Biometric authentication device, biometric authentication method, and biometric authentication program

Abstract

The measurement unit (21) measures biological information of an authentication target by means of a sensor. The authentication information processing unit (22) generates authentication information that differs according to individual living bodies on the basis of the biological information acquired by the measurement unit (21), and determines whether authentication is possible on the basis of whether or not the authentication information satisfies authentication conditions. The physical and psychological state estimation unit (23) generates physical and psychological information for estimating the physical and psychological state of the subject to be authenticated on the basis of the biological information, and estimates the physical and psychological state on the basis of the physical and psychological information. An authentication condition update unit (24) changes the authentication condition on the basis of the mind and body state estimated by the mind and body state estimation unit (23).

Description

Technical Field

[0001] The present disclosure relates to a technology for performing authentication based on biometric information. Background Art

[0002] As devices such as PCs and smartphones become more common, biometric authentication provided by these devices is also becoming increasingly common. PC stands for Personal Computer.

[0003] Many biometric authentication methods are image-based methods, in which biometric information such as face, fingerprint, and iris is used for authentication.

[0004] In recent years, with the widespread use of wearable devices, research and development of biometric authentication methods based on time-series biometric signals has continued to advance. For example, biometric signals such as electrocardiogram (ECG), photoplethysmography (PPG), and electroencephalogram (EEG) are utilized. ECG stands for ElectroCardioGram, PPG stands for PhotoPlethysmoGram, and EEG stands for ElectroEncephaloGram.

[0005] In biometric authentication, technologies for verifying the legitimacy of the authentication target are insufficient. The authentication target is the object being measured by a sensor. Verifying the legitimacy of the authentication target means verifying whether the authentication target is suitable for authentication.

[0006] For example, suppose the person being authenticated wants to operate a device such as driving a car after authentication. In this case, verifying the legitimacy of the person being authenticated means verifying whether the person being authenticated is suitable to operate the device. Specifically, in this case, it is necessary to verify whether the measurement object has not been replaced by someone else after authentication, whether the measurement object is truly a living organism, and whether the subject's health status is appropriate. Verifying whether the measurement object is truly a living organism means verifying whether a forged signal has been input. Verifying whether the subject's health status is appropriate means verifying whether the subject is conscious or intoxicated.

[0007] In particular, signal-based authentication is insufficient for verifying the aforementioned legitimacy compared to image-based authentication. Regarding facial authentication, which is an image-based authentication method, methods have been proposed that can achieve the aforementioned legitimacy verification by combining a camera with other sensors or extracting the necessary information through image processing. Regarding signal-based authentication, Patent Document 1 describes the following: By utilizing the fact that the information used for authentication is a time-series signal, the authentication process is repeated, thereby verifying after authentication whether the measurement object has been replaced by someone else.

[0008] Prior art literature

[0009] Patent Literature

[0010] Patent Document 1: International Publication No. 2021 / 140588 Summary of the Invention

[0011] Problems to be solved by the invention

[0012] When operating a device after authentication, it's necessary not only to verify that the measurement target hasn't been replaced by someone else, but also to verify that the measurement target is truly a living organism and that the target's health status is appropriate. However, conventional signal-based authentication systems haven't performed these verifications, leaving them unable to fully verify the legitimacy of the target. Consequently, the target is authenticated while being deemed unsuitable for the purpose, leaving them in a state where they can operate the device.

[0013] An object of the present disclosure is to enable control so that an authentication target can operate a device in a state more suitable for being an authentication target.

[0014] Means used to solve problems

[0015] The biometric authentication device of the present disclosure comprises:

[0016] a measuring unit that measures biological information of an authentication object using a sensor;

[0017] an authentication information processing unit that generates authentication information that differs for each individual living being based on the biometric information acquired by the measurement unit, and determines whether authentication is possible based on whether the authentication information satisfies authentication conditions;

[0018] a physical and mental state estimating unit that generates physical and mental information for estimating the physical and mental state of the authentication subject based on the biometric information, and estimates the physical and mental state based on the physical and mental information; and

[0019] An authentication condition updating unit changes the authentication condition based on the physical and mental state estimated by the physical and mental state estimating unit.

[0020] Effects of the Invention

[0021] In this disclosure, physical and mental information is generated based on biometric information to estimate the physical and mental state, and authentication conditions are modified based on the estimated physical and mental state. This allows authentication to be determined based on the physical and mental state. As a result, the subject of authentication can be controlled to operate the device in a state more suitable for the authentication recipient. BRIEF DESCRIPTION OF THE DRAWINGS

[0022] Figure 1 This is a structural diagram of the biometric authentication device 10 according to the first embodiment.

[0023] Figure 2 This is an explanatory diagram of information stored in the database of the first embodiment.

[0024] Figure 3 This is an explanatory diagram of information stored in the database of the first embodiment.

[0025] Figure 4 This is an explanatory diagram of the processing of the normal authentication method.

[0026] Figure 5 This is a flowchart showing the flow of processing by the biometric authentication device 10 according to the first embodiment.

[0027] Figure 6 This is an explanatory diagram of physical and mental information when estimating the physical condition according to the first embodiment.

[0028] Figure 7 This is an explanatory diagram of the estimation of the physical and mental state when estimating the physical condition according to the first embodiment.

[0029] Figure 8 This is an explanatory diagram of the mind-body information when estimating the sensor attachment state according to the first embodiment.

[0030] Figure 9 This is an explanatory diagram of the estimation of the physical and mental state when estimating the mounting state of the sensor according to the first embodiment.

[0031] Figure 10 This is a structural diagram of a biometric authentication device 10 according to the second embodiment.

[0032] Figure 11 This is an explanatory diagram of information stored in the database of the second embodiment.

[0033] Figure 12 This is a flowchart showing the flow of processing by the biometric authentication device 10 according to the second embodiment.

[0034] Figure 13This is an explanatory diagram of motion information when a fist-making motion of fingers is requested according to the second embodiment.

[0035] Figure 14 This is an explanatory diagram of motion information when a breathing motion is requested according to the second embodiment.

[0036] Figure 15 This is a structural diagram of a biometric authentication device 10 according to the third embodiment.

