Authentication device, authentication system, authentication method and program

Abstract

To reduce a possibility of spoofing when personal authentication is performed by using footsteps.SOLUTION: An authentication device comprises: sound wave detection means for detecting sound waves within a predetermined frequency range that is within a frequency range which can be collected by a microphone among sound waves collected by the microphone; and collation means for determining that spoofing is performed when it is determined that characteristics of the detected sound waves do not coincide with characteristics of sound waves output by varying the characteristics of the sound waves according to time when the sound waves are collected by the microphone within the predetermined frequency range.SELECTED DRAWING: Figure 1

Description

[Technical Field]

[0001] The present invention relates to an authentication device, an authentication system, an authentication method, and a program. [Background technology]

[0002] Personal authentication may be performed using footsteps. For example, Patent Document 1 describes a method for recognizing pedestrians based on low-frequency sounds collected by a microphone while they are walking. [Prior art documents] [Patent documents]

[0003] [Patent Document 1] Japanese Patent Application Laid-Open No. 2002-197437 Summary of the Invention [Problem to be solved by the invention]

[0004] When performing personal authentication using footsteps, it is preferable to be able to reduce the possibility of impersonation.

[0005] An example of an object of the present disclosure is to provide an authentication device, an authentication system, an authentication method, and a program that can solve the above-mentioned problems. [Means for solving the problem]

[0006] According to a first aspect of the present disclosure, an authentication device includes a sound wave detection means for detecting sound waves within a predetermined frequency range within a frequency range that can be picked up by the microphone from among the sound waves picked up by the microphone, and a comparison means for determining that impersonation has occurred when it is determined that the characteristics of the detected sound waves do not match the characteristics of sound waves output by the microphone within the predetermined frequency range, the characteristics of which change according to time.

[0007] According to a second aspect of the present disclosure, an authentication system includes a microphone, a sound wave output means for outputting sound waves within a predetermined frequency range within a frequency range that can be picked up by the microphone, with the characteristics of the sound waves changing according to the time, a sound wave detection means for detecting sound waves within the predetermined frequency range from among the sound waves picked up by the microphone, and a comparison means for determining that impersonation has occurred if it is determined that the characteristics of the detected sound waves do not match the characteristics of the sound waves output by the sound wave output means at the time the sound waves were picked up by the microphone.

[0008] According to a third aspect of the present disclosure, an authentication method includes a computer detecting sound waves within a predetermined frequency range from among sound waves collected by a microphone within a frequency range that can be collected by the microphone, and determining that impersonation has occurred if it determines that the characteristics of the detected sound waves do not match the characteristics of sound waves output by the microphone within the predetermined frequency range, the characteristics of which change according to time.

[0009] According to a fourth aspect of the present disclosure, the program causes a computer to detect sound waves within a predetermined frequency range from among sound waves collected by a microphone within a frequency range that can be collected by the microphone, and determine that impersonation has occurred if it is determined that the characteristics of the detected sound waves do not match the characteristics of sound waves output by the microphone within the predetermined frequency range, the characteristics of which are changed according to the time. [Effects of the Invention]

[0010] According to one aspect of the present disclosure, when performing personal authentication using footsteps, the possibility of impersonation can be reduced. [Brief explanation of the drawings]

[0011] [Figure 1] FIG. 1 is a diagram illustrating an example of the configuration of a footstep authentication system according to at least one embodiment. [Figure 2]FIG. 1 is a diagram illustrating an overview of a process performed by a footstep authentication system according to at least one embodiment. [Figure 3] 10A and 10B are diagrams illustrating examples of bit strings obtained by interference between two bit strings when a high frequency generating device according to at least one embodiment outputs a bit string by high frequency. [Figure 4] 10A and 10B are diagrams illustrating examples of high-frequency waves observed in spoofing when a high-frequency wave generating device according to at least one embodiment changes the frequency of the high-frequency wave depending on the time of day. [Figure 5] FIG. 2 is a diagram illustrating an example of a procedure of processing performed by a footstep authentication device according to at least one embodiment. [Figure 6] FIG. 1 illustrates an example of the configuration of an authentication device according to at least one embodiment. [Figure 7] FIG. 1 is a diagram illustrating an example of a configuration of an authentication system according to at least one embodiment. [Figure 8] FIG. 1 is a diagram illustrating an example of a procedure for processing spoofing detection according to at least one embodiment. [Figure 9] FIG. 1 illustrates an example configuration of a computer according to at least one embodiment. DETAILED DESCRIPTION OF THE INVENTION

[0012] The following describes embodiments of the present invention, but the following embodiments do not limit the scope of the invention as claimed. Furthermore, not all of the combinations of features described in the embodiments are necessarily essential to the solution of the invention.

[0013] First Embodiment 1 is a diagram showing an example of the configuration of a footstep authentication system according to at least one embodiment. In the configuration shown in Fig. 1, the footstep authentication system 1 includes a high-frequency generator 100, a microphone 200, and a footstep authentication device 300.

[0014] The footstep authentication device 300 includes a signal input unit 310, a calculation processing unit 320, a data storage unit 330, and a determination result display unit 340. The calculation processing unit 320 includes a footstep analysis unit 321, a high-frequency processing unit 324, and a matching unit 326. The footstep analysis unit 321 includes a footstep extraction unit 322 and a parameter detection unit 323. The high-frequency processing unit 324 includes a high-frequency detection unit 325.

[0015] The footstep authentication system 1 performs personal authentication (identification) using footsteps. In particular, the footstep authentication system 1 outputs sound waves (sound waves in the broad sense, i.e., ultrasonic waves, audible sounds, infrasound, etc.) as a countermeasure against impersonation using recorded footsteps. Personal authentication using footsteps is also called footstep authentication. The footstep authentication system 1 is an example of an authentication system. The footstep authentication system 1 changes some characteristics (such as frequency) of the sound waves it outputs depending on the time. When footsteps are recorded at that location, the sound waves it outputs can be used as a timestamp for the recording.

