Information processing system, information processing method, and recording medium

Abstract

An information processing system (10) comprises: an information acquisition means (110) for acquiring authentication history information indicating the history of an authentication process for comparing a target image with a registered image; an abnormality detection means (120) for detecting an abnormality in the authentication process on the basis of the authentication history information; a cause classification means (130) for, upon detection of the abnormality, classifying a cause of the abnormality by using the authentication history information; and a cause notification means (140) for notifying the classified cause of the abnormality. According to the information processing system, when an abnormality occurs in the authentication process, it is possible to notify the cause of the abnormality appropriately.

Description

[Technical Field]

[0001] The present disclosure relates to the technical fields of an information processing system, an information processing method, and a recording medium. [Background technology]

[0002] Known systems of this type detect abnormalities in authentication processing (for example, situations where authentication has not been performed correctly). For example, Patent Document 1 discloses detecting abnormalities by checking the continuity of location-time information. Patent Document 2 discloses detecting abnormalities by using both the location of the authentication device and the location information of the subject. Patent Document 3 discloses detecting abnormalities by checking whether the movement history at the gate meets predetermined conditions.

[0003] As another related technique, for example, Patent Document 4 discloses a technique for detecting impersonation, peeping, etc., using a face identification result that uses feature amounts of a face image. [Prior art documents] [Patent documents]

[0004] [Patent Document 1] Japanese Patent Application Laid-Open No. 2006-331048 [Patent Document 2] Japanese Patent Application Laid-Open No. 2002-117377 [Patent Document 3] Japanese Patent Application Laid-Open No. 2011-002918 [Patent Document 4] Japanese Patent Publication No. 2022-031747 Summary of the Invention [Problem to be solved by the invention]

[0005] This disclosure aims to improve upon the techniques disclosed in the prior art documents. [Means for solving the problem]

[0006] One aspect of the information processing system disclosed herein includes an information acquisition means for acquiring authentication history information indicating the history of authentication processing for comparing a target image with a registered image, an abnormality detection means for detecting an abnormality in the authentication processing based on the authentication history information, a cause classification means for classifying the cause of the abnormality using the authentication history information when the abnormality is detected, and a cause notification means for notifying the classified cause of the abnormality.

[0007] One aspect of the information processing method disclosed herein is to use at least one computer to obtain authentication history information indicating the history of an authentication process that compares a target image with a registered image, detect an abnormality in the authentication process based on the authentication history information, and, if an abnormality is detected, classify the cause of the abnormality using the authentication history information and notify the classified cause of the abnormality.

[0008] One aspect of the recording medium of this disclosure is a computer program recorded on at least one computer that causes the computer to execute an information processing method, which includes acquiring authentication history information indicating the history of an authentication process that compares a target image with a registered image, detecting an abnormality in the authentication process based on the authentication history information, and, if an abnormality is detected, classifying the cause of the abnormality using the authentication history information and notifying the user of the classified cause of the abnormality. [Brief explanation of the drawings]

[0009] [Figure 1] 1 is a block diagram showing a hardware configuration of an information processing system according to a first embodiment. [Figure 2] 1 is a block diagram showing a functional configuration of an information processing system according to a first embodiment. [Figure 3] 4 is a flowchart showing the flow of operations of the information processing system according to the first embodiment. [Figure 4] 10 is a flowchart showing the flow of a cause classification operation by the information processing system according to the second embodiment. [Figure 5]11 is a flowchart showing the flow of a cause classification operation by the information processing system according to the third embodiment. [Figure 6] 10 is a flowchart showing the flow of a cause classification operation performed by the information processing system according to the fourth embodiment. [Figure 7] 13 is a flowchart showing the flow of a cause classification operation performed by the information processing system according to the fifth embodiment. [Figure 8] 13 is a flowchart showing the flow of a cause classification operation by the information processing system according to the sixth embodiment. [Figure 9] 13 is a flowchart showing the flow of operations of the information processing system according to the seventh embodiment. DETAILED DESCRIPTION OF THE INVENTION

[0010] Hereinafter, embodiments of an information processing system, an information processing method, and a recording medium will be described with reference to the drawings.

[0011] First Embodiment An information processing system according to a first embodiment will be described with reference to FIGS.

[0012] (Hardware configuration) First, the hardware configuration of the information processing system according to the first embodiment will be described with reference to Fig. 1. Fig. 1 is a block diagram showing the hardware configuration of the information processing system according to the first embodiment.

[0013] 1, an information processing system 10 according to the first embodiment includes a processor 11, a RAM (Random Access Memory) 12, a ROM (Read Only Memory) 13, and a storage device 14. The information processing system 10 may further include an input device 15 and an output device 16. The processor 11, RAM 12, ROM 13, storage device 14, input device 15, and output device 16 are connected via a data bus 17.

