Attack object detection method and device, medium, equipment and product

Abstract

Embodiments of the present specification provide an attack object detection method, an attack object detection device, a computer readable storage medium, an electronic device and a computer program product. The method comprises: obtaining a first video corresponding to a first body part of a to-be-detected object and a second video corresponding to a second body part of the to-be-detected object, wherein the collection time of the two videos meets a preset requirement. Further, a first physiological signal is obtained according to the first video, and a second physiological signal is obtained according to the second video. Since the collection time of the two videos needs to meet the preset requirement, if the two videos come from the same living body, the physiological signals obtained from the above two videos should meet the consistency requirement. If the physiological signals obtained from the two videos cannot meet the consistency requirement, it means that there may be an attack object such as playing a video. Therefore, a detection result of the to-be-detected user is determined according to the first physiological signal and the second physiological signal.

Description

Technical Field

[0001] This specification relates to the field of identity recognition technology, and in particular to an attack target detection method, an attack target detection device, a computer-readable storage medium, an electronic device, and a computer program product. Background Technology

[0002] Identity verification systems have been widely used in recent years, and it is essential to ensure their reliability. Currently, liveness detection attacks pose a security risk to identity verification systems. Generally, liveness detection attacks involve attackers using photos, screen displays, masks, or other means to impersonate users.

[0003] To address the issue of liveness detection attacks, related technologies have provided attack target detection schemes, typically using a single-frame image as input to the attack target detection system. However, since a single-frame image contains limited information, the accuracy of the detection results needs improvement.

[0004] It should be noted that the information disclosed in the background section above is only used to enhance the understanding of the background of this specification, and therefore may include information that does not constitute prior art known to those skilled in the art. Summary of the Invention

[0005] The purpose of this specification is to provide an attack target detection method, attack target detection device, computer-readable storage medium, electronic device, and computer program product that can improve the accuracy of attack target detection to a certain extent.

[0006] Other features and advantages of this specification will become apparent from the following detailed description, or may be learned in part by practice of this specification.

[0007] According to one aspect of this specification, an attack target detection method is provided, the method comprising: acquiring a first video corresponding to a first body part of the target to be detected, and a second video corresponding to a second body part of the target to be detected, wherein the acquisition time of the first video and the second video meets a preset requirement; acquiring a first physiological signal based on the first video, and acquiring a second physiological signal based on the second video; and determining a detection result of the target to be detected based on the first physiological signal and the second physiological signal.

[0008] In an exemplary embodiment, based on the foregoing scheme, determining the detection result of the target object according to the first physiological signal and the second physiological signal includes: determining the target object as an attack target when either the first physiological signal or the second physiological signal is empty; and determining the consistency between the first physiological signal and the second physiological signal when neither the first physiological signal nor the second physiological signal is empty, and determining the detection result of the target object based on the consistency between the first physiological signal and the second physiological signal.

[0009] In an exemplary embodiment, based on the foregoing scheme, determining the detection result of the object to be detected based on the consistency between the first physiological signal and the second physiological signal includes: determining the object to be detected as a non-attack object when the consistency between the first physiological signal and the second physiological signal meets a preset condition; and determining the object to be detected as an attack object when the consistency between the first physiological signal and the second physiological signal does not meet the preset condition.

[0010] In an exemplary embodiment, based on the foregoing scheme, the first physiological signal and the second physiological signal are physiological signals of the same type, wherein the type of physiological signal is at least one of the following: heart rate, pulse, blood oxygen saturation and blood pressure.

[0011] In an exemplary embodiment, based on the foregoing scheme, the above method is applied to a terminal including a front-facing camera and a rear-facing camera; the first body part is the face, and the second body part is the fingers;

[0012] The acquisition of the first video corresponding to the first body part of the subject to be tested and the second video corresponding to the second body part of the subject to be tested includes: acquiring the first video corresponding to the face of the subject to be tested through the front camera component and acquiring the second video corresponding to the fingers of the subject to be tested through the rear camera component.

[0013] In an exemplary embodiment, based on the foregoing scheme, before acquiring the first video corresponding to the first body part of the object to be detected and the second video corresponding to the second body part of the object to be detected, the method further includes: turning on the rear light source and outputting a prompt, the prompt being used to instruct the user to face the front camera component and simultaneously cover the rear camera component and the rear light source with their finger.

[0014] In an exemplary embodiment, based on the foregoing scheme, the acquisition of the second physiological signal from the second video includes: acquiring the reflection change information of the finger illuminated by the rear light source from the second video, and determining the second physiological signal from the reflection change information.

[0015] In an exemplary embodiment, based on the foregoing scheme, obtaining the first physiological signal from the first video includes: obtaining facial feature change information from the first video, and determining the first physiological signal from the facial feature change information.

[0016] In an exemplary embodiment, based on the foregoing scheme, the first body part is the face, and the method further includes: performing facial recognition based on the first video corresponding to the face to obtain a facial recognition result; and determining the identity recognition result of the object to be detected based on the detection result and the facial recognition result.

[0017] According to another aspect of this specification, an attack target detection device is provided, the device comprising: a video acquisition module, a physiological signal acquisition module, and a detection result determination module.