[0016] Here, one possible example of spoofing using recorded footsteps is when a malicious third party records the footsteps of a person they wish to impersonate and plays the recorded footsteps at the location they wish to impersonate.The authentication device may then perform authentication based on the played footsteps, resulting in a false authentication in which the person they wish to impersonate (the person whose footsteps are being recorded) is successfully authenticated.

[0017] In response to this, the footstep authentication system 1 outputs sound waves within a certain frequency range at a location where sound waves for footstep authentication are to be collected, with some characteristics changing according to the time as described above.The footstep authentication system 1 then determines whether the collected sound contains sound waves within that frequency range other than the sound waves output in real time.If it determines that such sound waves are included, the footstep authentication system 1 determines that there is a possibility of spoofing using recorded footsteps.

[0018] Here, it is considered that the characteristics of footsteps differ depending on the location where the footsteps are recorded. As a result, if footsteps recorded in another location are played back, authentication may fail (the footsteps may not be recognized as belonging to the person whose footsteps are recorded). In the following, it is assumed that a person wishing to impersonate another person (a malicious third party) records footsteps while the person they wish to impersonate is walking in a location where the footstep authentication system 1 is collecting sound waves. The location from which the footstep authentication system 1 collects sound waves is also referred to as a sound collection location.

[0019] The sound waves output by the footstep authentication system 1 are not limited to a specific type of sound waves. The sound waves output by the footstep authentication system 1 can be any type of sound waves that can be collected by the microphone 200, are included in the recording frequency range of a recording device used by a person who wishes to impersonate someone (a malicious third party), are distinguishable from footsteps, and are distinguishable between sound waves output in real time and sound waves output in the past.

[0020] In the following, it is assumed that the high frequency generator 100 of the footstep authentication system 1 outputs a high frequency that is audible to humans but difficult to hear (for example, a high frequency of about the frequency of a mosquito sound), and that the frequency range in which the high frequency generator 100 outputs sound waves is included within the frequency range in which the microphone 200 can collect sound. It is also assumed that the frequency range in which the high frequency generator 100 outputs sound waves is included within the frequency range in which recording can be performed by a person who wishes to impersonate someone (a malicious third party). The sound waves output by the high frequency generator 100 are also called high frequency waves or high frequency sounds.

[0021] By having the high frequency generator 100 output sound waves at a frequency that cannot be heard by a person wishing to impersonate someone (a malicious third party), it is expected that the person will not be able to recognize that the high frequency time stamp is used to prevent impersonation, either when recording footsteps or when checking the recorded data. This is expected to deter a person wishing to impersonate someone (a malicious third party) from taking measures to prevent impersonation, such as editing the recorded data.

[0022] Furthermore, by outputting sound waves with a frequency different from the frequency band of footsteps, the high frequency generator 100 can relatively easily separate footsteps from high frequencies. This is expected to enable the footstep authentication system 1 to perform authentication using footsteps and detection of impersonation using high frequencies with relatively high accuracy.

[0023] Furthermore, by having the high frequency generator output sound waves with a frequency different from the frequency band of everyday sounds, it is possible to relatively easily separate everyday sounds from high frequencies even when everyday sounds are included in the sounds collected by the microphone 200. This is expected to enable the footstep authentication system 1 to detect impersonation using high frequencies with relatively high accuracy.

[0024] The high frequency generator 100 outputs a high frequency as described above. It is preferable that the high frequency generator 100 outputs a high frequency with weak directionality so that the high frequency output from the high frequency generator 100 can be recorded no matter where in the sound collection location a person wishing to impersonate someone (a malicious third party) records footsteps. The high frequency generator 100 is an example of a sound wave output means.

[0025] As described above, the microphone 200 collects sound waves at the sound collection location. The frequency range in which the microphone 200 collects sound waves includes the frequency range of footsteps and the frequency range of the high frequency signal output by the high frequency generator 100. The microphone 200 converts the collected sound waves into audio data and outputs it to the footstep authentication device 300.

[0026] In the following, it is assumed that the microphone 200 is a single microphone, and therefore the footsteps of only one person are obtained as footsteps for authentication. When the footsteps of multiple people are obtained as footsteps for authentication, it is conceivable that the footsteps picked up by the microphone 200 may include the footsteps of the person (a malicious third party) who wishes to impersonate the person in question, in addition to the recorded footsteps. In this case, the footstep authentication system 1 may be configured to determine that authentication has failed or that impersonation has occurred if the footsteps picked up by the microphone 200 include unregistered footsteps. This is expected to prevent impersonation using recorded footsteps.

[0027] The footstep authentication device 300 performs footstep authentication and determines whether or not someone is impersonating someone else, using sound wave audio data collected by the microphone 200. The footstep authentication device 300 is an example of an authentication device. The footstep authentication device 300 may be configured using a computer such as a personal computer (PC) or a workstation (WS).

[0028] The signal input unit 310 acquires sound wave audio data collected by the microphone 200. For example, the signal input unit 310 may be configured using a communication unit included in the footstep authentication device 300, and may receive the audio data transmitted by the microphone 200. The signal input unit 310 outputs the acquired audio data to the calculation processing unit 320.

[0029] The arithmetic processing unit 320 processes the audio data acquired by the signal input unit 310 . The footstep analysis unit 321 performs footstep authentication using the audio data acquired by the signal input unit 310.

[0030] The footstep extraction unit 322 extracts footstep information from the audio data acquired by the signal input unit 310. For example, the footstep extraction unit 322 may extract audio data in a frequency range that is predetermined as a frequency band of footsteps from the audio data acquired by the signal input unit 310.