[0014] The processor 11 loads a computer program. For example, the processor 11 is configured to load a computer program stored in at least one of the RAM 12, the ROM 13, and the storage device 14. Alternatively, the processor 11 may load a computer program stored in a computer-readable storage medium using a storage medium reading device (not shown). The processor 11 may acquire (i.e., load) the computer program from a device (not shown) located outside the information processing system 10 via a network interface. The processor 11 controls the RAM 12, the storage device 14, the input device 15, and the output device 16 by executing the loaded computer program. In particular, in this embodiment, when the processor 11 executes the loaded computer program, a functional block for classifying and notifying the above causes in the authentication process is realized within the processor 11. In other words, the processor 11 may function as a controller that executes each control in the information processing system 10.

[0015] The processor 11 may be configured as, for example, a central processing unit (CPU), a graphics processing unit (GPU), a field-programmable gate array (FPGA), a demand-side platform (DSP), or an application-specific integrated circuit (ASIC). The processor 11 may be configured as one of these, or may be configured to use multiple processors in parallel.

[0016] The RAM 12 temporarily stores computer programs executed by the processor 11. The RAM 12 temporarily stores data that the processor 11 temporarily uses while the processor 11 is executing the computer programs. The RAM 12 may be, for example, a dynamic random access memory (DRAM) or a static random access memory (SRAM). Alternatively, other types of volatile memory may be used instead of the RAM 12.

[0017] The ROM 13 stores computer programs executed by the processor 11. The ROM 13 may also store fixed data. The ROM 13 may be, for example, a P-ROM (Programmable Read Only Memory) or an EPROM (Erasable Read Only Memory). Alternatively, other types of non-volatile memory may be used instead of the ROM 13.

[0018] The storage device 14 stores data that is to be saved long-term by the information processing system 10. The storage device 14 may operate as a temporary storage device for the processor 11. The storage device 14 may include, for example, at least one of a hard disk device, a magneto-optical disk device, an SSD (Solid State Drive), and a disk array device.

[0019] The input device 15 is a device that receives input instructions from a user of the information processing system 10. The input device 15 may include, for example, at least one of a keyboard, a mouse, and a touch panel. The input device 15 may be configured as a mobile terminal such as a smartphone or a tablet. The input device 15 may also be, for example, a device that includes a microphone and is capable of voice input.

[0020] The output device 16 is a device that outputs information related to the information processing system 10 to the outside. For example, the output device 16 may be a display device (e.g., a display) that can display information related to the information processing system 10. The output device 16 may also be a speaker or the like that can output information related to the information processing system 10 as audio. The output device 16 may be configured as a mobile terminal such as a smartphone or a tablet. The output device 16 may also be a device that outputs information in a format other than an image. For example, the output device 16 may be a speaker that outputs information related to the information processing system 10 as audio.

[0021] 1 shows an example of information processing system 10 including a plurality of devices, but all or some of the functions may be realized by a single device (information processing device). In this case, the information processing device may be configured to include only processor 11, RAM 12, and ROM 13 described above, and the other components (i.e., storage device 14, input device 15, output device 16) may be provided by an external device connected to the information processing device. Furthermore, the information processing device may have some of its calculation functions realized by an external device (e.g., an external server, a cloud, etc.).

[0022] (Functional configuration) Next, the functional configuration of the information processing system 10 according to the first embodiment will be described with reference to Fig. 2. Fig. 2 is a block diagram showing the functional configuration of the information processing system according to the first embodiment.

[0023] The information processing system 10 according to the first embodiment is configured to classify causes of abnormalities in authentication processing and notify the user of the classified causes. In the authentication processing according to this embodiment, a target image (i.e., an image that is the target of the authentication processing) is compared with a registered image (a pre-registered image). The authentication processing is not particularly limited, and may be, for example, biometric authentication in which biometric information is extracted from the target image and compared. Specifically, the authentication processing may be face authentication in which a face image is compared, or other authentication in which an iris image or a fingerprint image is compared.

[0024] 2, the information processing system 10 according to the first embodiment is configured to include, as components for realizing its functions, a history information acquisition unit 110, an abnormality detection unit 120, an abnormality cause classification unit 130, and a cause notification unit 140. Each of the history information acquisition unit 110, the abnormality detection unit 120, the abnormality cause classification unit 130, and the cause notification unit 140 may be a processing block realized by, for example, the above-mentioned processor 11 (see FIG. 1).

[0025] The history information acquisition unit 110 is configured to be able to acquire authentication history information indicating the history of authentication processing. The history information acquisition unit 110 may acquire authentication history information each time authentication processing is executed, or may acquire accumulated authentication history information collectively. The authentication history information may include various information related to the authentication processing. For example, the authentication history information may include information indicating the result of the authentication processing (i.e., whether authentication was successful or not), information related to the images used in the authentication processing (i.e., the target image and registered images), information related to parameters (e.g., matching scores) and thresholds used to determine the authentication processing, information related to the authentication target, and information related to the authentication position and authentication time. The authentication history information acquired by the history information acquisition unit 110 is configured to be output to each of the anomaly detection unit 120 and the anomaly cause classification unit 130.

