A cross-device identity authentication method and device

Abstract

The application provides a cross-device identity authentication method and device, which is applied to a master device, collects a first physiological signal in response to receiving a contact signal sent by any end device, receives a second physiological signal collected by the end device, respectively pre-processes the first physiological signal and the second physiological signal to obtain a first time sequence signal and a second time sequence signal, respectively performs Fourier transform on the first time sequence signal and the second time sequence signal to obtain a first single-value signal and a second single-value signal, checks whether the first time sequence signal and the second time sequence signal are consistent and whether the first single-value signal and the second single-value signal are consistent, and if yes, sends identity authentication information to the end device to make the end device enter an unlocking state. In the scheme, the physiological signals collected by the master device and the end device connected with the master device are real-time dynamic and not easy to copy, so that the physiological characteristics are used for unlocking, and the purpose of preventing information leakage is achieved.

Description

Technical Field

[0001] This invention relates to the field of identity recognition technology, and more specifically to a cross-device identity authentication method and apparatus. Background Technology

[0002] In daily life, the master device connects to end devices such as watches, bracelets, and earphones via Bluetooth to control the end devices and activate their functions. Currently, common device unlocking methods often rely on the camera or fingerprint sensor on the master device (such as a mobile phone or computer) to authenticate and unlock it, while neglecting the authentication and unlocking of the end devices. This could lead to the leakage of personal information and privacy from these end devices.

[0003] In existing technologies, unlocking end devices through facial recognition or fingerprint recognition is a single point in time. The recognition method relies on static information of the human body, such as facial information and fingerprint information. Static information is often easy to copy and thus vulnerable to attack, which can easily lead to information leakage. Summary of the Invention

[0004] In view of this, embodiments of the present invention provide a cross-device identity authentication method and apparatus to achieve the purpose of unlocking using real-time dynamic physiological characteristics and preventing information leakage.

[0005] To achieve the above objectives, the embodiments of the present invention provide the following technical solutions:

[0006] The first aspect of this invention discloses a cross-device authentication method applied to a master device. The master device pre-responds to a user's authentication and enters an unlocked state, and connects to multiple end devices. Each end device is equipped with a physiological signal sensor for collecting real-time dynamic physiological signals of the human body. The method includes:

[0007] If no terminal device is currently in an unlocked state, then in response to receiving a contact signal from any of the terminal devices, the user's first physiological signal is collected, and the user's second physiological signal is collected by the physiological signal sensor on the terminal device; the contact signal indicates that the user is in contact with the terminal device;

[0008] The first physiological signal and the second physiological signal are preprocessed respectively to obtain the first time-series signal and the second time-series signal;

[0009] Perform Fourier transforms on the first time-series signal and the second time-series signal respectively to obtain the first single-valued signal and the second single-valued signal;

[0010] Verify whether the first timing signal and the second timing signal are consistent, and whether the first single-value signal and the second single-value signal are consistent;

[0011] If the first timing signal and the second timing signal are consistent, and the first single-value signal and the second single-value signal are consistent, then authentication information is sent to the terminal device, causing the terminal device to enter the unlocked state.

[0012] Preferably, the first physiological signal includes a face video signal, and the second physiological signal includes a PPG waveform signal. Correspondingly, the preprocessing of the first physiological signal and the second physiological signal to obtain the first time-series signal and the second time-series signal includes:

[0013] The face video signal is converted into a one-dimensional time-series signal using the rPPG algorithm to obtain the first time-series signal.

[0014] The PPG waveform signal is downsampled to obtain a second timing signal with the same frequency as the face video signal.

[0015] Preferably, the step of verifying whether the first timing signal and the second timing signal are consistent, and whether the first single-value signal and the second single-value signal are consistent, includes:

[0016] Correlation coefficients are obtained by performing correlation calculations based on the first and second time-series signals.

[0017] Error is calculated based on the first single-valued signal and the second single-valued signal to obtain the error value;

[0018] A consistency check is performed based on the correlation coefficient and the error value;

[0019] If the consistency check passes, it is determined that the first timing signal and the second timing signal are consistent, and the first single-value signal and the second single-value signal are consistent.

[0020] Preferably, the step of calculating the correlation coefficient based on the first time-series signal and the second time-series signal includes:

[0021] When there is no time delay between the first time-series signal and the second time-series signal, the correlation coefficient is calculated based on the Pearson correlation coefficient calculation formula, the first time-series signal, and the second time-series signal.

[0022] When there is a time delay between the first time-series signal and the second time-series signal, the correlation coefficient is calculated based on the cross-correlation function, the first time-series signal, and the second time-series signal.

[0023] Preferably, the consistency verification based on the correlation coefficient and the error value includes:

[0024] If the correlation coefficient is greater than the correlation coefficient threshold and the error value is less than the error threshold, then the consistency check is determined to be successful.