[0031] The parameter detection unit 323 acquires a feature parameter value (feature amount) of the footsteps from the footstep information extracted by the footstep extraction unit 322. The parameter detection unit 323 may acquire the parameter value by machine learning using a learning model such as a neural network. Alternatively, the parameter detection unit 323 may acquire the value of an item that is predetermined as a feature of the footsteps, such as the time interval between footsteps. The parameter detection unit 323 outputs the acquired feature parameter values ​​of the footsteps to the matching unit 326.

[0032] The high frequency processing unit 324 acquires high frequency characteristic information from the audio data acquired by the signal input unit 310. For example, the high frequency detection unit 325 of the high frequency processing unit 324 may extract audio data in a frequency range that is predetermined as a high frequency frequency band from the audio data acquired by the signal input unit 310. Then, the high frequency processing unit 324 may extract characteristic information, such as a frequency or a pulse train, that is predetermined according to the high frequency output from the high frequency generating device 100, from the high frequency audio data extracted by the high frequency detection unit 325.

[0033] The high frequency processing unit 324 outputs the acquired high frequency feature information to the matching unit 326 . As described above, the high frequency detection unit 325 extracts high frequency audio data from the audio data acquired by the signal input unit 310. The high frequency detection unit 325 is an example of an acoustic wave detection means.

[0034] The matching unit 326 performs footstep authentication using the characteristic parameter values ​​of the footsteps acquired by the parameter detection unit 323. For example, the matching unit 326 may calculate the similarity between the footstep feature parameter values ​​acquired by the parameter detection unit 323 and the footstep feature parameters stored for each person in the footstep database 333. Then, if it is determined that there is a person whose similarity is greater than a predetermined low-frequency threshold, the matching unit 326 may determine that authentication has been successful. On the other hand, if it is determined that the similarity for all persons is equal to or less than the low-frequency threshold, the matching unit 326 may determine that authentication has failed.

[0035] Successful authentication here means that the person whose footsteps are picked up by microphone 200 is determined to be the same person as one of the pre-registered people, or a specified person from among the pre-registered people. Any result other than successful authentication is also referred to as an authentication failure.

[0036] Furthermore, the matching unit 326 uses the high frequency characteristic information acquired by the high frequency processing unit 324 to determine whether or not impersonation has occurred. For example, the matching unit 326 may calculate the similarity between the high frequency characteristic information acquired by the high frequency processing unit 324 and the high frequency characteristic information stored in the high frequency storage unit 331 at the time when the microphone 200 picked up the sound waves of the target of spoofing. If the matching unit 326 determines that the similarity is greater than a predetermined high frequency threshold, it may determine that spoofing (spoofing using recorded footsteps) is not occurring. On the other hand, if it is determined that the similarity is equal to or less than the high frequency threshold, the matching unit 326 may determine that spoofing is occurring. The collation unit 326 is an example of a collation means.

[0037] The collation unit 326 performs processing according to the authentication result and the spoofing determination result. For example, if the verification unit 326 is used to manage the opening and closing of a gate, the gate may be opened if authentication is successful and it is determined that no spoofing is taking place. On the other hand, the verification unit 326 may not open the gate (close the gate or keep it closed) if authentication is unsuccessful or if it is determined that spoofing is taking place. Furthermore, the verification unit 326 may cause the determination result display unit 340 to display the authentication result and the determination result of impersonation.

[0038] The data storage unit 330 stores various types of data. The high frequency storage unit 331 stores the feature information of the high frequency output by the high frequency generator 100 . The time information storage unit 332 stores time information that serves as an index of the high frequency characteristic information stored in the high frequency storage unit 331 .

[0039] For example, the high frequency storage unit 331 stores feature information of the high frequency output by the high frequency generator 100, and the time information storage unit 332 stores time information indicating the time when the high frequency generator 100 output the high frequency. In addition, the matching unit 326 acquires time information indicating the time when the microphone 200 collected the sound waves that are the subject of footstep authentication and spoofing determination. The time when the microphone 200 collected the sound waves that are the subject of footstep authentication and spoofing determination is also referred to as the sound collection time.

[0040] Then, the collation unit 326 selects time information indicating a time that coincides with the sound collection time from the time information stored in the time information storage unit 332. Then, the collation unit 326 acquires high-frequency characteristic information linked to the selected time information from the high-frequency storage unit 331. In this way, the collation unit 326 acquires high-frequency characteristic information output by the high-frequency generating device 100 at the sound collection time.

[0041] The footstep database 333 stores characteristic parameter values ​​of footsteps for each person for footstep authentication. The determination result display unit 340 displays the result of footstep authentication and the determination result of impersonation. For example, the determination result display unit 340 may display a message indicating either authentication success, authentication failure, or impersonation.

[0042] FIG. 2 is a diagram showing an outline of the processing performed by the footstep authentication system 1. In the example of Fig. 2, the high frequency generator 100 outputs a high frequency. The microphone 200 collects sound waves including the high frequency output by the high frequency generator 100 and the footsteps of a person in the sound collection location. The footstep authentication device 300 performs footstep authentication using the footsteps included in the sound waves collected by the microphone 200. At that time, the footstep authentication device 300 also determines whether or not there is impersonation, using the high frequency included in the sound waves collected by the microphone 200.

[0043] The high frequency and its characteristic information used by the footstep authentication system 1 to determine whether someone is spoofing are not limited to a specific one. For example, the footstep authentication system 1 may use the following high frequency and characteristic information.