[0026] The anomaly detection unit 120 is configured to detect an anomaly in the authentication process based on the authentication history information acquired by the history information acquisition unit 110. Here, the term "anomaly" refers to a state in which the authentication process is not performed normally, and various anomalies are assumed. For example, the anomaly detection unit 120 may detect, as an anomaly, a failure in authentication of a registered user (i.e., a false rejection). Alternatively, the anomaly detection unit 120 may detect, as an anomaly, a successful authentication of an unregistered user (i.e., a false accept). Alternatively, the anomaly detection unit 120 may detect, as an anomaly, a situation in which a registered user is authenticated as a different user. Alternatively, the anomaly detection unit 120 may detect, as an anomaly, a situation in which normal authentication cannot be performed due to a defect in the image to be compared. Alternatively, the anomaly detection unit 120 may detect, as an anomaly, a situation in which the authentication target is a suspicious individual. The detection result by the anomaly detection unit 120 is configured to be output to the anomaly cause classification unit 130.

[0027] The anomaly cause classification unit 130 is configured to be able to classify the cause of an anomaly detected by the anomaly detection unit 120. The anomaly cause classification unit 130 classifies the cause of an anomaly in the authentication process using the authentication history information acquired by the history information acquisition unit 110. The anomaly cause classification unit 130 may classify the cause of an anomaly by determining to which of a plurality of pre-prepared candidate classifications the detected anomaly falls. The operation of the anomaly cause classification unit 130 to classify the cause of an anomaly will be described in detail in another embodiment described later. Information regarding the cause of an anomaly classified by the anomaly cause classification unit 130 is configured to be output to the cause notification unit 140.

[0028] The cause notification unit 140 is configured to be able to notify the cause of the abnormality classified by the abnormality cause classification unit 130. The cause notification unit 140 may notify, for example, the subject of authentication processing, a monitor, a system administrator, or the like, of the cause of the abnormality. The cause notification unit 140 may notify, for example, the cause of the abnormality via the output device 16 described above. For example, the cause notification unit 140 may display an image or video indicating the cause of the abnormality via a display. Alternatively, the cause notification unit 140 may output a sound indicating the cause of the abnormality via a speaker.

[0029] (Operation flow) Next, the overall flow of operations performed by the information processing system 10 according to the first embodiment will be described with reference to Fig. 3. Fig. 3 is a flowchart showing the flow of operations performed by the information processing system according to the first embodiment.

[0030] 3, when the operation of the information processing system 10 according to the first embodiment starts, the history information acquisition unit 110 first acquires authentication history information (step S101). Then, the anomaly detection unit 120 detects an anomaly in the authentication process based on the authentication history information acquired by the history information acquisition unit 110 (step S102).

[0031] If no abnormality is detected (step S102: NO), the subsequent processes are omitted and the series of operations ends. On the other hand, if an abnormality is detected (step S102: YES), the cause classification unit 130 executes a process of classifying the cause of the abnormality using the authentication history information acquired by the history information acquisition unit 110 (step S103).

[0032] The cause classification unit 130 identifies the cause of the abnormality from the processing result of step S103 (step S104). Then, the cause notification unit 140 notifies the cause of the abnormality identified by the cause classification unit 130 (step S105). Note that the cause notification unit 140 may also notify measures to improve the cause of the abnormality together with the cause of the abnormality.

[0033] (Technical Effects) Next, the technical effects obtained by the information processing system 10 according to the first embodiment will be described.

[0034] As described with reference to Figures 1 to 3, in the information processing system 10 according to the first embodiment, when an abnormality occurs in the authentication process, the cause of the abnormality is classified and the classified cause is notified. In this way, it is possible to appropriately notify the cause of the abnormality in the authentication process. Therefore, it becomes possible to appropriately perform corrective processing for the abnormality, for example.

[0035] Second Embodiment An information processing system 10 according to the second embodiment will be described with reference to Fig. 4. Note that the second embodiment describes a specific example of the operation of classifying the causes of anomalies in the first embodiment described above, and other parts may be the same as those in the first embodiment. Therefore, the following will describe in detail parts that differ from the first embodiment already described, and will omit explanations of other overlapping parts as appropriate.

[0036] (Cause classification operation) First, the flow of the cause classification operation (i.e., the operation when classifying the cause of an abnormality in authentication processing) by the information processing system 10 according to the second embodiment will be described with reference to Fig. 4. Fig. 4 is a flowchart showing the flow of the cause classification operation by the information processing system according to the second embodiment.

[0037] As shown in FIG. 4, when the information processing system 10 according to the second embodiment starts a cause classification operation, the cause classification unit 130 determines whether the quality of the target image (i.e., the target image matched in the authentication process) is low (step S201). The cause classification unit 130 may, for example, calculate a score indicating the quality of the target image and determine whether the score is equal to or greater than a predetermined threshold. If it is determined that the quality of the target image is low (step S201: YES), the cause classification unit 130 determines that the cause of the abnormality is due to the quality of the target image (step S202). That is, the cause classification unit 130 determines that the authentication process could not be performed normally due to the low quality of the target image.