[0018] The video acquisition module is configured to: acquire a first video corresponding to a first body part of the object to be detected, and a second video corresponding to a second body part of the object to be detected, wherein the acquisition time of the first video and the second video meets a preset requirement; the physiological signal acquisition module is configured to: acquire a first physiological signal based on the first video, and acquire a second physiological signal based on the second video; and the detection result determination module is configured to: determine the detection result of the object to be detected based on the first physiological signal and the second physiological signal.

[0019] According to another aspect of this specification, an electronic device is provided, including a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor executes the computer program to implement the attack target detection method as described in the above embodiments.

[0020] According to one aspect of this specification, a computer-readable storage medium is provided that stores instructions that, when executed on a computer or processor, cause the computer or processor to perform the attack target detection method as described in the above embodiments.

[0021] According to another aspect of this specification, a computer program product containing instructions is provided that, when the computer program product is run on a computer or processor, causes the computer or processor to perform the attack target detection method as described in the above embodiments.

[0022] The attack target detection method, attack target detection device, computer-readable storage medium, electronic device, and computer program product provided in the embodiments of this specification have the following technical effects:

[0023] In the exemplary embodiments provided in this specification, a first video corresponding to a first body part of the object to be detected and a second video corresponding to a second body part of the object to be detected are acquired, wherein the acquisition time of the two videos meets a preset requirement. Further, a first physiological signal is acquired from the first video, and a second physiological signal is acquired from the second video. Since the acquisition time of the two videos needs to meet the preset requirement, if the two videos are from the same living organism, the physiological signals acquired from the two videos should meet the consistency requirement. If a physiological signal cannot be acquired from the video, it indicates the presence of an attack target such as a static image; if the physiological signals acquired from the two videos do not meet the consistency requirement, it indicates the possible presence of an attack target such as a playing video. Therefore, the attack target detection scheme provided in the embodiments of this specification has high detection accuracy.

[0024] It should be understood that the above general description and the following detailed description are exemplary and explanatory only, and are not intended to limit this specification. Attached Figure Description

[0025] The accompanying drawings, which are incorporated in and form part of this specification, illustrate embodiments consistent with this specification and, together with the description, serve to explain the principles of this specification. It is obvious that the drawings described below are merely some embodiments of this specification, and those skilled in the art can obtain other drawings based on these drawings without any inventive effort.

[0026] Figure 1 This is a flowchart illustrating an attack target detection method provided in one embodiment of this specification.

[0027] Figure 2 This is a schematic diagram of a scenario for an attack target detection method provided in one embodiment of this specification.

[0028] Figure 3 This is a flowchart illustrating an attack target detection method provided in another embodiment of this specification.

[0029] Figure 4 This is a schematic diagram of the user interface during the attack target detection process provided in one embodiment of this specification.

[0030] Figures 5A to 5C These are schematic diagrams illustrating attack target detection scenarios provided in the embodiments of this specification.

[0031] Figure 6This is a schematic diagram of the attack target detection device provided in one embodiment of this specification.

[0032] Figure 7 This is a schematic diagram of the attack target detection device provided in another embodiment of this specification.

[0033] Figure 8 This is a schematic diagram of the structure of the electronic device provided in the embodiments of this specification. Detailed Implementation

[0034] To make the objectives, technical solutions, and advantages of this specification clearer, the embodiments of this specification will be described in further detail below with reference to the accompanying drawings.

[0035] In the following description, when referring to the accompanying drawings, the same numbers in different drawings denote the same or similar elements unless otherwise indicated. The embodiments described in the following exemplary embodiments do not represent all embodiments consistent with this specification. Rather, they are merely examples of apparatuses and methods consistent with some aspects of this specification as detailed in the appended claims.

[0036] Example embodiments will now be described more fully with reference to the accompanying drawings. However, example embodiments can be implemented in many forms and should not be construed as limited to the examples set forth herein; rather, these embodiments are provided to make this specification more comprehensive and complete, and to fully convey the concept of example embodiments to those skilled in the art. The described features, structures, or characteristics can be combined in any suitable manner in one or more embodiments. In the following description, numerous specific details are provided to give a full understanding of the embodiments described herein. However, those skilled in the art will recognize that the technical solutions described herein may be practiced with one or more of the specific details omitted, or other methods, components, apparatus, steps, etc., may be employed. In other instances, well-known technical solutions are not shown or described in detail to avoid obscuring various aspects of this specification.

[0037] Furthermore, the accompanying drawings are merely illustrative diagrams of this specification and are not necessarily drawn to scale. The same reference numerals in the drawings denote the same or similar parts, and therefore repeated descriptions of them will be omitted. Some block diagrams shown in the drawings are functional entities and do not necessarily correspond to physically or logically independent entities. These functional entities may be implemented in software, in one or more hardware modules or integrated circuits, or in different network and / or processor devices and / or microcontroller devices.

[0038] One attack target detection method provided by related technologies involves detecting attack targets based on a single image. While this method can intercept attacks on low-resolution images (such as mobile phone screens, printed photos, etc.), its interception effect on high-resolution images (such as high-definition mobile phone screens, high-precision head models, etc.) is minimal, indicating low accuracy in attack target detection.

[0039] Another attack target detection method provided by related technologies is based on user interaction, such as blinking or head shaking. However, this attack target detection scheme cannot detect pre-recorded high-definition videos as attack targets.

