fraudulent information, the CPU 20a leaves the first processing loop L1, and FIG. 7 and FIG. The unauthorized person information receiving process is terminated.

<Dangerous person information receipt processing>
While the server apparatus 20 performs the unauthorized person information receiving process described above, in the client apparatus 10, when there is a communication request for sending dangerous person information based on the above-described step S228 or S229, the CPU 10a receives the dangerous person information. The program 16 is read and the dangerous person information receiving process is started.

  FIG. 9 is a diagram showing the flow of this dangerous person information receiving process.

  After starting the dangerous person information receiving process, the CPU 10a first performs a process of receiving the dangerous person information (step S301). Specifically, the CPU 10a establishes communication with the server device 20 in response to a communication request from the server device 20, receives dangerous person information from the server device 20, and then blocks communication. To do.

  Subsequently, the CPU 20a registers the received dangerous person information in the dangerous person information management table 14 (step S302), and performs a process of deleting a record whose expiration date has passed from the dangerous person information management table 14 ( Step S303), the dangerous person information receiving process according to FIG.

  The CPU 10a that executes steps S301 and S302 corresponds to the first storage unit and the storage unit described above.

  Next, the operation and effect of the authentication system of this embodiment will be described.

  In the authentication system according to the present embodiment, when a user tries to use a client device to which access is restricted, when the biometric pattern reading device 10g of the client device 10 reads his / her own biometric pattern, the reading is performed. First, it is determined whether or not the biological pattern is a biological pattern that should be that of a dangerous person (step S104).

  If it is not determined that the biological pattern is that of a dangerous person (step S104; YES), it is subsequently determined whether or not the biological pattern is a biological pattern that may be that of a normal person ( Step S106).

  If it is determined that the biometric pattern is that of a normal person (step S106; YES), the user receives the release of the access restriction and starts using the client device 10 and the application therein. It becomes possible (step S110).

  Conversely, if it is determined that the biological pattern is not that of a normal person (step S106; NO), the biological pattern reading device 10g is read again. If it is not determined that the user's biometric pattern is that of a normal person even after the specified number of repetitions (step S106; NO, S109; YES), the user's biometric pattern is stored in the server device 20 as that of an unauthorized person. (Registered) (Steps S112, S201, S202).

  Then, if the user's biometric pattern is once registered in the server device 20 as an unauthorized person, then the authentication procedure fails many times in the same client device 10 or another client device 10. When the number of failures exceeds the upper limit of step S224, his / her biometric pattern is distributed to each client device 20 as a dangerous person (step SS222; YES, S224; YES, S228, S229).

  In this way, the user whose biometric pattern is distributed to each client device 10 as a dangerous person can not remove the access restriction regardless of which client device 10 performs the authentication procedure thereafter. Or, notification, locking, or video shooting will occur (step S104; NO, S114). However, in order to let the user know that such a measure has been taken (step S115), attempts to illegally perform the authentication procedure are psychologically suppressed.

  Therefore, according to the authentication system of the present embodiment, the dangerous person detection biometric pattern data 13 distributed from the server device 20 to each client device 10 has been illegally authenticated by any one of the client devices 10 in the past. As the information on the information, each client device 10 can share the information, and the dangerous person detection biometric pattern data 13 can prevent re-challenge of authentication by a person who desires unauthorized use.

  In the authentication system of this embodiment, once the authentication procedure is unsuccessful, the user is not authorized as an unauthorized person, but until the user fails several times. Is not recognized as an unauthorized person (step S109). In this way, even if the user erroneously inputs his / her biometric pattern, the user is not immediately recognized as an unauthorized person. In addition, by not limiting the number of times that the authentication procedure can be challenged, the possibility of accidental successful authentication is reduced.

  Further, in the authentication system of the present embodiment, an expiration date is provided for the unauthorized person information (FIGS. 3 and 5, steps S202 and S225). This is to prevent the person from being recognized as a dangerous person when the authentication procedure fails little by little over a long period of time.

  Further, in the authentication system of the present embodiment, when the biometric pattern data 24 related to the dangerous person information is the normal person detected biometric pattern data 22 of any client apparatus 10, the client apparatus 10 includes the dangerous person information. Is not sent (step S227; YES, S228). This is because the normal person is a dangerous person in the client device 10 that uses the normal person detection biological pattern 22 having a high similarity to the biological pattern data 24 related to the dangerous person information for normal person discrimination. This is to prevent judgment. As a result, a person who is normal only in a certain client device 10 is treated as a person who should release the access restriction in that client device 10 even if the other client device 10 illegally tries an authentication procedure. On the other hand, the other client devices 10 are treated as persons who should be excluded as dangerous persons because they are not normal persons.