[0038] On the other hand, if the quality of the target image is not determined to be low (step S201: NO), the cause classification unit 130 determines whether the quality of the registered image (i.e., the registered image compared with the target image) is low (step S203). The cause classification unit 130 may, for example, calculate a score indicating the quality of the registered image and determine whether the score is equal to or greater than a predetermined threshold. The threshold here may be the same as or different from the threshold used in determining the target image (i.e., the determination in step S201 described above). For example, if the target image is a face image, the image quality may be evaluated based on items such as whether the entire face is captured, whether the face is not obscured by hair, a hat, sunglasses, a mask, etc., whether the number of pixels and angle are within an acceptable range, whether there is any blur or shaking, and whether the brightness and contrast are sufficient.

[0039] If it is determined that the quality of the registered image is low (step S203: YES), the cause classification unit 130 determines that the cause of the abnormality is due to the quality of the registered image (step S204). That is, the cause classification unit 130 determines that the authentication process could not be executed normally due to the low quality of the registered image.

[0040] On the other hand, if the quality of the registered image is not determined to be low (step S203: NO), the cause classification unit 130 determines that the cause of the abnormality is something other than the quality of the target image and the quality of the registered image (step S205). In this case, the cause classification unit 130 may further execute another determination process to classify the cause.

[0041] If the abnormality is caused by the quality of the target image or the quality of the registered image, the cause notification unit 140 may notify the user of measures to improve the cause of the abnormality (i.e., the quality of the target image or the registered image) along with the classified cause of the abnormality. For example, the notification from the cause notification unit 140 may include a message such as "Please retake the target image" or "Please update the registered image."

[0042] (Technical Effects) Next, the technical effects obtained by the information processing system 10 according to the second embodiment will be described.

[0043] As described in Fig. 4, the information processing system 10 according to the second embodiment executes a process for checking the quality of the target image and the registered images. In this way, it becomes possible to identify that an abnormality has occurred due to low quality of the target image or the registered image. Therefore, it is possible to distinguish between cases where the cause of the abnormality is image quality and cases where it is not.

[0044] Third Embodiment An information processing system 10 according to the third embodiment will be described with reference to Fig. 5. Note that the third embodiment describes a specific example of a cause classification operation, similar to the second embodiment described above, and other parts may be the same as the first and second embodiments. Therefore, the following will describe in detail parts that differ from the embodiments already described, and will omit explanations of other overlapping parts as appropriate.

[0045] (Cause classification operation) First, the flow of the cause classification operation by the information processing system 10 according to the third embodiment will be described with reference to Fig. 5. Fig. 5 is a flowchart showing the flow of the cause classification operation by the information processing system according to the third embodiment. Note that the following processing is executed when an abnormality occurs in which a user to be authenticated is authenticated as another user.

[0046] 5, when the cause classification operation by the information processing system 10 according to the third embodiment is started, the cause classification unit 130 executes a process of comparing an image that matches the target image in the authentication process (i.e., an image determined to have the highest degree of match) with other registered images (step S301). This comparison process may be a 1:N comparison.

[0047] Next, the cause classification unit 130 determines whether there is another registered image that matches the matched image as a result of the above-mentioned comparison (step S302). If it is determined that there is a matching registered image (step S302: YES), the cause classification unit 130 determines that the cause of the abnormality is duplicate registration or the presence of a similar registered person (step S303).

[0048] An example of double registration is when an image of user A is registered not only as user A but also as user B. In this case, it is conceivable that user A will be authenticated as user B (i.e., the target image of user A to be authenticated will match the image of user A registered as user B).

[0049] An example of similar registered persons is a situation where two different people who cannot be easily distinguished exist, such as twins. In this case, too, it is conceivable that a situation will occur in which user A is authenticated as user B (i.e., the target image of user A to be authenticated matches the registered image of user B, who is very similar to user A).

[0050] On the other hand, if it is determined that there is no matching registered image (step S302: NO), the cause classification unit 130 determines that the cause of the abnormality is something other than the above (step S304). In this case, the cause classification unit 130 may further execute another determination process to classify the cause.

[0051] If the abnormality is due to duplicate registration, the cause notification unit 140 may notify measures to improve the cause of the abnormality (i.e., duplicate registration) along with the classified cause of the abnormality. For example, the notification content of the cause notification unit 140 may include a message such as "The same image has been registered twice. Please register the correct image."

[0052] (Technical Effects) Next, the technical effects obtained by the information processing system 10 according to the third embodiment will be described.

[0053] 5, the information processing system 10 according to the third embodiment executes a process of comparing a registered image that matches in the authentication process with other registered images. In this way, it becomes possible to identify an abnormality that occurs due to multiple identical or similar images being registered.