[0037] Figure 16 This is an explanatory diagram of information stored in the database of the third embodiment.

[0038] Figure 17 This is a flowchart showing the flow of processing by the biometric authentication device 10 according to the third embodiment.

[0039] Figure 18 This is an explanatory diagram of measurement information when the current amount is reduced according to the third embodiment.

[0040] Figure 19 This is an explanatory diagram of measurement information when the wavelength of the light source is changed in the third embodiment. DETAILED DESCRIPTION

[0041] Implementation method 1.

[0042] ***Structure description***

[0043] Reference Figure 1 , the structure of the biometric authentication device 10 according to the first embodiment will be described.

[0044] The biometric authentication device 10 is a computer. It is a wearable device equipped with sensors capable of acquiring biometric information. The wearable device may be in any form, such as clothing, a watch, a hat, a ring, or glasses. Alternatively, the biometric authentication device 10 may be a mobile device such as a smartphone or tablet. Alternatively, the biometric authentication device 10 may be a device equipped with a camera or other device. The physical appearance and structure of the biometric authentication device 10 are not limited to these.

[0045] The biometric authentication device 10 includes a processor 11, a memory 12, an auxiliary storage device 13, a sensor interface 14, a display interface 15, and a communication interface 16. The processor 11 is connected to other hardware via a signal line and controls the other hardware.

[0046] Processor 11 is an integrated circuit (IC) that performs processing. IC stands for Integrated Circuit. Specifically, processor 11 is a CPU, DSP, or GPU. CPU stands for Central Processing Unit. DSP stands for Digital Signal Processor. GPU stands for Graphics Processing Unit.

[0047] The memory 12 is a storage device that temporarily stores data. Specifically, the memory 12 is an SRAM or a DRAM. SRAM is short for Static Random Access Memory, and DRAM is short for Dynamic Random Access Memory.

[0048] The auxiliary storage device 13 is a storage device that stores data. As a specific example, the auxiliary storage device 13 is an HDD. HDD stands for Hard Disk Drive. Alternatively, the auxiliary storage device 13 may be a removable recording medium such as an SD (registered trademark) memory card, CompactFlash (registered trademark), NAND flash memory, a floppy disk, an optical disk, a high-density disk, a Blu-ray (registered trademark) disk, or a DVD. SD stands for Secure Digital. DVD stands for Digital Versatile Disk.

[0049] The sensor interface 14 is an interface for communicating with the sensor 17. The sensor 17 is a device for acquiring biological information of the user. As a specific example, the sensor interface 14 is a USB port. USB is an abbreviation for Universal Serial Bus.

[0050] exist Figure 1 In FIG. 1 , the biometric authentication device 10 is configured to include the sensor 17 . However, the sensor 17 may be provided outside the biometric authentication device 10 .

[0051] The display interface 15 is an interface for communicating with a display that displays information such as processing results. As a specific example, the display interface 15 is an HDMI (registered trademark) port. HDMI is an abbreviation for High-Definition Multimedia Interface.

[0052] The communication interface 16 is an interface for communicating with an external device. As a specific example, the communication interface 16 is an Ethernet (registered trademark) port or a wireless communication antenna.

[0053] exist Figure 1 In the embodiment, the sensor 17 is connected to the processor 11 via the sensor interface 14. However, it is also possible to provide the sensor 17 outside the biometric authentication device 10 and connect it via wireless communication. In this case, the sensor 17 is connected to the processor 11 via the communication interface 16.

[0054] Sensor 17 acquires biological information (biological signals) in a time series. Specifically, biological information corresponds to biological signals such as ECG, PPG, EEG, electromyography, and electrooculography that can be measured unconsciously by wearable devices, but is not limited to specific signals. In the following description, unless otherwise specified, PPG, which is optically measured based on cardiac or vascular activity, is used as an example.

[0055] The biometric authentication device 10 includes a measuring unit 21, an authentication information processing unit 22, a physical and mental state estimation unit 23, and an authentication condition update unit 24 as functional components. The functions of the functional components of the biometric authentication device 10 are implemented by software.

[0056] The auxiliary storage device 13 stores a program for realizing the functions of each functional component of the biometric authentication device 10. The program is read into the memory 12 by the processor 11 and executed by the processor 11. Thus, the functions of each functional component of the biometric authentication device 10 are realized.

[0057] The memory 12 or the auxiliary storage device 13 realizes a database that stores information obtained from the biological information obtained by the sensor 17. For example, Figure 2 As shown in FIG, in the database, the first authentication information and the second authentication information generated based on the biometric information are stored according to each user and the acquisition date and time. Figure 3 As shown, the database stores the first and second psychophysical information generated based on the biological information for each user and the acquisition date. Figure 2 and Figure 3 The tables shown can also be combined into one table.

[0058] In addition, the above database can also be distributed to the memory 12 and the auxiliary storage device 13. Figure 2 In FIG, data is stored in a table format. However, the database format is not limited to this, and NoSQL can also be used.

[0059] exist Figure 1 , only one processor 11 is shown. However, there may be multiple processors 11, and the multiple processors 11 may cooperate to execute programs that realize various functions.

[0060] Likewise, in Figure 1 , only one sensor 17 is shown. However, there may be multiple sensors 17. For example, the biometric authentication device 10 may include different types of sensors such as a PPG sensor and an ECG sensor (electrode) as the sensor 17, or may include two or more of the same sensor such as a PPG sensor.

[0061] ***Action description***

[0062] Reference Figures 4 to 9 The operation of the biometric authentication device 10 according to the first embodiment will be described.

[0063] The operation process of the biometric authentication device 10 in the first embodiment corresponds to the biometric authentication method in the first embodiment. In addition, the program for realizing the operation of the biometric authentication device 10 in the first embodiment corresponds to the biometric authentication program in the first embodiment.

[0064] The biometric authentication device 10 performs authentication using the periodicity of the biometric signal. At this time, the biometric authentication device 10 considers the subject's physical and mental state to implement biometric authentication including determining whether to continue the authentication state or whether to permit subsequent device operations.

[0065] Reference Figure 4 , explaining the processing of the usual authentication method.

[0066] exist Figure 4 The authentication process includes the registration process and the authentication process.