[0040] This specification provides an attack target detection method, an attack target detection device, a computer-readable storage medium, an electronic device, and a computer program product, which can solve the problems existing in the attack target detection solutions provided by related technologies.

[0041] Specifically, this specification first introduces embodiments of the attack target detection method. The attack target detection scheme provided in this specification can be applied to terminals requiring identity verification, such as... Figure 1 The terminal shown (e.g., a mobile phone, tablet computer, etc.) can be the execution subject of the attack target detection scheme provided in the embodiments of this specification.

[0042] In an exemplary embodiment, Figure 2 This is a flowchart illustrating an attack target detection method provided in one embodiment of this specification. Figure 2 As shown in the figure, the embodiment includes: S210-S230.

[0043] In S210, a first video corresponding to the first body part of the object to be detected and a second video corresponding to the second body part of the object to be detected are acquired, wherein the acquisition time of the first video and the second video meets the preset requirements.

[0044] In an exemplary embodiment, since the consistency between the first and second physiological signals is used to determine whether the two physiological signals originate from the same living organism, and physiological signals generated by different body parts of the same living organism at the same time period or point in time exhibit consistency, the acquisition times of the first and second videos used to generate the first and second physiological signals respectively should meet preset requirements. Specifically, the acquisition time period of the first video should at least overlap with the acquisition time period of the second video. For example, the first and second videos can be acquired simultaneously.

[0045] For example, by means of Figure 1The terminal shown implements the acquisition process for the first and second videos described above. (Reference) Figure 1 The terminal is equipped with a front-facing camera 21, a rear-facing camera 25, and a rear-facing light source 23. For example, when the camera is turned on... Figure 1 Before activating the terminal shown, or the target application installed on the terminal, authentication is required. Only after successful authentication can the terminal or the target application be successfully activated. For example, to facilitate the use of the authentication function, the user's posture during authentication is similar to that of a typical user of a terminal. Specifically, the user can face the front-facing camera component 21. To meet the preset requirements for video capture time, the user needs to face the front-facing camera component while simultaneously covering the rear-facing camera component 25 with their finger. At the same time, for accurate physiological signal acquisition, the user also needs to cover both the rear-facing camera component 25 and the rear light source 23 with their phone.

[0046] It should be noted that while capturing facial video, capturing videos of non-facial areas (such as arms, legs, etc.) can also achieve the attack target detection scheme provided in the embodiments of this specification. In implementing the attack target detection scheme provided in the embodiments of this specification using a mobile terminal, for ease of user operation, the capture of video of the fingers will be used as an example.

[0047] For example, the terminal contains application software for identity verification, and based on this application software, the following actions are performed: Figure 3 The embodiment shown. Wherein, Figure 3 This is a flowchart illustrating an attack target detection method provided in another embodiment of this specification. In S310, the rear light source is turned on, and a prompt is output. In S320, a first video corresponding to the face of the target to be detected is acquired through the front camera, and a second video corresponding to the fingers of the target to be detected is acquired through the rear camera.

[0048] For example, refer to Figure 4The diagram shows a user interface (UI) for displaying the aforementioned prompts in the identity verification system. These prompts instruct the user to face the front-facing camera and simultaneously cover the rear-facing camera and the rear light source with their fingers. Thus, the front-facing camera 21 captures a video of the subject's face, resulting in the first video, and the rear-facing camera 25 captures a video of the subject's fingers, resulting in the second video. Furthermore, the first and second videos must overlap in time. For example, if the first video was captured between 10:00:00 and 10:00:10 on July 26, 2022, and the second video was captured between 10:00:02 and 10:00:10 on July 26, 2022, then the two videos share a time overlap: 10:00:02 to 10:00:10 on July 26, 2022, meaning the video capture time meets the aforementioned preset requirements.

[0049] For example, to ensure the accuracy of collecting the aforementioned second physiological information (e.g., physiological signals corresponding to the finger), when collecting the second video (video about the finger), the finger needs to cover both the rear camera component 25 and the rear light source 23. For example, the aforementioned prompts can be output as voice or displayed on the terminal screen as text or icons, thereby guiding the user to perform video collection in the correct manner.

[0050] For example, during the process of collecting facial or finger videos, if the collection method does not meet the requirements, such as the front camera failing to capture an image of the entire facial area, or the user's finger not covering the rear camera or the rear light source, an alert is output to correct the user's video collection method. This allows for the acquisition of accurate physiological signals through the collected video, ultimately improving the accuracy of detecting the target of the attack.

[0051] In an exemplary embodiment, reference is made to Figures 5A-5C The usage scenarios provided in the embodiments of this specification are not limited to, for example, Figure 1 The examples shown are of mobile phones and tablet computers. The usage scenarios provided in the embodiments of this specification can also be as follows: Figure 5A In the laptop usage scenario shown, for example, the first video, i.e., the video about the face, can be obtained by the first camera component 51, while the non-face video (such as the finger in the above embodiment) can be captured by the second camera component 53 set on the device body (a light source can also be set nearby), to obtain the second video.