[0054] <Fourth embodiment> An information processing system 10 according to the fourth embodiment will be described with reference to Fig. 6. Note that the fourth embodiment describes a specific example of a cause classification operation, similar to the second and third embodiments described above, and other parts may be the same as the first to third embodiments. Therefore, the following will describe in detail parts that differ from the embodiments already described, and will omit explanations of other overlapping parts as appropriate.

[0055] (Cause classification operation) First, the flow of the cause classification operation by the information processing system 10 according to the fourth embodiment will be described with reference to Fig. 6. Fig. 6 is a flowchart showing the flow of the cause classification operation by the information processing system according to the fourth embodiment. Note that the following processing is executed when an abnormality occurs in which the target image of the user to be authenticated matches the registered images of two different people.

[0056] 6, when the cause classification operation by the information processing system 10 according to the fourth embodiment is started, the cause classification unit 130 changes the threshold value used to determine whether authentication is successful in the authentication process (i.e., the threshold value for determining whether the images match) (step S401). For example, the cause classification unit 130 may change the threshold value so that authentication is less likely to succeed. More specifically, the cause classification unit 130 may change a loose threshold value that allows for some tolerance of strangers in order to reduce the false rejection rate to a strict threshold value that reduces the false acceptance rate.

[0057] Next, the cause classification unit 130 uses the changed threshold to perform a matching process on the first candidate image (the image with the highest degree of match) and the second candidate image (the image with the second highest degree of match) that match the target image (step S402).The cause classification unit 130 then determines whether the result of the re-matching is unchanged from the initial authentication result (step S403).That is, the cause classification unit 130 determines whether both the first candidate image and the second candidate image continue to match.

[0058] If there is no change in the authentication result (step S403: YES), the cause classification unit 130 determines that the cause of the abnormality is double registration (i.e., the same image is registered twice) (step S404). This is because if the first candidate image and the second candidate image are the same image, changing the threshold value used for authentication is likely to result in no change in the authentication result.

[0059] On the other hand, if there is a change in the authentication result (step S403: NO), the cause classification unit 130 determines whether it is determined that the first candidate image matches but the second candidate image does not match (step S405). If it is determined that the first candidate image matches but the second candidate image does not match (step S405: YES), the cause classification unit 130 determines that the above cause is the presence of a similar person (step S406). This is because it is considered that, by setting a stricter threshold, only the image of the person in question (i.e., the first candidate image) is determined to match, and the image of a similar person (i.e., the second candidate image) is determined to not match.

[0060] On the other hand, if it is not determined that the first candidate image matches and the second candidate image does not match (step S405: NO), the cause classification unit 130 determines that the cause of the abnormality is something other than the above (step S304). In this case, the cause classification unit 130 may further execute another determination process to classify the cause.

[0061] (Technical Effects) Next, the technical effects obtained by the information processing system 10 according to the fourth embodiment will be described.

[0062] 6, in the information processing system 10 according to the fourth embodiment, the threshold value used in the authentication process is changed and a process of re-matching is executed. By changing the ease of authentication in this way and performing authentication again, it becomes possible to determine from the authentication result whether the cause of the abnormality is due to duplicate registration or the presence of another person who looks very similar.

[0063] Fifth Embodiment An information processing system 10 according to a fifth embodiment will be described with reference to Fig. 7. Note that the fifth embodiment describes a specific example of a cause classification operation, similar to the second to fourth embodiments described above, and other parts may be the same as the first to fourth embodiments. Therefore, the following will describe in detail parts that differ from the embodiments already described, and will omit explanations of other overlapping parts as appropriate.

[0064] (Cause classification operation) First, the flow of the cause classification operation by the information processing system 10 according to the fifth embodiment will be described with reference to Fig. 7. Fig. 7 is a flowchart showing the flow of the cause classification operation by the information processing system according to the fifth embodiment. Note that the following processing is executed when an abnormality occurs in which a user to be authenticated is authenticated as another user.

[0065] 7, when the cause classification operation by the information processing system 10 according to the fifth embodiment starts, the cause classification unit 130 acquires matching scores (i.e., scores indicating the degree of match) between the target image and multiple registered images (step S501). That is, the cause classification unit 130 acquires multiple matching scores calculated for each of the multiple registered images in the authentication process (1:N matching).

[0066] Next, the cause classification unit 130 determines whether or not there are multiple registered images with high matching scores among the multiple matching scores (step S502). For example, the cause classification unit 130 determines whether or not there are multiple authentication scores that exceed a predetermined threshold. The threshold here may be the same as the threshold used in the authentication process, or may be a different value.

[0067] If it is determined that there are multiple registered images with high matching scores (step S502: YES), the cause classification unit 130 determines that the cause of the abnormality is duplicate registration or the presence of similar registered people (step S503).This is because if multiple identical or similar images are registered, it is thought that high matching scores will be calculated for all of the multiple registered images.