[0067] During registration, (1) measurements are performed using sensors. (2) Feature quantities are extracted from the measured information. (3) The extracted feature quantities are saved as a template.

[0068] During authentication, (1) measurements are taken using sensors. (2) Feature quantities are extracted from the measured information. (3) The extracted feature quantities are compared with the template stored during registration to determine whether authentication is possible.

[0069] Reference Figure 5 , the processing flow of the biometric authentication device 10 according to the first embodiment is described.

[0070] In the first embodiment, the Figure 4 However, the biometric authentication device 10 is not intended to extend the existing specific authentication method. Figure 4 The processing shown is just an example. Figure 4 The processing at the time of registration shown has been executed in advance.

[0071] (Step S101: Measurement Process)

[0072] The measuring unit 21 constantly measures the biometric information of the authentication target using the sensor 17. Constant measurement means measurement at minute time intervals.

[0073] The processes from steps S102 to S107 are repeatedly executed in parallel with the processes from steps S108 to S111. The processes from steps S108 to S111 are repeatedly executed at observation intervals that are independent of the biological signal cycle. Here, the processes from steps S108 to S111 are repeatedly executed at intervals shorter than the biological signal cycle, such as one-second intervals.

[0074] (Step S102: Period Extraction Process)

[0075] The authentication information processing unit 22 extracts a signal of a specific period of time constituting the biometric signal, which is the biometric information measured in step S101, at a specific timing such as when measurement starts or when a device is operated.

[0076] Specifically, the authentication information processing unit 22 focuses on the periodicity and characteristics of the biometric signal, such as maximum and minimum values, and extracts a waveform that matches or is similar to a specific shape. Alternatively, the authentication information processing unit 22 may extract a signal waveform for a specific period of time, such as one second or one minute.

[0077] (Step S103: Authentication Information Generation Process)

[0078] The authentication information processing unit 22 generates authentication information that is unique to each individual living being based on the signal of the specific cycle extracted in step S102. The authentication information processing unit 22 may use the entire signal of the specific cycle as authentication information, or may extract a portion of the signal of the specific cycle as a feature value and use that feature as authentication information.

[0079] (Step S104: Authentication Information Storage Process)

[0080] The authentication information processing unit 22 processes the authentication information generated in step S103 as follows: Figure 2 Stored in the database as shown.

[0081] (Step S105: Authentication determination process)

[0082] The authentication information processing unit 22 determines whether the authentication information generated in step S103 satisfies the authentication conditions. This determines whether the authentication target can be authenticated. If the authentication information satisfies the authentication conditions, the authentication information processing unit 22 considers the target to be legitimate and performs authentication. On the other hand, if the authentication information does not satisfy the authentication conditions, the authentication information processing unit 22 does not consider the target to be legitimate and does not perform authentication.

[0083] In the first embodiment, the authentication information processing unit 22 compares the template stored in the database with the authentication information generated in step S103. If the difference between the template and the authentication information is within the range specified by the authentication conditions, the authentication information processing unit 22 determines that the authentication conditions are satisfied. On the other hand, if the difference between the template and the authentication information is outside the range specified by the authentication conditions, the authentication information processing unit 22 determines that the authentication conditions are not satisfied.

[0084] If authentication is successful and the device is operated, the authentication information processing unit 22 proceeds to step S106. If authentication is successful and the device is operated, the authentication information processing unit 22 proceeds to step S107. If authentication is unsuccessful, the authentication information processing unit 22 terminates the process. Alternatively, if authentication is unsuccessful, the authentication information processing unit 22 may accept the authentication request again and restart the process from step S101.

[0085] The processing of steps S101 to S105 corresponds to Figure 4 The authentication process shown.

[0086] (Step S106: Device Operation Processing)

[0087] The device operation is performed by the authentication object. If the device operation continues, the process moves to step S107. On the other hand, if the device operation is completed, the process ends.

[0088] (Step S107: Authentication Continues Processing)

[0089] The authentication information processing unit 22 returns the process to step S101 to continue the authentication process.

[0090] (Step S108: Physical and mental information generation process)

[0091] The physical and mental state estimation unit 23 generates physical and mental information for estimating the physical and mental state of the authentication target based on the biometric information measured in step S101. Physical and mental information is information that changes non-periodically (long-term) regardless of the period of the biometric information. Specific examples of physical and mental information will be described later.

[0092] (Step S109: Physical and mental information storage processing)

[0093] The physical and mental state estimation unit 23 generates the physical and mental information generated in step S108 as follows: Figure 3 Stored in the database as shown.

[0094] If the observation time has elapsed after executing step S110, the physical and mental state estimation unit 23 proceeds to step S110. On the other hand, if the observation time has not elapsed after executing step S110, the physical and mental state estimation unit 23 returns to step S101. Whether the observation time has elapsed can also be determined by whether the process of step S109 has been executed a fixed number of times.

[0095] (Step S110: Physical and Mental State Estimation Process)

[0096] The physical and mental state estimation unit 23 estimates the physical and mental state of the authentication subject based on the physical and mental information stored in the database in step S109. A method of estimating the physical and mental state will be described later.

[0097] If the estimated physical and mental state is good, the physical and mental state estimation unit 23 returns the process to step S101. On the other hand, if the estimated physical and mental state is bad, the physical and mental state estimation unit 23 proceeds to step S111.

[0098] (Step S111: Authentication Condition Update Process)

[0099] The authentication condition updating unit 24 changes the authentication condition used in step S105 according to the physical and mental state. Here, since the physical and mental state is poor, the authentication condition updating unit 24 makes the authentication condition stricter.

[0100] Then, the authentication condition updating unit 24 returns the process to step S101.

[0101] A specific example of the physical and mental information generated in step S108 , a method of estimating the physical and mental state in step S110 , and a method of changing the authentication conditions in step S111 will be described.

[0102] Here, two examples (a) and (b) are described. The biometric authentication device 10 selects and uses either (a) or (b) that is appropriate for the biometric information. Alternatively, the biometric authentication device 10 may use (a) and (b) in combination.

[0103] In the two examples (a) and (b), the following situation is assumed: the processing shown in steps S101 to S105 is implemented at the start of measurement or before specific device operation, etc., and when it is determined that the subject is a legitimate person, the authentication state is continued and the measurement is repeated.