[0044] (1) When using unmodulated high frequency (1-1) Pulse train (1-2) High frequency (1-3) High frequency phase (1-4) A combination of two or more of the above (1-1) to (1-3)

[0045] (2) When a continuous wave is used as the carrier wave and modulated using a modulation method such as AM modulation, FM modulation, or PM modulation. (2-1) Bit pattern (2-2) Bit length (2-3) Timing for generating modulated waves (2-4) Period during which modulated waves are generated (2-5) Interval for generating modulated waves (2-6) Frequency of modulated wave (2-7) A combination of two or more of the above (2-1) to (2-6)

[0046] In (1-1) and (1-3), if the signals cannot be identified due to interference between the real-time high frequency and the recorded high frequency, the matching unit 326 may determine that spoofing has occurred. In (1-2), the frequency of the high frequency signal may be changed depending on the time, and when high frequencies of two frequencies are detected, the matching unit 326 may determine that spoofing has occurred. (1-3) can be used when the phase shift due to the influence of reflected waves can be ignored.

[0047] In (2-1) and (2-2), signal identification (detection of each bit) is necessary to confirm the high frequency in real time. When high frequency signals of the same frequency are used with two bit values ​​(bit value 0 and bit value 1), if the signals cannot be identified due to interference, the collation unit 326 may determine that spoofing has occurred. When high frequency signals of different frequencies with two bit values ​​are used, if two different signals are identified at the same time (i.e., two high frequency signals with different frequencies are detected at the same time), the collation unit 326 may determine that spoofing has occurred.

[0048] FIG. 3 is a diagram showing an example of a bit string obtained by interference between two bit strings when the high frequency generator 100 outputs a bit string using a high frequency. Figure 3 shows an example where the real-time high frequency represents a bit string of "00111000" and the recorded high frequency represents a bit string of "11010010." In the example of Figure 3, the bit value "1" is represented by the presence of sound waves, and the bit value "0" is represented by the absence of sound waves, so that the bit value "1" is represented when the bit value "1" and the bit value "0" are superimposed.

[0049] In this case, the real-time high frequency and the recorded high frequency interfere with each other to express the bit string "11111010." The bit string "11111010" due to the interference is different from the real-time bit string "00111000," and the matching unit 326 can detect spoofing.

[0050] In the cases (2-3) to (2-5), if the real-time high frequency and the recorded high frequency do not overlap in time, the verification unit 326 can detect spoofing. In (2-6), even if the real-time high frequency and the recorded high frequency overlap in time, the two high frequencies are different in frequency, so that the collation unit 326 can detect spoofing.

[0051] 4 is a diagram showing an example of high-frequency waves observed during spoofing when the high-frequency wave generating device 100 changes the frequency of the high-frequency wave depending on the time. The horizontal axis of the graph in Fig. 4 represents frequency, and the vertical axis represents the intensity of sound waves at each frequency. Line L11 shows an example of the frequency spectrum of footsteps, line L12 shows an example of the frequency spectrum of high-frequency waves reproduced by impersonation, and line L13 shows an example of the frequency spectrum of high-frequency waves output by the high-frequency wave generator 100 in real time. The high frequency generator 100 changes the frequency of the high frequency signal depending on the time, so that the high frequency detector 325 detects two high frequencies with different frequencies. This is expected to enable the collator 326 to detect spoofing.

[0052] FIG. 5 is a diagram showing an example of the procedure of the processing performed by the footstep authentication device 300. In the process of FIG. 5, the signal input unit 310 acquires real-time audio data generated by the microphone 200 (step S11).

[0053] Next, the calculation processing unit 320 separates the audio data acquired by the signal input unit 310 into high-frequency components and low-frequency components (step S12). Specifically, the footstep extraction unit 322 extracts low-frequency audio data (audio data indicating sound waves in a frequency range predetermined as the frequency range of footsteps) from the audio data acquired by the signal input unit 310. Furthermore, the high-frequency detection unit 325 extracts high-frequency audio data (audio data indicating sound waves in a frequency range predetermined as the frequency range of high frequencies output by the high-frequency generating device 100) from the audio data acquired by the signal input unit 310.

[0054] After step S12, the high frequency processing unit 324 acquires feature information of the high frequencies detected by the high frequency detection unit 325 (the high frequencies indicated by the audio data extracted by the high frequency detection unit 325) (step S21). Next, the matching unit 326 compares the feature information acquired by the high frequency processing unit 324 with the high frequency feature information stored in the high frequency memory unit 331 at the time when the microphone 200 picked up the audio of the audio data acquired by the signal input unit 310 (step S22).

[0055] After step S12, the parameter detection unit 323 acquires the feature quantities (feature parameter values) of the footsteps indicated in the low-frequency audio data extracted by the footstep extraction unit 322 (step S31). Next, the matching unit 326 performs personal authentication using the feature acquired by the parameter detection unit 323 (step S32). For example, the matching unit 326 calculates the similarity between the feature acquired by the parameter detection unit 323 and each of the feature stored for each person in the footstep database 333, and determines whether there is a person whose similarity is greater than a predetermined low-frequency threshold.

[0056] Alternatively, when a person to be authenticated notifies his / her own identification number, and a specific person is designated from among the people whose features are stored in the footstep database 333, the matching unit 326 may calculate the similarity between the feature acquired by the parameter detection unit 323 and the feature of the designated person. Then, the matching unit 326 may determine whether the calculated similarity is greater than a low-frequency threshold.

[0057] After steps S22 and S32, the matching unit 326 determines whether the feature information compared in step S22 matches (step S41). When the high-frequency processing unit 324 acquires multiple pieces of high-frequency feature information and only one piece of the multiple pieces of high-frequency feature information matches the feature information read from the high-frequency storage unit 331, the matching unit 326 determines that the feature information does not match.

[0058] If it is determined that the high frequency feature amounts match (step S41: YES), the matching unit 326 determines whether or not the personal authentication in step S32 has been successful (step S51). If the matching unit 326 determines that the authentication is successful (step S51: YES), the footstep authentication device 300 performs a process that is predetermined as a process to be performed when the authentication is successful (step S61). For example, if the footstep authentication system 1 is used to manage the opening and closing of a gate, the footstep authentication device 300 may open the gate, and the determination result display unit 340 may display a message that the authentication is successful. After step S51, the footstep authentication device 300 ends the processing of FIG.