[0068] On the other hand, if it is determined that there are not multiple registered images with high matching scores (step S502: NO), the cause classification unit 130 determines that the cause of the abnormality is something other than the above (step S504). In this case, the cause classification unit 130 may further execute another determination process to classify the cause.

[0069] (Technical Effects) Next, the technical effects obtained by the information processing system 10 according to the fifth embodiment will be described.

[0070] 7, in the information processing system 10 according to the fifth embodiment, matching scores with a plurality of registered images are obtained. In this way, it is possible to identify the cause of an abnormality by comparing and analyzing the plurality of matching scores.

[0071] Sixth Embodiment An information processing system 10 according to the sixth embodiment will be described with reference to Fig. 8. Note that the information processing system 10 according to the sixth embodiment describes a specific example of a cause classification operation, similar to the second to fifth embodiments described above, and other parts may be the same as the first to fifth embodiments. Therefore, hereinafter, parts that differ from the embodiments already described will be described in detail, and explanations of other overlapping parts will be omitted as appropriate.

[0072] (Cause classification operation) First, the flow of the cause classification operation by the information processing system 10 according to the sixth embodiment will be described with reference to Fig. 8. Fig. 8 is a flowchart showing the flow of the cause classification operation by the information processing system according to the sixth embodiment.

[0073] 8, when the cause classification operation by the information processing system 10 according to the sixth embodiment is started, the cause classification unit 130 executes a first process (step S601). Note that the first process here is a process of checking the quality of the target image and the registered image described in the second embodiment (see FIG. 4).

[0074] Next, the cause classification unit 130 executes a second process (step S602). The second process here is a process of comparing the registered image that matches in the authentication process described in the third embodiment with other registered images (see FIG. 5).

[0075] Next, the cause classification unit 130 executes a third process (step S603). The third process here is a process of changing the threshold value used in the authentication process described in the fourth embodiment and executing matching again (see FIG. 6).

[0076] Finally, the cause classification unit 130 classifies the cause of the abnormality based on the results of the first, second, and third processes described above (step S604). For example, the result of the first process can classify abnormalities caused by the quality of the target image or the registered image. The result of the second process can classify abnormalities caused by duplicate registration or the presence of similar registered persons. The result of the third process can distinguish between abnormalities caused by duplicate registration and abnormalities caused by the presence of similar registered persons.

[0077] Although the example given here is one in which the first process, the second process, and the third process are executed in this order, the order in which the processes are executed is not particularly limited. For example, the first process, the second process, and the third process may be executed one after the other, or may be executed simultaneously in parallel.

[0078] (Technical Effects) Next, the technical effects obtained by the information processing system 10 according to the sixth embodiment will be described.

[0079] As described in Fig. 8, in the information processing system 10 according to the sixth embodiment, the cause of the abnormality is classified based on the results of multiple processes. In this way, since multiple results are taken into consideration, it is possible to classify the cause of the abnormality more accurately and in more detail than when, for example, the cause of the abnormality is classified using only one process. For example, the second process alone cannot determine whether the cause of the abnormality is due to duplicate registration or the presence of a similar person, but by further combining and executing the third process, it becomes possible to distinguish between these causes.

[0080] In the above-described embodiment, examples have been given in which the first process, the second process, and the third process are executed, but in addition to these processes, a process (fourth process) of analyzing the matching scores with multiple registered images described in the fifth embodiment may also be executed.

[0081] Furthermore, the first to fourth processes may be executed in appropriate combination. That is, at least two processes may be selected from the first to fourth processes and executed in combination to classify the cause of the abnormality. For example, the first process and the second process may be executed in combination, or the second process and the third process may be executed in combination.

[0082] Furthermore, in addition to the first to fourth processes, other processes may be executed. An example of such other processes is a process for performing liveness determination (impersonation determination). By executing such processes, it becomes possible to classify, for example, the presence of a suspicious person who is attempting to fraudulently break through authentication as the cause of the abnormality.

[0083] Seventh Embodiment An information processing system 10 according to the seventh embodiment will be described with reference to Fig. 9. Note that the information processing system 10 according to the seventh embodiment differs only in some of its operations from those of the first to sixth embodiments described above, and other parts may be the same as those of the first to sixth embodiments. Therefore, the following will describe in detail the parts that differ from the embodiments already described, and will omit a description of other overlapping parts as appropriate.

[0084] (Operation flow) First, the overall flow of operations performed by the information processing system 10 according to the seventh embodiment will be described with reference to Fig. 9. Fig. 9 is a flowchart showing the flow of operations performed by the information processing system according to the seventh embodiment. Note that in Fig. 9, the same processes as those shown in Fig. 3 are denoted by the same reference numerals.

[0085] 9, when the operation of the information processing system 10 according to the seventh embodiment starts, the history information acquisition unit 110 first acquires authentication history information (step S101). Then, the anomaly detection unit 120 detects an anomaly in the authentication process based on the authentication history information acquired by the history information acquisition unit 110 (step S102).