[0052] The usage scenarios provided in the embodiments of this specification can also be as follows: Figure 5BThe scenario shown illustrates a face-scanning entry system using identity recognition. For example, the first video (the video of the face) can be acquired via the third camera component 55, while a non-facial video (such as a finger in the above embodiment) can be captured via a fourth camera component 57 (a light source can also be placed nearby), thus obtaining the second video.

[0053] The usage scenarios provided in the embodiments of this specification can also be as follows: Figure 5C In the usage scenario of the ATM shown, for example, the first video, i.e., the video about the face, can be obtained by setting a fifth camera component (not shown in the figure) in the ATM, while a non-face video (such as the fingers in the above embodiment) can be captured by setting a sixth camera component in the ATM (a light source can also be set nearby, not shown in the figure), to obtain the second video.

[0054] Continue to refer to Figure 2 In S220, a first physiological signal is obtained based on the first video, and a second physiological signal is obtained based on the second video.

[0055] In an exemplary embodiment, reference is made to Figure 3 As one implementation of obtaining the first physiological signal based on the first video, S330 is executed: obtaining facial feature change information based on the first video, and determining the first physiological signal based on the facial feature change information.

[0056] Because heartbeats can cause color changes in the facial skin area, corresponding physiological signals can be identified. Therefore, in this embodiment, a facial physiological signal extraction algorithm is used to extract facial feature change information from the first video, and further, the first physiological signal is determined based on the facial feature change information. For example, this embodiment uses non-contact image photoplethysmography (IPPG) to determine the first physiological signal. It should be noted that this embodiment is not limited to using non-contact IPPG to extract the first physiological signal; other methods in the art for obtaining the physiological signal may also be used.

[0057] In an exemplary embodiment, reference is made to Figure 3 As one implementation of obtaining a second physiological signal based on a second video, S330' is executed: obtaining information on the reflection change of the finger illuminated by the rear light source based on the second video, and determining the second physiological signal based on the reflection change information.

[0058] Because heartbeats can cause color changes in the skin of the fingers (excluding facial skin), the corresponding physiological signals can be identified. Simultaneously, to avoid insufficient light caused by the fingers covering the rear camera and thus improve the accuracy of physiological signal extraction, this embodiment uses a finger physiological signal extraction algorithm to extract the reflective change information of the fingers illuminated by the rear light source from the second video. Furthermore, the second physiological signal is determined based on this reflective change information. Exemplarily, this embodiment uses contact-based photoplethysmography (PPG) to determine the second physiological signal. It should be noted that this embodiment is not limited to using contact-based PPG to extract the second physiological signal; other methods in the art for acquiring the physiological signal may also be used.

[0059] In an exemplary embodiment, the first physiological signal and the second physiological signal are of the same type, wherein the type of physiological signal includes one or more of heart rate, pulse, blood oxygen saturation and blood pressure.

[0060] In an exemplary embodiment, after acquiring the first physiological signal and the second physiological signal, S230 is executed: determining the detection result of the object to be detected based on the first physiological signal and the second physiological signal.

[0061] For example, refer to Figure 3 S340-S370 can be considered a specific implementation of S230. In S340, it is determined whether both the first physiological signal and the second physiological signal are not empty. For a single-frame image, since it cannot reflect the skin color change caused by heartbeat, if a single-frame image (including a high-definition mobile phone screen, a high-precision head model, etc.) is used as the attack target, since no physiological signal can be obtained (i.e., the physiological signal is empty), it indicates that the object to be detected is the attack target. Therefore, S370 is executed: determine that the object to be detected is the attack target.

[0062] For example, if it is determined in S340 that neither the first physiological signal nor the second physiological signal is empty, then S350 is executed: whether the consistency between the first physiological signal and the second physiological signal meets a preset condition. Since the two physiological signals originate from the same living organism and the acquisition time of the two videos meets the preset requirements, the correlation between the first physiological signal and the second physiological signal is high. For example, if the physiological signal is heart rate, the correlation between the heart rate signal extracted from the face video and the heart rate signal extracted from the finger video can be compared within a preset time period. If the correlation is greater than a preset value, it can be said that the consistency between the first physiological signal and the second physiological signal meets the preset condition; if the correlation is not greater than the preset value, it can be said that the consistency between the first physiological signal and the second physiological signal does not meet the preset condition. It should be noted that comparing whether the correlation is greater than a preset value can be used as one implementation method to determine whether the consistency between physiological signals meets the preset requirements. The embodiments in this specification are not limited to this method of determining whether the consistency between physiological signals meets the preset requirements.

[0063] Continue to refer to Figure 3 If, in step S350, the consistency between the first and second physiological signals meets a preset condition, indicating that the first and second videos originate from the same living being, then step S360 is executed: the target to be detected is determined to be a non-attack target, i.e., the current target to be detected is determined to be a real person. If, in step S350, the consistency between the first and second physiological signals does not meet a preset condition, indicating that the first and second videos do not originate from the same living being—for example, the first video may not be from a real face but rather a pre-recorded facial video—then step S370 is executed: the target to be detected is determined to be an attack target.

[0064] The solutions provided by the above-described embodiments can overcome the problems existing in the attack target detection solutions provided by related technologies. For example, by judging whether the pre-arrived physiological signal is empty, the situation of using a single frame image or head model as an attack target can be excluded. By judging whether the consistency between two physiological signals meets the preset conditions, the situation of using a pre-recorded video as an attack target can be excluded. It can be seen that the attack target detection solution provided by the embodiments of this specification can improve the detection accuracy.