[0059] On the other hand, if the matching unit 326 determines that the authentication has failed in step S51 (step S51: NO), the footstep authentication device 300 performs a process that is predetermined as a process to be performed when the authentication has failed (step S71). For example, if the footstep authentication system 1 is used to manage the opening and closing of a gate, the footstep authentication device 300 may not open the gate (close the gate or keep the gate closed), and the determination result display unit 340 may display a warning message that the authentication has failed. After step S71, the footstep authentication device 300 ends the processing of FIG.

[0060] On the other hand, if it is determined in step S41 that the high frequency feature amounts do not match (step S41: NO), the footstep authentication device 300 performs a process that is predetermined as a process to be performed when spoofing is detected (step S81). For example, if the footstep authentication system 1 is used to manage the opening and closing of a gate, the footstep authentication device 300 may not open the gate (close the gate or keep the gate closed), and the determination result display unit 340 may display a warning message that spoofing has been detected. After step S81, the footstep authentication device 300 ends the processing of FIG.

[0061] The collation unit 326 may perform the process of step S51 before the process of step S41. In this case, after steps S22 and S23, the matching unit 326 performs the process of step S51 (determines whether or not authentication has been successful).

[0062] If it is determined that the authentication is successful (step S:51: YES), the matching unit 326 performs the process of step S41 (determine whether the high-frequency feature amounts match). If the matching unit 326 determines that the high-frequency feature amounts match (step S41: YES), the footstep authentication device 300 performs the process of step S61 (processing when authentication is successful). After step S61, the footstep authentication device 300 ends the process of FIG. 5.

[0063] On the other hand, if the matching unit 326 determines in step S41 that the high-frequency features do not match (step S41: NO), the footstep authentication device 300 performs the process of step S81 (processing when spoofing is detected). After step S81, the footstep authentication device 300 ends the process of FIG. 5.

[0064] On the other hand, if the matching unit 326 determines that the authentication has failed in step S51 (step S51: NO), the footstep authentication device 300 performs the process of step S71 (processing when authentication has failed). After step S71, the footstep authentication device 300 ends the process of FIG.

[0065] Alternatively, the collation unit 326 may execute the process of step S41 and the process of step S51 in parallel. In this case, if the matching unit 326 determines in step S41 that the high frequency feature amounts do not match (step S41: NO), the footstep authentication device 300 performs the process of step S81 (processing when spoofing is detected). Furthermore, if the matching unit 326 determines that the authentication has failed in step S51 (step S51: NO), the footstep authentication device 300 performs the process of step S71 (processing when authentication has failed).

[0066] After steps S41 and S51, only when the matching unit 326 determines that the high frequency features match (step S41: YES) and that authentication is successful (step S51: YES), the footstep authentication device 300 performs the processing of step S61 (processing when authentication is successful), and then terminates the processing of Figure 5. On the other hand, if the matching unit 326 determines that the high frequency features do not match (step S41: NO) or that authentication has failed (step S51: NO), the footstep authentication device 300 terminates the processing of Figure 5 (without performing the processing of step S61).

[0067] As described above, high frequency detection section 325 detects sound waves within a predetermined frequency range that is within the frequency range that can be collected by microphone 200, from the sound waves collected by microphone 200. If the comparison unit 326 determines that the characteristics of the detected sound waves do not match the characteristics of the sound waves output by the microphone 200, which are output by changing the characteristics of the sound waves according to the time within a predetermined frequency range, it determines that impersonation has occurred. The footstep authentication device 300 is expected to be able to detect impersonation using recorded footsteps when performing personal authentication using footsteps. In this respect, the footstep authentication device 300 can reduce the possibility of impersonation when performing personal authentication using footsteps.

[0068] Furthermore, the matching unit 326 performs authentication using footsteps from the sound waves collected by the microphone 200, and if it determines that the person whose footsteps are the same as a person registered in advance and that the characteristics of the detected sound waves match the characteristics of the sound waves output by the microphone 200, which are output with the characteristics of the sound waves changed according to the time within a predetermined frequency range, it determines that the authentication is successful. The footstep authentication device 300 can detect impersonation using recorded footsteps, and if impersonation using recorded footsteps is detected, it can prevent authentication from succeeding.

[0069] The predetermined frequency range is within the human audible range. According to the footstep authentication device 300, it is expected that the sound waves (sound waves output by the high frequency generator 100) outputted within a predetermined frequency range with characteristics of the sound waves changed according to the time will be recorded by a recording device used by a person who has committed impersonation (a malicious third party) to record footsteps. As a result, it is expected that the footstep authentication device 300 will be able to determine whether the footsteps picked up by the microphone 200 are from a recording or not, and will be able to detect impersonation using a recording of footsteps.

[0070] The predetermined frequency range is a frequency range within the audible range of humans, and is a frequency range that is considered to be difficult for humans to hear. The footstep authentication device 300 uses sound waves with a frequency that cannot be heard by a person who wants to impersonate someone (a malicious third party), so it is expected that when footsteps are recorded, or when a person who wants to impersonate someone (a malicious third party) checks the recorded data, they will not be able to recognize that sound waves for detecting impersonation have been recorded. This is expected to prevent a person who wants to impersonate someone (a malicious third party) from taking measures to prevent impersonation, such as editing the recorded data.

[0071] Furthermore, sound waves that are output with their characteristics changed according to time within a predetermined frequency range are sound waves that are output with their frequency changed according to time. According to the footstep authentication device 300, even if sound waves (sound waves output by the high frequency generator 100) output with sound wave characteristics changed according to time within a predetermined frequency range overlap with sound waves from a recording, the frequency of the two sound waves is different, so the matching unit 326 can detect impersonation.