[0104] (a) Estimation of physical condition

[0105] In (a), the physical and mental state estimation unit 23 estimates the physical condition of the authentication object as the physical and mental state of the authentication object. In steps S108 to S109, as shown in FIG. Figure 6 As shown, the physical and mental state estimation unit 23 extracts the distance (time) between each cycle, obtained by focusing on the maximum value within one cycle of the biological information, as physical and mental information and stores it. After this process is repeated and the observation time has passed, in step S110, the physical and mental state estimation unit 23 estimates the physical condition of the authentication subject based on the physical and mental information stored in the database.

[0106] In step S110, the physical and mental state estimation unit 23 estimates the physical and mental state of the authentication target based on the physical and mental information generated at each time (i=1, 2, ..., n). Figure 7 As shown in (A), for i = 1, ..., n-1, the mind-body information generated at each time (i = 1, 2, ..., n) is plotted as coordinates. Below, the physical and mental state to be estimated is exemplified by the subject's physical condition, particularly a relaxed state, but the estimation target is not limited to a specific state. Furthermore, while the example of plotting mind-body information as two-dimensional coordinates (i, i+1) is described, this is not limited to a specific dimension.

[0107] like Figure 7 As shown in (B), let the mind-body information generated five times be f1, f2, f3, f4, and f5. In this case, plotting is performed for each i where i = 1, ..., 4. Specifically, when i = 1, the plot is performed with coordinates (f1, f2). When i = 2, the plot is performed with coordinates (f2, f3). When i = 3, the plot is performed with coordinates (f3, f4). When i = 4, the plot is performed with coordinates (f4, f5).

[0108] Then, the physical and mental state estimation unit 23 determines the state of relaxation of the subject by confirming the value of the physical and mental information. For example, as the variance of the physical and mental information, the physical and mental state estimation unit 23 determines the state of relaxation of the subject by the radius of the smallest circle surrounding all the drawn points. For example, if the heart rate increases due to tension, the variance becomes larger. Specifically, since the difference between the first characteristic value and the second characteristic value, the difference between the second characteristic value and the third characteristic value, the difference between the third characteristic value and the fourth characteristic value... become larger, the variance becomes larger. However, if the heart rate is not as high as a certain value, the difference between the characteristic values between the times does not change significantly, and it is considered that the variance becomes smaller. Therefore, a benchmark can also be set so that the state of relaxation is determined taking this into account.

[0109] If the physical and mental state estimation unit 23 estimates that the physical condition is good (OK in step S110), and maintains the authentication condition at the initial condition. On the other hand, if the physical and mental state estimation unit 23 estimates that the physical condition is poor (NG in step S110) when the user is not relaxed, it determines that it may be difficult to continue to maintain the authentication state or difficult to permit device operation, and causes the processing to enter step S111. Then, in step S111, the authentication condition update unit 24 changes the authentication condition to a condition that is stricter than the initial condition. For example, the authentication condition update unit 24 reduces the allowable error, which is the range of the difference between the allowable template and the authentication information. Alternatively, the authentication condition update unit 24 may set the authentication state to end when the device operation cannot be permitted.

[0110] (b) Estimation of the sensor assembly state

[0111] In (b), the physical and mental state estimation unit 23 estimates the assembly state of the sensor of the authentication object as the physical and mental state of the authentication object. Here, the assembly state is the contact state of the sensor. In steps S108 to S109, (1) the physical and mental state estimation unit 23 extracts the distance (time) between each cycle obtained by focusing on the maximum value in one cycle of the biological information as physical and mental information, and stores it. Alternatively, (2) the physical and mental state estimation unit 23 extracts the distance (time) between each cycle as physical and mental information, as in (a). Figure 8 As shown, within a time window larger than one cycle, the moving average within the time window is continuously extracted while shifting by a small amount and stored as physical and mental information. After the process (1) or (2) is repeated and the observation time has passed, in step S110, the physical and mental state estimation unit 23 estimates the subject's assembly state based on the physical and mental information stored in the database.

[0112] In step S110, when the distance between each cycle is used as the physical and mental information as in (a), the physical and mental state estimation unit 23 estimates the physical and mental state of the authentication subject based on the physical and mental information generated at each time (i=1, 2, ..., n). For example, Figure 7 As shown, for i=1, ..., n-1, the mind-body information generated at each time (i=1, 2, ..., n) is plotted as coordinates. The mind-body state estimation unit 23 then determines changes in the sensor's contact state by confirming the values of the mind-body information. For example, the change in state is determined by confirming the variance of the mind-body information. If the variance is large, the measured value is irregular or deviates from the normally measured value, and it is considered that the sensor's contact state may be poor (loosely mounted). Conversely, if the variance is small, the measured value is stable within the normally measured value range, and the sensor's contact state is considered to be good.

[0113] When the moving average within the time window is used as the physical and mental information, the physical and mental state estimation unit 23 Figure 9As shown, a moving average is calculated within each time window, and the waveforms of the moving averages are compared to determine changes in contact state that are unrelated to periodic components such as heartbeat and respiration. At this point, the physical and mental state estimation unit 23 compares the waveforms between each time window by calculating an indicator such as the Euclidean distance. For example, if there are time windows i = 1, ..., n, the physical and mental state estimation unit 23 compares the waveforms between time window i and time window i+1 based on the indicator for each i where i = 1, ..., n-1. Furthermore, the physical and mental state estimation unit 23 is not limited to the Euclidean distance; indicators such as error, correlation coefficient, cosine similarity, Mahalanobis distance, and dynamic time warping can also be used between time windows. If the waveform changes significantly between time windows, the sensor contact state is likely poor (loosely attached). Conversely, if the waveform changes slightly between time windows, the measured value is stable, and the sensor contact state is considered good.