[0065] In an exemplary embodiment, facial recognition is also performed based on the first video corresponding to the aforementioned face to obtain a facial recognition result. For example, a pre-trained classification model is used to determine the user's identity based on facial features. Furthermore, the detection result and the facial recognition result are combined to determine the identity recognition result of the object to be detected, thereby further improving the accuracy of the identity recognition result. For example, if the detection result indicates a non-attack object, but the facial recognition result indicates a non-target user, then it can be determined that the current object to be detected is not the target user. For example, only when the detection result indicates a non-attack object and the facial recognition result indicates a target user can the current object to be detected be determined to be the target user.

[0066] The attack target detection scheme provided in the embodiments of this specification can overcome the problems existing in the attack target detection schemes provided in related technologies. For example, by judging whether the pre-arrived physiological signal is empty, the situation of using a single frame image or head model as an attack target can be excluded. By judging whether the consistency between two physiological signals meets the preset conditions, the situation of using a pre-recorded video as an attack target can be excluded. It can be seen that the attack target detection scheme provided in the embodiments of this specification can improve the detection accuracy and play a good role in preventing attacks.

[0067] It should be noted that the above figures are merely illustrative of the processes included in the methods according to exemplary embodiments of this specification, and are not intended to be limiting. It is readily understood that the processes shown in the above figures do not indicate or limit the temporal order of these processes. Furthermore, it is readily understood that these processes may, for example, be executed synchronously or asynchronously in multiple modules.

[0068] The following are embodiments of the apparatus described in this specification, which can be used to execute the embodiments of the methods described in this specification. For details not disclosed in the apparatus embodiments of this specification, please refer to the embodiments of the methods described in this specification.

[0069] in, Figure 6 This is a schematic diagram of the attack target detection device provided in one embodiment of this specification. Please refer to [link / reference]. Figure 6 The attack target detection device shown in the figure can be implemented as a whole or part of an electronic device through software, hardware, or a combination of both. It can also be integrated as an independent module on a server or as an independent module in an electronic device.

[0070] The attack target detection device 600 described in the embodiments of this specification includes: a video acquisition module 610, a physiological signal acquisition module 620, and a detection result determination module 630.

[0071] The video acquisition module 610 is configured to: acquire a first video corresponding to a first body part of the object to be detected, and a second video corresponding to a second body part of the object to be detected, wherein the acquisition time of the first video and the second video meets a preset requirement; the physiological signal acquisition module 620 is configured to: acquire a first physiological signal based on the first video, and acquire a second physiological signal based on the second video; and the detection result determination module 630 is configured to: determine the detection result of the object to be detected based on the first physiological signal and the second physiological signal.

[0072] In an exemplary embodiment, Figure 7 This is a schematic diagram of an attack target detection device provided in another embodiment of this specification. Please refer to... Figure 7 :

[0073] In an exemplary embodiment, based on the foregoing scheme, the physiological signal acquisition module 620 is specifically used to: determine the target to be detected as an attack target when the first physiological signal or the second physiological signal is empty; and determine the consistency between the first physiological signal and the second physiological signal when neither the first physiological signal nor the second physiological signal is empty, and determine the detection result of the target to be detected based on the consistency between the first physiological signal and the second physiological signal.

[0074] In an exemplary embodiment, based on the aforementioned scheme, the physiological signal acquisition module 620 is specifically used to: determine the object to be detected as a non-attack object when the consistency between the first physiological signal and the second physiological signal meets a preset condition; and determine the object to be detected as an attack object when the consistency between the first physiological signal and the second physiological signal does not meet the preset condition.

[0075] In an exemplary embodiment, based on the foregoing scheme, the first physiological signal and the second physiological signal are physiological signals of the same type, wherein the type of physiological signal is at least one of the following: heart rate, pulse, blood oxygen saturation and blood pressure.

[0076] In an exemplary embodiment, based on the foregoing scheme, the above method is applied to a terminal including a front-facing camera and a rear-facing camera; the first body part is the face, and the second body part is the fingers; the video acquisition module 610 is specifically used to: acquire a first video corresponding to the face of the object to be detected through the front-facing camera, and acquire a second video corresponding to the fingers of the object to be detected through the rear-facing camera.

[0077] In an exemplary embodiment, based on the foregoing scheme, the attack target detection device 600 further includes an output module 640.

[0078] The output module 640 is configured to: turn on the rear light source and output a prompt before acquiring the first video corresponding to the first body part of the object to be detected and the second video corresponding to the second body part of the object to be detected. The prompt is used to instruct the user to face the front camera component and simultaneously cover the rear camera component and the rear light source with their fingers.

[0079] In an exemplary embodiment, based on the foregoing scheme, the physiological signal acquisition module 620 includes: a first acquisition unit 6202.

[0080] The first acquisition unit 6202 is used to: acquire the reflection change information of the finger illuminated by the rear light source based on the second video, and determine the second physiological signal based on the reflection change information.

[0081] In an exemplary embodiment, based on the foregoing scheme, the physiological signal acquisition module 620 includes: a second acquisition unit 6204.