[0086] If no abnormality is detected (step S102: NO), the subsequent processes are omitted and the series of operations ends. On the other hand, if an abnormality is detected (step S102: YES), the cause classification unit 130 executes a process of classifying the cause of the abnormality using the authentication history information acquired by the history information acquisition unit 110 (step S103).

[0087] The cause classification unit 130 identifies the cause of the abnormality from the processing result of step S103 (step S104). Then, particularly in this embodiment, the cause notification unit 140 determines a notification destination of the cause of the abnormality according to the cause of the abnormality identified by the cause classification unit 130 (step S701). Thereafter, the cause notification unit 140 notifies the determined notification destination of the cause of the abnormality (step S105).

[0088] For example, if the cause of the abnormality is the quality of the target image or the registered image, the cause notification unit 140 may notify the subject of the authentication process of the cause of the abnormality. Alternatively, if the cause of the abnormality is duplicate registration or the presence of a similar person, the cause notification unit 140 may notify a system administrator of the cause of the abnormality. Alternatively, if the cause of the abnormality is a suspicious person, the cause notification unit 140 may notify a monitor of the cause of the abnormality.

[0089] The cause notification unit 140 may also change the notification mode depending on the cause of the abnormality. For example, the cause of an abnormality with a high degree of urgency may be notified in a conspicuous display mode (for example, a conspicuous color or large characters) or with a loud sound. The notification timing for the cause of an abnormality with a high degree of urgency may also be set to occur as early as possible. On the other hand, the notification timing for an abnormality with a low degree of urgency may be set to be somewhat delayed (for example, the cause of an abnormality may be notified all at once at a later date).

[0090] (Technical Effects) Next, the technical effects obtained by the information processing system 10 according to the seventh embodiment will be described.

[0091] 9, in the information processing system 10 according to the seventh embodiment, the notification destination is determined according to the classified cause of the abnormality. In this way, the cause of the abnormality in the authentication process can be appropriately notified to the person to be notified. Therefore, it becomes possible to appropriately perform corrective processing for the abnormality, for example.

[0092] The scope of each embodiment also includes a processing method in which a program that operates the configuration of each embodiment to realize the functions of the above-described embodiments is recorded on a recording medium, the program recorded on the recording medium is read as code, and the program is executed on a computer. In other words, a computer-readable recording medium is also included in the scope of each embodiment. Furthermore, each embodiment includes not only a recording medium on which the above-described program is recorded, but also the program itself.

[0093] Examples of recording media that can be used include floppy disks, hard disks, optical disks, magneto-optical disks, CD-ROMs, magnetic tapes, non-volatile memory cards, and ROMs. Furthermore, the scope of each embodiment is not limited to programs that execute processing by themselves, but also includes programs that execute processing by operating on an OS in cooperation with other software or functions of an expansion board. Furthermore, the program itself may be stored on a server, and part or all of the program may be downloadable from the server to a user terminal.

[0094] <Additional Notes> The above-described embodiment may be further described as follows, but is not limited to the following.

[0095] (Appendix 1) The information processing system described in Appendix 1 is an information processing system including: an information acquisition means for acquiring authentication history information indicating a history of authentication processing for matching a target image with a registered image; an abnormality detection means for detecting an abnormality in the authentication processing based on the authentication history information; a cause classification means for classifying a cause of the abnormality using the authentication history information when the abnormality is detected; and a cause notification means for notifying the classified cause of the abnormality.

[0096] (Appendix 2) The information processing system described in Appendix 2 is the information processing system described in Appendix 1, in which the classification means performs a first process to determine whether the quality of at least one of the target image and the registered image is above a predetermined quality, and classifies the cause of the abnormality based on the result of the first process.

[0097] (Appendix 3) The information processing system described in Appendix 3 is the information processing system described in Appendix 1 or 2, in which the classification means performs a second process to compare matching images, which are registered images that matched the target image in the authentication process, with non-matching images, which are registered images that did not match the target image, and classifies the cause of the abnormality based on the results of the second process.

[0098] (Appendix 4) The information processing system described in Appendix 4 is the information processing system described in any one of Appendixes 1 to 3, wherein the classification means performs a third process of re-matching the target image with the registered image using a second threshold value higher than the first threshold value used in the authentication process, and classifies the cause of the abnormality based on the result of the third process.

[0099] (Appendix 5) The information processing system described in Appendix 5 is the information processing system described in any one of Appendixes 1 to 4, wherein the classification means executes a fourth process to obtain multiple matching scores indicating the degree of match between the target image and each of the multiple registered images, and classifies the cause of the abnormality based on the multiple matching scores.

[0100] (Appendix 6) The information processing system described in Appendix 6 is the information processing system described in any one of Appendixes 1 to 5, wherein the classification means performs (i) a first process of determining whether the quality of at least one of the target image and the registered image is equal to or higher than a predetermined quality, (ii) a second process of comparing a matching image, which is the registered image that matches the target image, with a non-matching image, which is the registered image that does not match the target image, and (iii) a third process of re-matching the target image with the registered image using a second threshold value that is higher than the first threshold value used in the authentication process, and classifies the cause of the abnormality based on the results of the first process, the second process, and the third process.