[0114] When the physical and mental state estimation unit 23 estimates that the assembly state of the sensor is good (OK in step S110), the authentication condition is maintained at the initial condition. On the other hand, when the physical and mental state estimation unit 23 estimates that the contact state of the sensor is poor (NG in step S110), the measurement is not performed accurately, and it is determined that it may be difficult to continue to maintain the authentication state or difficult to permit the device operation, so the processing enters step S111. Then, in step S111, the authentication condition update unit 24 changes the authentication condition to a condition that is stricter than the initial condition. For example, the authentication condition update unit 24 reduces the range of the difference between the allowable template and the authentication information, that is, the allowable difference. Alternatively, the authentication condition update unit 24 may set the authentication state to end when the device operation cannot be permitted.

[0115] In the above description, in step S111, the authentication condition updating unit 24 modifies the authentication conditions to stricter conditions when the physical and mental state is poor. However, in step S111, the authentication condition updating unit 24 may also modify the authentication conditions to looser conditions when the physical and mental state is good. Specifically, in example (a), the authentication condition may be modified to looser conditions when the physical state is good, or in example (b), the authentication condition may be modified to looser conditions when the assembly is in good condition.

[0116] In this case, in step S110, if the physical and mental state has changed since the last determination, the physical and mental state estimation unit 23 advances the process to step S111. Then, in step S111, the authentication condition update unit 24 changes the authentication conditions to be more relaxed if the physical and mental state is better than the last time, and changes the authentication conditions to be more stringent if the physical and mental state is worse than the last time.

[0117] In the above description, the authentication condition updating unit 24 changes the authentication condition. However, the authentication condition updating unit 24 may change the authentication information generated in step S103 in addition to or instead of the authentication condition.

[0118] **Effects of Implementation Method 1**

[0119] As described above, the biometric authentication device 10 of Embodiment 1 generates physical and mental information and estimates the physical and mental state of the subject being authenticated. The biometric authentication device 10 then modifies the authentication conditions based on the physical and mental state. This allows authentication to be determined based on the physical and mental state. Specifically, by tightening or loosening the authentication conditions based on the physical and mental state, biometric authentication can be achieved that takes into account changes in biometric signals caused by factors such as the passage of time, health status, and physical movement during device operation. As a result, the subject can be controlled to operate the device in a state more suitable for authentication.

[0120] **Other structures**

[0121] <Variation 1>

[0122] In the first embodiment, each functional component is implemented by software. However, as a modification example 1, each functional component may be implemented by hardware. Regarding this modification example 1, the differences from the first embodiment will be described.

[0123] When each functional component is implemented by hardware, the biometric authentication device 10 includes an electronic circuit instead of the processor 11, memory 12, and auxiliary storage device 13. The electronic circuit is a dedicated circuit that implements the functions of each functional component, memory 12, and auxiliary storage device 13.

[0124] Electronic circuits include single circuits, complex circuits, programmable processors, parallel programmable processors, logic ICs, GAs, ASICs, and FPGAs. GA stands for Gate Array. ASIC stands for Application Specific Integrated Circuit. FPGA stands for Field-Programmable Gate Array.

[0125] Each functional component may be realized by a single electronic circuit, or may be realized by distributing each functional component across a plurality of electronic circuits.

[0126] <Variation 2>

[0127] As a second modification, some of the functional components may be implemented by hardware, and the other functional components may be implemented by software.

[0128] The processor 11, the memory 12, the auxiliary storage device 13, and the electronic circuit are referred to as a processing circuit. That is, the functions of each functional component are realized by the processing circuit.

[0129] Implementation method 2.

[0130] The difference between the second embodiment and the first embodiment is that the authentication target is determined to be a living body based on whether the biometric information generated by a specific action is measured, and the authentication conditions are changed. In the second embodiment, this difference is described, and the description of the same points is omitted.

[0131] ***Structure description***

[0132] Reference Figure 10 , the structure of the biometric authentication device 10 according to the second embodiment is described.

[0133] The biometric authentication device 10 is different from the biometric authentication device 10 in that it includes the operation processing unit 25 as a functional component. Figure 1 The illustrated biometric authentication device 10 is different. The function of the operation processing unit 25 is realized by software or hardware in the same manner as other functional components.

[0134] In addition, if Figure 11 As shown, the database implemented by the memory 12 or the auxiliary storage device 13 stores specific actions and first and second action information generated based on biometric information for each user and acquisition date. Information such as an identifier indicating the action content is stored in the specific action. Figure 11 The table shown can also be used with Figure 2 or Figure 3 At least any of the tables shown are aggregated into one table.

[0135] ***Action description***

[0136] Reference Figures 12 to 14 , the operation of the biometric authentication device 10 according to the second embodiment will be described.

[0137] The operation process of the biometric authentication device 10 in the second embodiment corresponds to the biometric authentication method in the second embodiment. In addition, the program for realizing the operation of the biometric authentication device 10 in the second embodiment corresponds to the biometric authentication program in the second embodiment.

[0138] Reference Figure 12 , the processing flow of the biometric authentication device 10 according to the second embodiment is described.

[0139] The processing of steps S201 to S207 is the same as Figure 5 The processing of steps S101 to S107 is the same as that of steps S208 to S211. The processing of steps S208 to S211 is executed at any timing. The processing of steps S208 to S211 can be executed regularly or at a certain timing.

[0140] (Step S208: Action Request Processing)

[0141] The action processing unit 25 requests the authentication target to perform a specific action. For example, the action processing unit 25 displays a message requesting the specific action on the display via the display interface 15 and causes the biometric authentication device 10 to vibrate. The request method is not limited to this and other methods may be used.

[0142] Specifically, a specific action is a change in posture or rotation of a specific body part, such as a finger or arm. A specific action can also be any change in posture of the entire body, such as lying, sitting, or standing. Furthermore, while the examples herein illustrate actions that can be easily observed from the outside, actions that are not necessarily easily observed from the outside, such as breathing, can also be considered specific actions.

[0143] (Step S209: Action Information Setting Process)

[0144] The action processing unit 25 sets the biometric information measured within the reference time from the request to perform the specific action as the action information. Here, the action processing unit 25 sets the biometric information measured within the reference time as the action information regardless of whether the authentication object actually performs the specific action. The action processing unit 25 stores the action information in Figure 11 The database shown.

[0145] (Step S210: Motion Estimation Process)

[0146] The motion processing unit 25 determines whether the motion information stored in step S209 includes biometric information resulting from a specific motion. If the biometric information resulting from a specific motion is included, the motion processing unit 25 determines that the specific motion has been performed. On the other hand, if the biometric information resulting from a specific motion is not included, the motion processing unit 25 determines that the specific motion has not been performed.