[0072] In addition, the sound waves output within a predetermined frequency range with their characteristics changed according to time are modulated waves in which a carrier wave based on a continuous wave is modulated, and are modulated so that the characteristics of the sound waves change according to time. According to the footstep authentication device 300, it is expected that characteristics can be given to sound waves with relatively high accuracy by modulating the carrier wave.

[0073] Second Embodiment 6 is a diagram showing an example of the configuration of an authentication device according to at least one embodiment. In the configuration shown in FIG. 6, authentication device 610 includes sound wave detection unit 611 and matching unit 612.

[0074] With this configuration, the sound wave detection unit 611 detects sound waves within a predetermined frequency range that can be picked up by the microphone, from among the sound waves picked up by the microphone. If the comparison unit 612 determines that the characteristics of the detected sound waves do not match the characteristics of the sound waves output by the microphone, the characteristics of which change according to the time within a predetermined frequency range, at the time the sound waves are collected, it determines that impersonation has occurred.

[0075] The sound wave detection unit 611 is an example of a sound wave detection means, and the matching unit 612 is an example of a matching means. The authentication device 610 is expected to be able to detect impersonation using recorded footsteps when performing personal authentication using footsteps. In this respect, the authentication device 610 can reduce the possibility of impersonation when performing personal authentication using footsteps.

[0076] Third Embodiment Fig. 7 is a diagram showing an example of the configuration of an authentication system according to at least one embodiment. In the configuration shown in Fig. 7, authentication system 620 includes sound wave output unit 621, microphone 622, and authentication device 623. Authentication device 623 includes sound wave detection unit 624 and matching unit 625.

[0077] With this configuration, the sound wave output unit 621 outputs sound waves within a predetermined frequency range that can be collected by the microphone 622, changing the characteristics of the sound waves according to the time. The sound wave detection unit 624 detects sound waves within a predetermined frequency range from among the sound waves collected by the microphone 622. If the matching unit 625 determines that the characteristics of the detected sound waves do not match the characteristics of the sound waves output by the sound wave output unit 621 at the time the sound waves were collected by the microphone 622, it determines that impersonation has occurred.

[0078] The sound wave output unit 621 is an example of a sound wave output means, the sound wave detection unit 624 is an example of a sound wave detection means, and the matching unit 625 is an example of a matching means. The authentication system 620 is expected to be able to detect impersonation using recorded footsteps when performing personal authentication using footsteps. In this respect, the authentication system 620 can reduce the possibility of impersonation when performing personal authentication using footsteps.

[0079] <Fourth embodiment> 8 is a diagram showing an example of a procedure for processing in spoofing detection according to at least one embodiment. The authentication method shown in FIG. 8 includes detecting sound waves (step S611) and making a determination (step S612).

[0080] In detecting sound waves (step S611), the computer detects sound waves within a predetermined frequency range that can be picked up by the microphone, from the sound waves picked up by the microphone. In making the judgment (step S612), if the computer determines that the characteristics of the detected sound waves do not match the characteristics of the sound waves output by the microphone, which are output by changing the characteristics of the sound waves according to the time within a predetermined frequency range, it determines that impersonation has occurred.

[0081] The authentication method shown in Fig. 8 is expected to be able to detect impersonation using recorded footsteps when performing personal authentication using footsteps. In this respect, the authentication method shown in Fig. 8 can reduce the possibility of impersonation when performing personal authentication using footsteps.

[0082] FIG. 9 illustrates an example configuration of a computer according to at least one embodiment. In the configuration shown in FIG. 9, a computer 700 includes a CPU 710, a main memory device 720, an auxiliary memory device 730, an interface 740, and a non-volatile recording medium 750.

[0083] One or more of the above-described footstep authentication device 300, authentication device 610, and authentication device 623, or a part thereof, may be implemented in the computer 700. In this case, the operation of each of the above-described processing units is stored in the auxiliary storage device 730 in the form of a program. The CPU 710 reads the program from the auxiliary storage device 730, loads it into the main storage device 720, and executes the above-described processing in accordance with the program. The CPU 710 also allocates storage areas in the main storage device 720 corresponding to each of the above-described storage units in accordance with the program. Communication between each device and other devices is performed by an interface 740 having a communication function and performing communication under the control of the CPU 710. The interface 740 also has a port for a nonvolatile recording medium 750, and reads information from the nonvolatile recording medium 750 and writes information to the nonvolatile recording medium 750.

[0084] When the footstep authentication device 300 is implemented in a computer 700, the operations of the arithmetic processing unit 320 and each unit thereof are stored in the form of a program in an auxiliary storage device 730. The CPU 710 reads the program from the auxiliary storage device 730, loads it into the main storage device 720, and executes the above-mentioned processing in accordance with the program.

[0085] Furthermore, the CPU 710, in accordance with the program, allocates a storage area in the main memory device 720 for the processing of the footstep authentication device 300, such as a storage area for the data storage unit 330. Communication between the footstep authentication device 300 and other devices, such as acquisition of audio data by the signal input unit 310, is performed by the interface 740, which has a communication function and operates under the control of the CPU 710. Display of images by the footstep authentication device 300, such as display of messages by the determination result display unit 340, is performed by the interface 740 having a display device and displaying various images under the control of the CPU 710. Reception of user operations by the footstep authentication device 300 is performed by the interface 740 having an input device and receiving user operations under the control of the CPU 710.

[0086] When the authentication device 610 is implemented in the computer 700, the operations of the sound wave detection unit 611 and the matching unit 612 are stored in the form of a program in the auxiliary storage device 730. The CPU 710 reads the program from the auxiliary storage device 730, loads it into the main storage device 720, and executes the above-mentioned processing in accordance with the program.