[0082] The second acquisition unit 6204 is used to: acquire facial feature change information based on the first video, and determine the first physiological signal based on the facial feature change information.

[0083] In an exemplary embodiment, based on the foregoing scheme, the first body part is the face. In an exemplary embodiment, based on the foregoing scheme, the attack target detection device 600 further includes an identification module 650.

[0084] The aforementioned recognition module 650 is used to: perform facial recognition based on the first video corresponding to the face to obtain a facial recognition result; and determine the identity recognition result of the object to be detected based on the detection result and the facial recognition result.

[0085] It should be noted that the attack target detection device provided in the above embodiments is only illustrated by the division of the above functional modules when executing the attack target detection method. In actual applications, the above functions can be assigned to different functional modules as needed, that is, the internal structure of the device can be divided into different functional modules to complete all or part of the functions described above.

[0086] Furthermore, the attack target detection device and attack target detection method embodiments provided in the above embodiments belong to the same concept. Therefore, for details not disclosed in the device embodiments of this specification, please refer to the attack target detection method embodiments described above in this specification, which will not be repeated here.

[0087] The example numbers in this specification are for descriptive purposes only and do not represent the superiority or inferiority of the examples.

[0088] This specification also provides an electronic device, including a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor executes the program to implement the steps of any of the methods described above.

[0089] Figure 8 This is a schematic diagram of the electronic device provided in the embodiments of this specification. Please refer to... Figure 8 As shown, the electronic device 800 includes a processor 801 and a memory 802.

[0090] In this embodiment, processor 801 is the control center of the computer system and can be a processor of a physical machine or a processor of a virtual machine. Processor 801 may include one or more processing cores, such as a 4-core processor or an 8-core processor. Processor 801 may be implemented using at least one hardware form of Digital Signal Processing (DSP), Field-Programmable Gate Array (FPGA), or Programmable Logic Array (PLA). Processor 801 may also include a main processor and a coprocessor; the main processor is used to process data in the wake-up state, and the coprocessor is a low-power processor used to process data in the standby state.

[0091] In the embodiments described in this specification, the processor 801 is specifically used for:

[0092] A first video corresponding to a first body part of the subject to be tested and a second video corresponding to a second body part of the subject to be tested are acquired, wherein the acquisition time of the first video and the second video meets a preset requirement; a first physiological signal is acquired based on the first video and a second physiological signal is acquired based on the second video; and the detection result of the subject to be tested is determined based on the first physiological signal and the second physiological signal.

[0093] Furthermore, determining the detection result of the target object based on the first physiological signal and the second physiological signal includes: determining the target object as an attack target when either the first physiological signal or the second physiological signal is empty; and determining the consistency between the first physiological signal and the second physiological signal when neither the first physiological signal nor the second physiological signal is empty, and determining the detection result of the target object based on the consistency between the first physiological signal and the second physiological signal.

[0094] Furthermore, the above-mentioned determination of the detection result of the object to be detected based on the consistency between the first physiological signal and the second physiological signal includes: determining the object to be detected as a non-attack object when the consistency between the first physiological signal and the second physiological signal meets a preset condition; and determining the object to be detected as an attack object when the consistency between the first physiological signal and the second physiological signal does not meet the preset condition.

[0095] Furthermore, the first physiological signal and the second physiological signal mentioned above are physiological signals of the same type, wherein the type of physiological signal is at least one of the following: heart rate, pulse, blood oxygen saturation and blood pressure.

[0096] Furthermore, the above method is applied to a terminal including a front-facing camera and a rear-facing camera; the first body part is the face, and the second body part is the finger; the acquisition of the first video corresponding to the first body part of the object to be detected and the second video corresponding to the second body part of the object to be detected includes: acquiring the first video corresponding to the face of the object to be detected through the front-facing camera and acquiring the second video corresponding to the finger of the object to be detected through the rear-facing camera.

[0097] Furthermore, the processor 801 described above is specifically used for:

[0098] Before acquiring the first video corresponding to the first body part of the subject under test and the second video corresponding to the second body part of the subject under test: turn on the rear light source and output a prompt message, which instructs the user to face the front camera component and simultaneously cover the rear camera component and the rear light source with their finger.

[0099] Optionally, obtaining the second physiological signal based on the second video includes: obtaining the reflection change information of the finger illuminated by the rear light source based on the second video, and determining the second physiological signal based on the reflection change information.

[0100] In an exemplary embodiment, based on the foregoing scheme, obtaining the first physiological signal from the first video includes: obtaining facial feature change information from the first video, and determining the first physiological signal from the facial feature change information.

[0101] Furthermore, the processor 801 described above is specifically used for:

[0102] The first body part mentioned above is the face, and the method further includes: performing facial recognition based on the first video corresponding to the face to obtain a facial recognition result; and determining the identity recognition result of the object to be detected based on the detection result and the facial recognition result.

[0103] Memory 802 may include one or more computer-readable storage media, which may be non-transitory. Memory 802 may also include high-speed random access memory and non-volatile memory, such as one or more disk storage devices or flash memory devices. In some embodiments of this specification, the non-transitory computer-readable storage media in memory 802 is used to store at least one instruction for execution by processor 801 to implement the methods in the embodiments of this specification.