Configuration diagram of authentication system of this embodiment Configuration diagram of client device The figure which shows an example of the data structure of a dangerous person information management table Server device configuration diagram The figure which shows an example of the data structure of an unauthorized person information management table Diagram showing the flow of authentication processing Diagram showing the flow of unauthorized person information receiving process Diagram showing the flow of unauthorized person information receiving process Diagram showing the flow of dangerous person information receiving process

Explanation of symbols

10 Client device 10a CPU
12 Biometric pattern data for normal person detection 13 Biometric pattern data for detection of dangerous person 14 Dangerous person information management table 15 Authentication program 16 Dangerous person information receiving program 20 Server device 20a CPU
22 Biometric pattern data for normal person detection 23 Client information management table 24 Unauthorized person biometric pattern data 25 Unauthorized person information management table 26 Unauthorized person information receiving program

Claims (3)

An authentication system in which a server device and one or more client devices are communicatively connected to each other via a network,
Each of the client devices is
One or more dangerous person detection biometric pattern information for detecting a dangerous person who should take defensive measures, and a normal person who may release an access restriction applied to any function in the device A first storage unit for storing one or more normal person biometric pattern information for detecting,
A first storage unit that stores the dangerous person detection biometric pattern information in the first storage unit when the dangerous person detection biometric pattern information is sent from the server device;
A reading unit for reading the biometric pattern and generating biometric pattern information;
A defensive unit that activates a defensive function when the degree of similarity based on the biometric pattern information generated by the reading unit and the biometric pattern information for dangerous person detection in the first storage unit exceeds a first threshold;
The biometric pattern generated by the reading unit when the degree of similarity based on the biometric pattern information generated by the reading unit and the normal pattern biometric pattern information in the first storage unit does not exceed the second threshold value A transmission unit for transmitting information to the server device; and
When the degree of similarity based on the biometric pattern information generated by the reading unit and the biometric pattern information for normal person detection in the first storage unit exceeds the second threshold, access restriction in the device is applied. It has a restriction release part that releases the access restriction for the function
The server device is
A second storage unit for storing biological pattern information;
When biometric pattern information is sent from the client device, a second storage unit that stores the biometric pattern information in the second storage unit,
For each of the biometric pattern information in the second storage unit, a counting unit that counts the number of other biometric pattern information in the second storage unit whose degree of similarity with respect to the biometric pattern information exceeds a third threshold value, as well as,
An authentication system comprising: a distribution unit that distributes biometric pattern information whose number counted by the counting unit exceeds a predetermined upper limit to each client device as biometric pattern information for dangerous person detection. Computer
One or more dangerous person detection biometric pattern information for detecting a dangerous person who should take defensive measures, and a normal person who may release an access restriction applied to any function in the computer Storage means for storing one or more normal person detection biometric pattern information for storage in a storage device,
Storage means for storing the dangerous person detection biometric pattern information in the storage device when the dangerous person detecting biometric pattern information is received from the server apparatus through the communication device connected to the server apparatus via the network,
An acquisition means for acquiring biological pattern information through a reading device for reading the biological pattern and generating biological pattern information;
Defensive means for operating a defensive function when the degree of similarity based on the biometric pattern information obtained by the obtaining means and the dangerous person detection biometric pattern information in the storage device exceeds a first threshold;
The biometric pattern information acquired by the acquisition means when the degree of similarity based on the biometric pattern information acquired by the acquisition means and the biometric pattern information for normal person detection in the storage device does not exceed the second threshold value Transmitting means for transmitting to the server device through the communication device, and
When the degree of similarity based on the biometric pattern information acquired by the acquisition means and the biometric pattern information for normal person detection in the storage device exceeds the second threshold, access restriction in the computer is applied. An authentication program that functions as a restriction releasing means for releasing the access restriction for a function that exists. The transmitting unit continuously performs the determination that the degree of similarity based on the biometric pattern information acquired by the acquiring unit and the biometric pattern information for normal person detection does not exceed the second threshold value a predetermined number of times. 3. The authentication program according to claim 2, wherein only when the biometric pattern information acquired by the acquisition unit is transmitted to the server device through the communication device.