[0147] Then, if the specific action is performed, the action processing unit 25 estimates that the authentication target is a living being with thoughts. If the action processing unit 25 estimates that the authentication target is a living being, the process returns to step S201. On the other hand, if the action processing unit 25 does not estimate that the authentication target is a living being, the process proceeds to step S211.

[0148] (Step S211: Authentication Condition Update Process)

[0149] The authentication condition updating unit 24 changes the authentication condition used in step S205 depending on whether the authentication target is estimated to be a living body. Here, the authentication condition updating unit 24 estimates that the authentication target is not a living body, and therefore tightens the authentication condition.

[0150] Then, the authentication condition updating unit 24 returns the process to step S201.

[0151] exist Figure 12 In place of Figure 5 The processing of step S108 to step S111 is performed, and the processing of step S208 to step S211 is performed. However, it is also possible to Figure 5 In other words, the authentication conditions may be changed based on the physical and mental state, and also based on whether the person is a living being.

[0152] A specific example of the specific action requested in step S208 , the biometric information measured when the specific action is performed, and a method of changing the authentication conditions in step S211 will be described.

[0153] Here, two examples (c) and (d) are described. The biometric authentication device 10 selects and uses either (c) or (d) that is appropriate for the biometric information. Alternatively, the biometric authentication device 10 may use (c) and (d) in combination.

[0154] In the two examples (c) and (d), the following situation is assumed: the processing shown in steps S201 to S205 is implemented at the start of measurement or before specific device operation, etc., and when it is determined that the subject is a legitimate person, the authentication state is continued and the measurement is repeated.

[0155] (c) Fingers clenching into a fist

[0156] In (c), the action processing unit 25 requests the fist-making action of the fingers as a specific action. In step S208, as shown in FIG. Figure 13 As shown, the motion processing unit 25 requests the user to make a fist from an open palm as a specific motion. In step S209, regardless of whether the subject of authentication has performed the requested motion, the motion processing unit 25 stores the biometric information measured in step S201 as motion information in the database. In step S210, the motion processing unit 25 determines whether the motion information stored in the database includes biometric information resulting from the fisting motion of the fingers.

[0157] The action processing unit 25 determines whether a change occurs in the action information. For example, it determines whether a change occurs in the action information. Figure 13 The amplitude changes shown in the figure are biometric information caused by a specific action, such as making a fist. When the fingers are closed, the amplitude of the biometric signal may increase or decrease due to changes in the sensor's contact state, compared to when the fingers are open. Therefore, the amplitude may change with the fist movement.

[0158] Appears in action information Figure 13 If the amplitude changes as shown in the figure, the action processing unit 25 considers that the finger is making a fist and determines that the authentication object is a living body (OK in step S210). Then, the action processing unit 25 maintains the authentication condition at the initial condition. On the other hand, there is no Figure 13 If the amplitude changes as shown, the motion processing unit 25 determines that the fisting action is not being performed and determines that the authentication object may not be a living body (NG in step S210). The motion processing unit 25 then determines that it may be difficult to continue the authentication state or to allow the device operation, and the process proceeds to step S211.

[0159] Then, in step S211, the authentication condition update unit 24 changes the authentication conditions to stricter conditions than the initial conditions. For example, the authentication condition update unit 24 may reduce the permissible difference between the template and the authentication information, i.e., the tolerance. Alternatively, if the authentication condition update unit 24 cannot permit device operation, it may set the authentication status to terminate.

[0160] (d) Breathing movements

[0161] In (d), the motion processing unit 25 requests a deep breath as the specific motion. In step S208, the motion processing unit 25 requests a deep breath as the specific motion. In step S209, regardless of whether the subject of authentication has performed the requested motion, the biometric information measured in step S201 is stored in the database as motion information. In step S210, the motion processing unit 25 determines whether the motion information stored in the database includes biometric information resulting from a deep breath.

[0162] The action processing unit 25 determines whether the action information appears Figure 14 The rise or fall of the baseline shown. The rise or fall of the baseline is biological information that may change due to deep breathing, which is a specific action.

[0163] Appears in action information Figure 14If the baseline shown in FIG2 is raised, the action processing unit 25 considers that a deep breathing action is performed and determines that the authentication object is a living body (OK in step S210). Then, the action processing unit 25 maintains the authentication condition to the initial condition. On the other hand, there is no Figure 14 If the baseline shown in FIG2 is rising, the motion processing unit 25 determines that the deep breathing action is not being performed and determines that the authentication object may not be a living body (NG in step S210). Then, the motion processing unit 25 determines that it may be difficult to continue the authentication state or difficult to permit the device operation, and the process proceeds to step S211.

[0164] Then, in step S211, the authentication condition update unit 24 changes the authentication conditions to stricter conditions than the initial conditions. For example, the authentication condition update unit 24 may reduce the permissible difference between the template and the authentication information, i.e., the tolerance. Alternatively, if the authentication condition update unit 24 cannot permit device operation, it may set the authentication status to terminate.

[0165] **Effects of Implementation Method 2**

[0166] As described above, the biometric authentication device 10 of Embodiment 2, when a specific action is requested and biometric information resulting from the specific action is measured, estimates that the subject being authenticated is a living being. The biometric authentication device 10 then changes the authentication conditions based on whether the subject being authenticated is estimated to be a living being. This allows authentication to be performed while ensuring that the subject being authenticated is a living being with consciousness. In other words, authentication can be performed while ensuring that the subject being authenticated is not an artificial object.

[0167] Implementation method 3.

[0168] The third embodiment differs from the second embodiment in that it determines whether the authentication target is a living body regardless of the authentication target's identity and changes the authentication conditions. In the third embodiment, this difference is described, and description of the same points is omitted.

[0169] ***Structure description***

[0170] Reference Figure 15 , the structure of the biometric authentication device 10 according to the third embodiment will be described.

[0171] Biometric authentication device 10 and Figure 10 The biometric authentication device 10 shown is different in that it includes a measurement condition processing unit 26 as a functional component, instead of the operation processing unit 25. The function of the measurement condition processing unit 26 is realized by software or hardware, similarly to the other functional components.