[0104] In some embodiments, the electronic device 800 further includes a peripheral device interface 803 and at least one peripheral device. The processor 801, memory 802, and peripheral device interface 803 are connected via a bus or signal line. Each peripheral device can be connected to the peripheral device interface 803 via a bus, signal line, or circuit board. Specifically, the peripheral device includes at least one of a display screen 804, a camera 805, and an audio circuit 806.

[0105] Peripheral device interface 803 can be used to connect at least one input / output (I / O) related peripheral device to processor 801 and memory 802. In some embodiments of this specification, processor 801, memory 802, and peripheral device interface 803 are integrated on the same chip or circuit board; in other embodiments of this specification, any one or two of processor 801, memory 802, and peripheral device interface 803 can be implemented on separate chips or circuit boards. This specification does not specifically limit the embodiments in this regard.

[0106] Display screen 804 is used to display a user interface (UI). The UI may include graphics, text, icons, videos, and any combination thereof. When display screen 804 is a touch display screen, it also has the ability to collect touch signals on or above its surface. These touch signals can be input as control signals to processor 801 for processing. In this case, display screen 804 can also be used to provide virtual buttons and / or a virtual keyboard, also known as soft buttons and / or a soft keyboard. In some embodiments of this specification, there may be one display screen 804, which is used as the front panel of the electronic device 800; in other embodiments, there may be at least two display screens 804, respectively disposed on different surfaces of the electronic device 800 or in a folded design; in still other embodiments, display screen 804 may be a flexible display screen, disposed on a curved or folded surface of the electronic device 800. Furthermore, display screen 804 may be configured as a non-rectangular irregular shape, i.e., a non-rectangular screen. Display screen 804 may be made of materials such as Liquid Crystal Display (LCD) or Organic Light-Emitting Diode (OLED).

[0107] Camera 805 is used to capture images or videos. Optionally, camera 805 includes a front-facing camera and a rear-facing camera. Typically, the front-facing camera is located on the front panel of the electronic device, and the rear-facing camera is located on the back of the electronic device. In some embodiments, there are at least two rear-facing cameras, which are any one of a main camera, a depth-sensing camera, a wide-angle camera, and a telephoto camera, to achieve background blurring by fusion of the main camera and the depth-sensing camera, panoramic shooting by fusion of the main camera and the wide-angle camera, virtual reality (VR) shooting, or other fusion shooting functions. In some embodiments of this specification, camera 805 may also include a flash. The flash can be a single-color temperature flash or a dual-color temperature flash. A dual-color temperature flash refers to a combination of a warm light flash and a cool light flash, which can be used for light compensation at different color temperatures.

[0108] The audio circuit 806 may include a microphone and a speaker. The microphone is used to collect sound waves from the user and the environment, and convert the sound waves into electrical signals that are input to the processor 801 for processing. For stereo sound acquisition or noise reduction purposes, there may be multiple microphones, each located in a different part of the electronic device 800. The microphone may also be an array microphone or an omnidirectional microphone.

[0109] Power supply 807 is used to supply power to various components in electronic device 800. Power supply 807 can be alternating current, direct current, a disposable battery, or a rechargeable battery. When power supply 807 includes a rechargeable battery, the rechargeable battery can be a wired rechargeable battery or a wireless rechargeable battery. A wired rechargeable battery is a battery that is charged via a wired line, while a wireless rechargeable battery is a battery that is charged via a wireless coil. The rechargeable battery can also be used to support fast charging technology.

[0110] The block diagrams of the electronic device shown in the embodiments of this specification do not constitute a limitation on the electronic device 800. The electronic device 800 may include more or fewer components than shown, or combine certain components, or use different component arrangements.

[0111] In the description of this specification, it should be understood that the terms "first," "second," etc., are used for descriptive purposes only and should not be construed as indicating or implying relative importance. Those skilled in the art can understand the specific meaning of these terms in this specification based on the specific circumstances. Furthermore, in the description of this specification, unless otherwise stated, "multiple" means two or more. "And / or" describes the relationship between related objects, indicating that three relationships can exist. For example, A and / or B can represent: A alone, A and B simultaneously, or B alone. The character " / " generally indicates that the preceding and following related objects are in an "or" relationship.

[0112] This specification also provides a computer-readable storage medium storing instructions that, when executed on a computer or processor, cause the computer or processor to perform one or more steps in the above embodiments. If the constituent modules of the above-described attack target detection device are implemented as software functional units and sold or used as independent products, they can be stored in the aforementioned computer-readable storage medium.

[0113] In the above embodiments, implementation can be achieved, in whole or in part, through software, hardware, firmware, or any combination thereof. When implemented in software, it can be implemented, in whole or in part, as a computer program product. The computer program product includes one or more computer instructions. When these computer program instructions are loaded and executed on a computer, all or part of the processes or functions described in the embodiments of this specification are generated. The computer can be a general-purpose computer, a special-purpose computer, a computer network, or other programmable device. The computer instructions can be stored in or transmitted through a computer-readable storage medium. The computer instructions can be transmitted from one website, computer, server, or data center to another website, computer, server, or data center via wired (e.g., coaxial cable, fiber optic, Digital Subscriber Line (DSL)) or wireless (e.g., infrared, wireless, microwave, etc.) means. The computer-readable storage medium can be any available medium accessible to a computer or a data storage device such as a server or data center that integrates one or more available media. The aforementioned available media can be magnetic media (e.g., floppy disks, hard disks, magnetic tapes), optical media (e.g., Digital Versatile Discs (DVDs)), or semiconductor media (e.g., Solid State Disks (SSDs)).