[0025] or,

[0026] Multiply the difference between 1 and the correlation coefficient by the error value to obtain the evaluation index value;

[0027] If the evaluation index value is less than the index threshold, then the consistency verification is deemed successful.

[0028] A second aspect of this invention discloses a cross-device authentication method, applicable to any end device connected to a host device. The end device is equipped with a physiological signal sensor for collecting real-time dynamic physiological signals of the human body. The host device is pre-unlocked by the user through authentication. The method includes:

[0029] If no terminal device is currently in an unlocked state, a contact signal is sent to the master device in response to the user's contact; the contact signal indicates that the user is in contact with the terminal device.

[0030] The user's second physiological signal is acquired using the physiological signal sensor and then sent to the main device.

[0031] It receives the authentication information sent by the master device and enters the unlock state.

[0032] Preferably, the various end devices are interconnected, and the method further includes:

[0033] When in the unlocked state, in response to receiving a contact signal sent by the target device in the unlocking state, the system uses the physiological signal sensor to collect the user's third physiological signal and receives the fourth physiological signal collected by the target device using the physiological signal sensor; the contact signal indicates that the user is in contact with the target device.

[0034] The third physiological signal and the fourth physiological signal are preprocessed respectively to obtain the third time-series signal and the fourth time-series signal;

[0035] Perform Fourier transforms on the third time-series signal and the fourth time-series signal respectively to obtain the third single-valued signal and the fourth single-valued signal;

[0036] Verify whether the third timing signal and the fourth timing signal are consistent, and whether the third single-value signal and the fourth single-value signal are consistent;

[0037] If the third timing signal and the fourth timing signal are consistent, and the third single-value signal and the fourth single-value signal are consistent, then the authentication information is sent to the target device, causing the target device to enter the unlocked state.

[0038] Preferably, the method further includes:

[0039] If the system detects that contact with the user has ceased while it is in the unlocked state, it will enter the pending unlock state.

[0040] A third aspect of this invention discloses a cross-device authentication device applied to a main device. The main device pre-responds to a user entering an unlocked state after successful authentication and connects to multiple end devices. Each end device is equipped with a physiological signal sensor for collecting real-time dynamic physiological signals of the human body. The device includes:

[0041] A response unit is configured to, in response to receiving a contact signal from any of the terminal devices if no terminal device is currently in an unlocked state, acquire a first physiological signal of the user and receive a second physiological signal of the user acquired by the physiological signal sensor on the terminal device; the contact signal indicates that the user is in contact with the terminal device.

[0042] A preprocessing unit is used to preprocess the first physiological signal and the second physiological signal respectively to obtain a first time-series signal and a second time-series signal;

[0043] The transformation unit is used to perform Fourier transforms on the first time-series signal and the second time-series signal respectively to obtain a first single-valued signal and a second single-valued signal;

[0044] The verification unit is used to verify whether the first timing signal and the second timing signal are consistent, and whether the first single-value signal and the second single-value signal are consistent;

[0045] The unlocking unit is configured to send authentication information to the terminal device if the first timing signal and the second timing signal are consistent, and the first single-value signal and the second single-value signal are consistent, thereby enabling the terminal device to enter the unlocked state.

[0046] A fourth aspect of this invention discloses a cross-device authentication device applied to an end device, the end device being connected to a master device, the end device being equipped with a physiological signal sensor for collecting real-time dynamic physiological signals of the human body, the master device being pre-unlocked by the user through authentication, the device comprising:

[0047] A transmitting unit is configured to send a contact signal to the master device in response to a user's contact; the contact signal indicates that the user is in contact with the end device.

[0048] The acquisition unit is used to acquire the user's second physiological signal using the physiological signal sensor and send the second physiological signal to the main device.

[0049] The receiving unit is used to receive the authentication information sent by the master device and enter the unlock state.

[0050] Based on the above embodiments of the present invention, a cross-device authentication method and apparatus are provided, applied to a main device. The main device pre-responds to a user entering an unlocked state after authentication and connects to multiple terminal devices. Each terminal device is equipped with a physiological signal sensor for collecting real-time dynamic physiological signals of the human body. The method includes: if no terminal device is currently in an unlocked state, in response to receiving a contact signal sent by any terminal device, collecting a first physiological signal of the user and receiving a second physiological signal of the user collected by the physiological signal sensor on the terminal device; the contact signal indicates that the user is in contact with the terminal device; preprocessing the first physiological signal and the second physiological signal respectively to obtain a first time-series signal and a second time-series signal; performing Fourier transform on the first time-series signal and the second time-series signal respectively to obtain a first single-valued signal and a second single-valued signal; verifying whether the first time-series signal and the second time-series signal are consistent, and whether the first single-valued signal and the second single-valued signal are consistent; if the first time-series signal and the second time-series signal are consistent, and the first single-valued signal and the second single-valued signal are consistent, then sending authentication information to the terminal device, causing the terminal device to enter an unlocked state. In this solution, the unlocked master device and the terminal device connected to the master device are used to collect real-time dynamic and difficult-to-copy physiological signals of the user for unlock verification, so as to achieve the purpose of unlocking by using real-time dynamic physiological characteristics and preventing information leakage. Attached Figure Description

[0051] To more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are only embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on the provided drawings without creative effort.