[0172] In addition, if Figure 16As shown, the database implemented by the memory 12 or the auxiliary storage device 13 stores measurement conditions, first measurement information generated from biometric information, and second measurement information for each user and acquisition date. The measurement conditions include information such as identifiers indicating the measurement conditions. Figure 16 The table shown can also be used with Figure 2 or Figure 3 or Figure 11 At least any of the tables shown are aggregated into one table.

[0173] ***Action description***

[0174] Reference Figures 17 to 19 , the operation of the biometric authentication device 10 according to the third embodiment will be described.

[0175] The operation process of the biometric authentication device 10 in the third embodiment corresponds to the biometric authentication method in the third embodiment. In addition, the program for realizing the operation of the biometric authentication device 10 in the third embodiment corresponds to the biometric authentication program in the third embodiment.

[0176] Reference Figure 17 , the processing flow of the biometric authentication device 10 according to the third embodiment is described.

[0177] The processing from step S301 to step S307 is the same as Figure 12 The processing of steps S201 to S207 is the same as that of steps S201 to S207. The processing of steps S308 to S311 is executed at any timing. The processing of steps S308 to S311 can be executed regularly or at a certain timing.

[0178] (Step S308: Measurement Condition Change Process)

[0179] The measurement condition processing unit 26 changes the measurement conditions of the biological information.

[0180] The measurement conditions are changeable regardless of the authentication subject's intentions. Specific examples of the measurement conditions will be described later.

[0181] (Step S309: Measurement Information Setting Process)

[0182] The measurement condition processing unit 26 sets the biological information measured within the reference time after the measurement condition is changed as the measurement information. The measurement condition processing unit 26 stores the measurement information in Figure 16 The database shown.

[0183] (Step S310: Change Determination Process)

[0184] The measurement condition processing unit 26 determines whether the measurement information stored in step S309 includes biometric information corresponding to the changed measurement conditions. If biometric information corresponding to the changed measurement conditions is included, the measurement condition processing unit 26 estimates that the authentication target is a sentient being.

[0185] If the measurement condition processing unit 26 estimates that the authentication target is a living body, the processing returns to step S301. On the other hand, if the measurement condition processing unit 26 does not estimate that the authentication target is a living body, the processing proceeds to step S311.

[0186] (Step S311: Authentication Condition Update Process)

[0187] The authentication condition updating unit 24 changes the authentication condition used in step S305 depending on whether the authentication target is estimated to be a living body. Here, the authentication condition updating unit 24 estimates that the authentication target is not a living body, and therefore tightens the authentication condition.

[0188] Then, the authentication condition updating unit 24 returns the process to step S301.

[0189] exist Figure 17 In place of Figure 12 The processing of step S208 to step S211 is performed, and the processing of step S308 to step S311 is performed. However, it is also possible to Figure 12 In addition to the processing of steps S208 to S211, the processing of steps S308 to S311 is executed. That is, it is also possible to request a specific action to estimate whether it is a living body and change the measurement conditions to estimate whether it is a living body.

[0190] A specific example of the measurement conditions set in step S308, the biometric information measured when the measurement conditions are changed, and a method of changing the authentication conditions in step S311 will be described.

[0191] Here, two examples (e) and (f) are described. The biometric authentication device 10 selects and uses either (e) or (f) that is appropriate for the biometric information. Alternatively, the biometric authentication device 10 may use (e) and (f) in combination.

[0192] In the two examples (e) and (f), the following situation is assumed: the processing shown in steps S301 to S305 is implemented at the start of measurement or before specific device operation, etc., and when it is determined that the subject is a legitimate person, the authentication state is continued and the measurement is repeated.

[0193] (e) Reduction in current flow

[0194] In (e), the measurement condition processing unit 26 reduces the current amount as one of the measurement conditions. Figure 18 As shown, the measurement condition processing unit 26 reduces the amount of current flowing through the sensor 17, which is one of the measurement conditions. In step S309, the measurement condition processing unit 26 stores the biological information measured in step S301 as measurement information in the database. In step S310, the measurement condition processing unit 26 determines whether the measurement information stored in the database includes biological information in which the amount of current is reduced.

[0195] The measurement condition processing unit 26 determines whether the measurement information contains Figure 18 The amplitude changes shown. Amplitude changes occur because the amount of light emitted by the sensor's light source sometimes changes in response to changes in the current flow, and this is reflected in the biometric information. When the current flow decreases, the amplitude of the biometric signal sometimes decreases.

[0196] Appears in measurement information Figure 18 If the amplitude shown in FIG3 changes, the measurement condition processing unit 26 determines that the authentication object is a biological body (OK in step S310). Then, the measurement condition processing unit 26 maintains the authentication condition at the initial condition. On the other hand, there is no change in the measurement information. Figure 18 If the amplitude changes as shown, the measurement condition processing unit 26 determines that the authentication target may not be a living body (NG in step S310). Then, the measurement condition processing unit 26 determines that it may be difficult to continue the authentication state or to permit the device operation, and advances the process to step S311.

[0197] Then, in step S311, the authentication condition update unit 24 changes the authentication conditions to stricter conditions than the initial conditions. For example, the authentication condition update unit 24 may reduce the permissible difference between the template and the authentication information, i.e., the tolerance. Alternatively, if the authentication condition update unit 24 cannot permit device operation, it may set the authentication status to terminate.

[0198] (f) Change of light source wavelength

[0199] In (f), the measurement condition processing unit 26 changes the wavelength (light color) of the light source as one of the measurement conditions. In step S308, the measurement condition processing unit 26 switches the switch on the hardware equipped with multiple light sources such as LEDs, and sets the light source itself to be used to another light source. LED is the abbreviation of Light-Emitting Diode. The measurement condition processing unit 26 can also change the wavelength based on the use of a light source that can change the wavelength. In step S309, the measurement condition processing unit 26 stores the biological information measured in step S301 as measurement information in the database. In step S310, the measurement condition processing unit 26 determines whether the measurement information stored in the database contains biological information when the wavelength of the light source is changed.