[0101] (Appendix 7) The information processing system according to Supplementary Note 7 is the information processing system according to any one of Supplementary Notes 1 to 6, wherein the cause notification means changes the notification destination depending on the cause of the abnormality. is.

[0102] (Appendix 8) The information processing method described in Appendix 8 is an information processing method that, by at least one computer, acquires authentication history information indicating a history of authentication processing that compares a target image with a registered image, detects an abnormality in the authentication processing based on the authentication history information, and, if the abnormality is detected, classifies the cause of the abnormality using the authentication history information and notifies the classified cause of the abnormality.

[0103] (Appendix 9) The recording medium described in Appendix 10 is a recording medium having recorded thereon a computer program for causing at least one computer to execute an information processing method, which includes acquiring authentication history information indicating a history of authentication processing for matching a target image with a registered image, detecting an abnormality in the authentication processing based on the authentication history information, and, if the abnormality is detected, classifying the cause of the abnormality using the authentication history information and notifying the classified cause of the abnormality.

[0104] (Appendix 10) The computer program described in Appendix 10 is a computer program that causes at least one computer to execute an information processing method that acquires authentication history information indicating a history of authentication processing that compares a target image with a registered image, detects an abnormality in the authentication processing based on the authentication history information, and, if the abnormality is detected, classifies the cause of the abnormality using the authentication history information and notifies the user of the classified cause of the abnormality.

[0105] (Appendix 11) The information processing device described in Appendix 11 is an information processing device including: an information acquisition means for acquiring authentication history information indicating a history of authentication processing for comparing a target image with a registered image; an abnormality detection means for detecting an abnormality in the authentication processing based on the authentication history information; a cause classification means for classifying a cause of the abnormality using the authentication history information when the abnormality is detected; and a cause notification means for notifying the classified cause of the abnormality.

[0106] This disclosure may be modified as appropriate within the scope that does not contradict the gist or idea of ​​the invention that can be read from the claims and the entire specification, and information processing systems, information processing methods, and recording media that involve such modifications are also included in the technical idea of ​​this disclosure. [Explanation of symbols]

[0107] 10 Information Processing Systems 11 processors 110 History information acquisition unit 120 Abnormality detection unit 130 Abnormality cause classification section 140 Cause notification section

Claims

1. an information acquisition means for acquiring authentication history information indicating a history of authentication processing for matching a target image with a registered image; an abnormality detection means for detecting an abnormality in the authentication process based on the authentication history information; a cause classification means for classifying the cause of the abnormality using the authentication history information when the abnormality is detected; a cause notification means for notifying the user of the classified cause of the abnormality; An information processing system comprising:

2. the cause classification means executes a first process of determining whether or not a quality of at least one of the target image and the registered image is equal to or higher than a predetermined quality, and classifies the cause of the abnormality based on a result of the first process; The information processing system according to claim 1 .

3. the cause classification means executes a second process of comparing a matched image, which is the registered image that matches the target image in the authentication process, with a non-matched image, which is the registered image that does not match the target image, and classifies the cause of the abnormality based on the result of the second process.

3. The information processing system according to claim 1 or 2.

4. the cause classification means executes a third process of re-collating the target image with the registered image using a second threshold value that is higher than the first threshold value used in the authentication process, and classifies the cause of the abnormality based on a result of the third process.

3. The information processing system according to claim 1 or 2.

5. the cause classification means executes a fourth process of acquiring a plurality of matching scores indicating degrees of match between the target image and each of the plurality of registered images, and classifies the cause of the abnormality based on the plurality of matching scores.

3. The information processing system according to claim 1 or 2.

6. The cause classification means executes (i) a first process of determining whether the quality of at least one of the target image and the registered image is equal to or higher than a predetermined quality, (ii) a second process of matching a matched image, which is the registered image that matches the target image, with a non-matched image, which is the registered image that does not match the target image, and (iii) a third process of re-matching the target image with the registered image using a second threshold value that is higher than the first threshold value used in the authentication process, and classifies the cause of the abnormality based on the results of the first process, the second process, and the third process. The information processing system according to claim 1 .

7. the cause notification means changes the notification destination depending on the cause of the abnormality.

3. The information processing system according to claim 1 or 2.

8. by at least one computer, Acquire authentication history information indicating a history of authentication processing for matching the target image with a registered image; Detecting an abnormality in the authentication process based on the authentication history information; When the abnormality is detected, classifying the cause of the abnormality using the authentication history information; notifying the cause of the classified abnormality; Information processing methods.

9. At least one computer Acquire authentication history information indicating a history of authentication processing for matching the target image with a registered image; Detecting an abnormality in the authentication process based on the authentication history information; When the abnormality is detected, classifying the cause of the abnormality using the authentication history information; notifying the cause of the classified abnormality; A computer program that executes an information processing method.

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