[0087] Furthermore, the CPU 710 allocates a storage area in the main storage device 720 for the authentication device 610 to perform processing in accordance with the program. Communication between the authentication device 610 and other devices is performed by an interface 740 having a communication function and operating under the control of the CPU 710. Interaction between the authentication device 610 and a user is performed by the interface 740 having an input device and an output device, presenting information to the user via the output device under the control of the CPU 710, and accepting user operations via the input device.

[0088] One or more of the above-described programs may be recorded on nonvolatile recording medium 750. In this case, interface 740 may read the programs from nonvolatile recording medium 750. CPU 710 may then directly execute the programs read by interface 740, or may temporarily store the programs in main storage device 720 or auxiliary storage device 730 and then execute them.

[0089] Note that the processing of each part may be performed by recording a program for executing all or part of the processing performed by the footstep authentication device 300, the authentication device 610, and the authentication device 623 on a computer-readable recording medium, and having a computer system load and execute the program recorded on the recording medium. Note that the "computer system" here includes the OS (Operating System) and hardware such as peripheral devices. Furthermore, "computer-readable recording media" refers to portable media such as flexible disks, optical magnetic disks, ROMs (Read Only Memory), and CD-ROMs (Compact Disc Read Only Memory), as well as storage devices such as hard disks built into computer systems. The program may be one that realizes part of the aforementioned functions, or may be one that can realize the aforementioned functions in combination with a program already stored in the computer system.

[0090] Although the embodiments of the present invention have been described above in detail with reference to the drawings, the specific configuration is not limited to these embodiments and includes designs within the scope of the present invention. Furthermore, the above-described embodiments may be combined with other embodiments as appropriate.

[0091] Some or all of the above embodiments can be described as, but are not limited to, the following supplementary notes.

[0092] (Appendix 1) a sound wave detection means for detecting sound waves within a predetermined frequency range that can be picked up by the microphone, from among the sound waves picked up by the microphone; a comparison means for determining that spoofing has occurred when it is determined that the characteristics of the detected sound waves do not match the characteristics of the sound waves outputted by changing the characteristics of the sound waves according to time within the predetermined frequency range at the time the sound waves were collected by the microphone; An authentication device comprising:

[0093] (Appendix 2) The matching means performs authentication using footsteps among the sound waves collected by the microphone, and determines that the person whose footsteps are the same as a pre-registered person, and determines that the authentication is successful if it determines that the characteristics of the detected sound waves match the characteristics of the sound waves output by the microphone, the characteristics of which are changed according to time within the predetermined frequency range. 10. The authentication device of claim 1.

[0094] (Appendix 3) The predetermined frequency range is a frequency range within the human audible range. 10. An authentication device according to claim 1 or 2.

[0095] (Appendix 4) The predetermined frequency range is a frequency range within the human audible range and a frequency range that is considered to be difficult for hearing. 10. The authentication device according to claim 3.

[0096] (Appendix 5) The sound waves outputted by changing the characteristics of the sound waves according to time within the predetermined frequency range are sound waves outputted by changing the frequency of the sound waves according to time. 5. An authentication device according to any one of claims 1 to 4.

[0097] (Appendix 6) The sound waves outputted within the predetermined frequency range with their characteristics changed according to time are modulated waves in which a carrier wave based on a continuous wave is modulated, and are modulated so that the characteristics of the sound waves change according to time. 6. An authentication device according to any one of claims 1 to 5.

[0098] (Appendix 7) With a microphone, a sound wave output means for outputting sound waves within a predetermined frequency range within the frequency range that can be picked up by the microphone, with characteristics of the sound waves being changed according to time; a sound wave detection means for detecting sound waves within the predetermined frequency range among the sound waves collected by the microphone; a verification means for determining that spoofing has occurred when it is determined that the characteristics of the detected sound waves do not match the characteristics of the sound waves output by the sound wave output means at the time the sound waves were collected by the microphone; An authentication system comprising:

[0099] (Appendix 8) The matching means performs authentication using footsteps among the sound waves collected by the microphone, and determines that the person whose footsteps are the same as a pre-registered person, and determines that the authentication is successful if it determines that the characteristics of the detected sound waves match the characteristics of the sound waves output by the sound wave output means at the time the sound waves were collected by the microphone. 1. The authentication system described in Appendix 7.

[0100] (Appendix 9) The predetermined frequency range is a frequency range within the human audible range. 1. An authentication system as described in Appendix 7 or Appendix 8.

[0101] (Appendix 10) The predetermined frequency range is a frequency range within the human audible range and a frequency range that is considered to be difficult for hearing. 10. The authentication system described in Appendix 9.

[0102] (Appendix 11) The sound wave output means changes the frequency of the sound waves according to time. 11. An authentication system according to any one of claims 7 to 10.

[0103] (Appendix 12) The sound wave output means outputs the sound wave as a modulated wave obtained by modulating a carrier wave based on a continuous wave, and modulates the sound wave so that the characteristics of the sound wave change according to time. 12. An authentication system according to any one of claims 7 to 11.

[0104] (Appendix 13) The computer Among the sound waves collected by the microphone, sound waves within a predetermined frequency range within a frequency range that can be collected by the microphone are detected; If it is determined that the characteristics of the detected sound waves do not match the characteristics of the sound waves outputted by changing the characteristics of the sound waves according to time within the predetermined frequency range at the time the sound waves were collected by the microphone, it is determined that spoofing has occurred. Authentication methods, including:

[0105] (Appendix 14) The computer Authentication is performed using footsteps among the sound waves collected by the microphone, and if it is determined that the person whose footsteps are the same as a pre-registered person, and if it is determined that the characteristics of the detected sound waves match the characteristics of the sound waves output by the microphone, which are output with the characteristics of the sound waves changed according to time within the predetermined frequency range, it is determined that authentication is successful. 14. The authentication method of claim 13, comprising:

[0106] (Appendix 15) The predetermined frequency range is a frequency range within the human audible range. 13. An authentication method as set forth in Appendix 13 or Appendix 14.