[0200] The measurement condition processing unit 26 determines whether the measurement information contains Figure 19 The decrease in amplitude or disappearance of the inflection point in the waveform is shown. This decrease in amplitude and the disappearance of the inflection point in the waveform are changes in biological information that are sometimes reflected by changes in the wavelength of the light source. When the wavelength of the light source is changed, the amplitude of the biological signal decreases and the inflection point in the waveform disappears. Therefore, by changing the wavelength of the light source, the amplitude decreases. Furthermore, the inflection point in the waveform disappears.

[0201] Appears in measurement information Figure 19 If the amplitude shown in FIG3 decreases or the inflection point in the waveform disappears, the measurement condition processing unit 26 determines that the authentication object is a living body (OK in step S310). Then, the measurement condition processing unit 26 maintains the authentication conditions at the initial conditions. On the other hand, if there is no Figure 19 If the amplitude shown decreases or the inflection point in the waveform disappears, the measurement condition processing unit 26 determines that the authentication target may not be a living body (NG in step S310). The measurement condition processing unit 26 then determines that it may be difficult to maintain the authentication state or to permit device operation, and the process proceeds to step S311.

[0202] Then, in step S311, the authentication condition update unit 24 changes the authentication conditions to stricter conditions than the initial conditions. For example, the authentication condition update unit 24 may reduce the permissible difference between the template and the authentication information, i.e., the tolerance. Alternatively, if the authentication condition update unit 24 cannot permit device operation, it may set the authentication status to terminate.

[0203] **Effects of Implementation Method 3**

[0204] As described above, when the biometric authentication device 10 of Embodiment 3 changes its measurement conditions and measures biometric information corresponding to the changed measurement conditions, it estimates that the subject being authenticated is a living being. The biometric authentication device 10 then changes the authentication conditions based on whether the subject being authenticated is estimated to be a living being. This allows authentication to be performed based on the assurance that the subject is a living being, regardless of the subject's identity. In other words, authentication can be performed based on the assurance that the subject is not an artifact.

[0205] In addition, the “unit” in the above description may be rewritten as “circuit,” “step,” “process,” “process,” or “processing circuit.”

[0206] The above describes the embodiments and modifications of the present disclosure. Several of these embodiments and modifications may be implemented in combination. Furthermore, any one or several of these embodiments and modifications may be implemented in part. Furthermore, the present disclosure is not limited to the above embodiments and modifications, and various modifications may be made as needed.

[0207] Description of Reference Numerals

[0208] 10 Biometric authentication device, 11 processor, 12 memory, 13 auxiliary storage device, 14 sensor interface, 15 display interface, 16 communication interface, 17 sensor, 21 measurement unit, 22 authentication information processing unit, 23 physical and mental state estimation unit, 24 authentication condition updating unit, 25 action processing unit, 26 measurement condition processing unit.

Claims

1. A biometric authentication device, wherein: The biometric authentication device comprises: a measuring unit that measures biological information of an authentication object using a sensor; an authentication information processing unit that generates authentication information that differs for each individual living being based on the biometric information acquired by the measurement unit, and determines whether authentication is possible based on whether the authentication information satisfies authentication conditions; a physical and mental state estimating unit that generates physical and mental information for estimating the physical and mental state of the authentication subject based on the biometric information, and estimates the physical and mental state based on the physical and mental information; as well as An authentication condition updating unit changes the authentication condition based on the physical and mental state estimated by the physical and mental state estimating unit.

2. The biometric authentication device according to claim 1, wherein: The physical and mental state estimating unit generates the physical and mental information at observation intervals, and estimates the physical and mental state based on the physical and mental information generated during an observation time.

3. The biometric authentication device according to claim 2, wherein: The authentication condition updating unit estimates the physical and mental state based on changes in the physical and mental information generated at the observation interval.

4. The biometric authentication device according to any one of claims 1 to 3, wherein: The physical and mental state estimation unit generates information indicating the physical condition of the authentication subject as the physical and mental information.

5. The biometric authentication device according to any one of claims 1 to 3, wherein: The physical and mental state estimation unit generates information indicating a mounting state of the sensor as the physical and mental information.

6. The biometric authentication device according to any one of claims 1 to 5, wherein: The authentication condition updating unit changes the authentication condition according to whether the authentication target is estimated to be a living body.

7. The biometric authentication device according to claim 6, wherein: The biometric authentication device further includes a motion processing unit that estimates that the authentication target is a living being when biometric information due to a specific motion is measured. The authentication condition updating unit changes the authentication condition based on whether the operation processing unit estimates that the authentication target is a living body.

8. The biometric authentication device according to claim 7, wherein: The action processing unit requests the authentication target to perform the specific action, and estimates that the authentication target is a living body when biometric information resulting from the specific action is measured within a reference time from the request to perform the specific action.

9. The biometric authentication device according to any one of claims 6 to 8, wherein: The biometric authentication device further includes a measurement condition processing unit that estimates that the authentication target is a biological person when the measurement condition is changed and biometric information corresponding to the changed measurement condition is measured. The authentication condition updating unit changes the authentication condition based on whether the measurement condition processing unit estimates that the authentication target is a living body.

10. A biometric authentication method, wherein: The computer uses sensors to measure the biological information of the authentication object. The computer generates authentication information that is different for each individual organism based on the biometric information, and determines whether authentication is possible based on whether the authentication information satisfies authentication conditions. The computer generates physical and mental information for estimating the physical and mental state of the authentication subject based on the biometric information, and estimates the physical and mental state based on the physical and mental information. The computer changes the authentication condition according to the physical and mental state.

11. A biometric authentication program, wherein: The biometric authentication program enables the computer to function as a biometric authentication device. The biometric authentication device performs the following processing: Measurement processing, measuring the biometric information of the authentication object through sensors; authentication information processing for generating authentication information that is different for each individual living being based on the biometric information obtained by the measurement processing, and determining whether authentication is possible based on whether the authentication information satisfies authentication conditions; a physical and mental state estimation process for generating physical and mental information for estimating the physical and mental state of the authentication subject based on the biometric information, and estimating the physical and mental state based on the physical and mental information; as well as The authentication condition update process changes the authentication condition based on the physical and mental state estimated by the physical and mental state estimation process.

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