[0114] It should be noted that the above description describes specific embodiments of this specification. Other embodiments are within the scope of the appended claims. In some cases, the actions or steps recorded in the claims may be performed in a different order than that shown in the embodiments and still achieve the desired results. Furthermore, the processes depicted in the drawings do not necessarily require the specific or sequential order shown to achieve the desired results. In some embodiments, multitasking and parallel processing are also possible or may be advantageous.

[0115] The above description is merely a specific embodiment of this specification, but the scope of protection of this specification is not limited thereto. Any variations or substitutions that can be easily conceived by those skilled in the art within the scope of the technology disclosed in this specification should be included within the scope of protection of this specification. Therefore, equivalent variations made in accordance with the claims of this specification are still within the scope of this specification.

Claims

1. An attack target detection method, wherein, The method includes: A first video corresponding to the face of the object to be detected and a second video corresponding to the fingers of the object to be detected are acquired, wherein the acquisition time of the first video and the second video meets a preset requirement, the face of the object to be detected faces the first camera component used to acquire the first video, and the fingers of the object to be detected cover the second camera component used to acquire the second video and the light source; A first physiological signal is obtained from the first video, and a second physiological signal is obtained from the second video based on the light source irradiation of the finger. The detection result of the object to be detected is determined based on the first physiological signal and the second physiological signal.

2. The method according to claim 1, wherein, The step of determining the detection result of the object to be detected based on the first physiological signal and the second physiological signal includes: If either the first physiological signal or the second physiological signal is empty, the object to be detected is determined to be the target of attack. If neither the first physiological signal nor the second physiological signal is empty, the consistency between the first physiological signal and the second physiological signal is determined, and the detection result of the object to be detected is determined based on the consistency between the first physiological signal and the second physiological signal.

3. The method according to claim 2, wherein, Determining the detection result of the object to be detected based on the consistency between the first physiological signal and the second physiological signal includes: If the consistency between the first physiological signal and the second physiological signal meets a preset condition, the object to be detected is determined to be a non-attack object; If the consistency between the first physiological signal and the second physiological signal does not meet the preset condition, the object to be detected is determined to be an attack target.

4. The method according to any one of claims 1 to 3, wherein, The first physiological signal and the second physiological signal are physiological signals of the same type, wherein the type of physiological signal is at least one of the following: heart rate, pulse, blood oxygen saturation and blood pressure.

5. The method according to any one of claims 1 to 3, wherein, The first camera component is a front-facing camera component on the detection device; the second camera component is a rear-facing camera component on the detection device; The acquisition of the first video corresponding to the face of the object to be detected and the second video corresponding to the fingers of the object to be detected includes: The front-facing camera captures a first video of the face of the object to be detected, and the rear-facing camera captures a second video of the fingers of the object to be detected.

6. The method according to claim 5, wherein, The light source is a rear-mounted light source. Before acquiring the first video corresponding to the face of the object to be detected and the second video corresponding to the fingers of the object to be detected, the method further includes: The rear light source is turned on, and a prompt message is output, which instructs the user to face the front camera and simultaneously cover the rear camera and the rear light source with their finger.

7. The method according to claim 6, wherein, The step of obtaining the second physiological signal of the finger based on the light source illumination from the second video includes: The second physiological signal is determined based on the reflection change information of the finger of the object to be detected illuminated by the rear light source according to the second video, and the reflection change information is used to determine the second physiological signal.

8. The method according to claim 5, wherein, The step of obtaining the first physiological signal based on the first video includes: Facial feature change information is obtained from the first video, and the first physiological signal is determined based on the facial feature change information.

9. The method according to any one of claims 1 to 3 or any one of claims 6 to 8, wherein the method further comprises: Facial recognition is performed based on the first video corresponding to the face to obtain the facial recognition result; Based on the detection results and the facial recognition results, the identity recognition result of the object to be detected is determined.

10. An attack target detection device, wherein, The device includes: The video acquisition module is used to: acquire a first video corresponding to the face of the object to be detected, and a second video corresponding to the fingers of the object to be detected, wherein the acquisition time of the first video and the second video meets a preset requirement, the face of the object to be detected faces the first camera component used to acquire the first video, and the fingers of the object to be detected cover the second camera component used to acquire the second video and the light source; A physiological signal acquisition module is used to: acquire a first physiological signal based on the first video, and acquire a second physiological signal obtained by the finger based on the light source illumination based on the second video; The detection result determination module is used to: determine the detection result of the object to be detected based on the first physiological signal and the second physiological signal.

11. A computer-readable storage medium storing instructions that, when executed on a computer or processor, cause the computer or processor to perform the attack target detection method as described in any one of claims 1 to 9.

12. An electronic device comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein, When the processor executes the computer program, it implements the attack target detection method as described in any one of claims 1 to 9.

13. A computer program product containing instructions that, when run on a computer or processor, causes the computer or processor to perform the attack target detection method as described in any one of claims 1 to 9.

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