[0107] (Appendix 16) The predetermined frequency range is a frequency range within the human audible range and a frequency range that is considered to be difficult for hearing. The authentication method described in Appendix 15.

[0108] (Appendix 17) The sound waves outputted by changing the characteristics of the sound waves according to time within the predetermined frequency range are sound waves outputted by changing the frequency of the sound waves according to time. 17. The authentication method of any one of appendices 13 to 16.

[0109] (Appendix 18) The sound waves outputted within the predetermined frequency range with their characteristics changed according to time are modulated waves in which a carrier wave based on a continuous wave is modulated, and are modulated so that the characteristics of the sound waves change according to time. 18. The authentication method of any one of appendices 13 to 17.

[0110] (Appendix 19) On the computer, Detecting sound waves within a predetermined frequency range that can be picked up by the microphone from among the sound waves picked up by the microphone; determining that spoofing has occurred when it is determined that the characteristics of the detected sound waves do not match the characteristics of the sound waves outputted by changing the characteristics of the sound waves according to time within the predetermined frequency range at the time the sound waves were collected by the microphone; A program that executes the following.

[0111] (Appendix 20) The computer, performing authentication using footsteps among the sound waves collected by the microphone, determining that the person whose footsteps are the same as a pre-registered person, and determining that the authentication was successful if it is determined that the characteristics of the detected sound waves match the characteristics of the sound waves output by the microphone, the characteristics of which are changed according to time within the predetermined frequency range; 19. The program of claim 19,

[0112] (Appendix 21) The predetermined frequency range is a frequency range within the human audible range. 19. The program of claim 20.

[0113] (Appendix 22) The predetermined frequency range is a frequency range within the human audible range and a frequency range that is considered to be difficult for hearing. 21. The program described in Appendix 21.

[0114] (Appendix 23) The sound waves outputted by changing the characteristics of the sound waves according to time within the predetermined frequency range are sound waves outputted by changing the frequency of the sound waves according to time. 23. The program of any one of appendices 19 to 22.

[0115] (Appendix 24) The sound waves outputted within the predetermined frequency range with their characteristics changed according to time are modulated waves in which a carrier wave based on a continuous wave is modulated, and are modulated so that the characteristics of the sound waves change according to time. 24. The program of any one of appendices 19 to 23. [Explanation of symbols]

[0116] 1. Footstep authentication system 100 High frequency generator 200 microphones 300 Footstep authentication device 310 Signal input section 320 Processing Unit 321 Footstep Analysis Unit 322 Footstep Extraction Unit 323 Parameter detection unit 324 High Frequency Processing Section 325 High frequency detector 326 Collation Unit 330 Data storage unit 331 High Frequency Memory Unit 332 Time information storage unit 333 Footstep Database 340 Judgment result display section 610, 623 Authentication device 611, 624 ultrasonic detector 612, 625 Collation section 620 Authentication System 621 Sound wave output unit 622 Mike

Claims

1. a sound wave detection means for detecting sound waves within a predetermined frequency range that can be picked up by the microphone, from among the sound waves picked up by the microphone; a comparison means for determining that spoofing has occurred when it is determined that the characteristics of the detected sound waves do not match the characteristics of the sound waves outputted by changing the characteristics of the sound waves according to time within the predetermined frequency range at the time the sound waves were collected by the microphone; An authentication device comprising:

2. The matching means performs authentication using footsteps among the sound waves collected by the microphone, and determines that the person whose footsteps are the same as a pre-registered person, and determines that the authentication is successful if it determines that the characteristics of the detected sound waves match the characteristics of the sound waves output by the microphone, the characteristics of which are changed according to time within the predetermined frequency range. The authentication device according to claim 1 .

3. The predetermined frequency range is a frequency range within the human audible range. The authentication device according to claim 1 .

4. The predetermined frequency range is a frequency range within the human audible range and a frequency range that is considered to be difficult for hearing. The authentication device according to claim 3 .

5. The sound waves outputted by changing the characteristics of the sound waves according to time within the predetermined frequency range are sound waves outputted by changing the frequency of the sound waves according to time. The authentication device according to claim 1 .

6. The sound waves outputted within the predetermined frequency range with their characteristics changed according to time are modulated waves in which a carrier wave based on a continuous wave is modulated, and are modulated so that the characteristics of the sound waves change according to time. The authentication device according to claim 1 .

7. With a microphone, a sound wave output means for outputting sound waves within a predetermined frequency range within the frequency range that can be picked up by the microphone, with characteristics of the sound waves being changed according to time; a sound wave detection means for detecting sound waves within the predetermined frequency range among the sound waves collected by the microphone; a verification means for determining that spoofing has occurred when it is determined that the characteristics of the detected sound waves do not match the characteristics of the sound waves output by the sound wave output means at the time the sound waves were collected by the microphone; An authentication system comprising:

8. The computer Among the sound waves collected by the microphone, sound waves within a predetermined frequency range within a frequency range that can be collected by the microphone are detected; If it is determined that the characteristics of the detected sound waves do not match the characteristics of the sound waves outputted by changing the characteristics of the sound waves according to time within the predetermined frequency range at the time the sound waves were collected by the microphone, it is determined that spoofing has occurred. Authentication methods, including:

9. On the computer, Detecting sound waves within a predetermined frequency range that can be picked up by the microphone from among the sound waves picked up by the microphone; determining that spoofing has occurred when it is determined that the characteristics of the detected sound waves do not match the characteristics of the sound waves outputted by changing the characteristics of the sound waves according to time within the predetermined frequency range at the time the sound waves were collected by the microphone; A program that executes the following.

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