[0052] Figure 1 This is a flowchart of a cross-device authentication method disclosed in an embodiment of the present invention;

[0053] Figure 2This is a flowchart of another cross-device authentication method disclosed in an embodiment of the present invention;

[0054] Figure 3 This is a structural diagram of a cross-device identity authentication device disclosed in an embodiment of the present invention;

[0055] Figure 4 This is a structural diagram of another cross-device identity authentication device disclosed in an embodiment of the present invention. Detailed Implementation

[0056] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0057] In this application, the terms "comprising," "including," or any other variations thereof are intended to cover a non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such a process, method, article, or apparatus. Without further limitation, an element defined by the phrase "comprising one..." does not exclude the presence of other identical elements in the process, method, article, or apparatus that includes said element.

[0058] First, the terms appearing in this application will be explained as follows:

[0059] PPG (Photoplethysmography) is a method that shines light into the skin and measures the light scattering caused by blood flow. Most wearable devices use PPG to measure heart rate and other physiological characteristics (respiratory rate, blood oxygenation, etc.). Optical heart rate sensors work on the principle that when hemodynamics change, such as changes in pulse rate (heart rate) or blood volume (cardiac output), the light entering the body will undergo predictable scattering.

[0060] Electrode electrocardiography, also known as ECG, requires wearing specific equipment to detect physiological characteristics such as heart rate and respiratory rate. It has relatively high accuracy but also high cost, and is commonly used in hospital electrocardiogram examinations.

[0061] rPPG (remote heart rate detection technology based on face video) is a name derived from PPG. It is a signal measured remotely, that is, a signal obtained based on video, and the heart rate can be calculated from this signal.

[0062] In summary, ECG, PPG, and rPPG are all techniques for extracting heart rate, but they differ in their measurement methods and the equipment required.

[0063] As can be seen from the background technology, in the existing technology, unlocking terminal devices by means of facial recognition or fingerprint recognition is a single point in time recognition. The recognition method relies on static information of the human body that is static and unchanging, such as facial information and fingerprint information. Static information is often easy to copy and thus vulnerable to attack, which can easily lead to information leakage.

[0064] Therefore, the present invention provides a cross-device identity authentication method and apparatus. In this scheme, the unlocked master device and the terminal device connected to the master device are used to collect the user's real-time dynamic and difficult-to-copy physiological signals for unlocking verification, so as to achieve the purpose of unlocking by using real-time dynamic physiological characteristics and preventing information leakage.

[0065] like Figure 1 The diagram shows a flowchart of a cross-device authentication method disclosed in an embodiment of the present invention. The method is applied to a master device, which responds in advance to the user entering an unlocked state after the user has passed authentication, and connects to multiple end devices. Each end device is equipped with a physiological signal sensor, which is used to collect real-time dynamic physiological signals of the human body.

[0066] It should be noted that the main device can be a mobile phone, computer, or other devices, and the terminal device can be a device that connects to the main device via Bluetooth and provides corresponding functions, such as headphones, watches, or wristbands. The physiological signal sensor can be a small PPG (pulse wave photogrammetry) sensor or an ECG (electrode electrocardiogram) sensor, or a small visual sensor. In this application, a PPG sensor is used for illustration due to cost reasons.

[0067] In this embodiment of the invention, the main device needs to be unlocked in advance through authentication to determine that the user currently using the main device is an authenticated user. The unlocked main device is then used to verify the terminal device to determine whether the user using the terminal device is the same as the user using the main device. If they are the same, the device is unlocked to prevent information leakage. The authentication and unlocking method of the main device adopts existing methods, such as face recognition, fingerprint recognition, etc.

[0068] Cross-device authentication methods include the following steps:

[0069] Step S101: If there is no terminal device currently in the unlocked state, then in response to receiving a contact signal sent by any terminal device, the user's first physiological signal is collected, and the user's second physiological signal is collected by the physiological signal sensor on the terminal device.

[0070] In step S101, the contact signal indicates that the user is in contact with the terminal device.

[0071] It should be noted that the first physiological signal and the second physiological signal contain the same dynamic human physiological characteristics, such as heart rate and respiratory rate (this application uses heart rate as an example for explanation). These dynamic physiological characteristics are not easily replicated.

[0072] It is understandable that human heart rate and respiratory rate will change at different times. Therefore, in order to ensure the accuracy of the comparison, the first and second physiological signals were collected at the same time.

[0073] The first physiological signal can be a facial video signal. In this application, the user's heart rate is extracted from the facial video signal using a remote heart rate detection technology based on facial video, namely rPPG (Predictions) technology.

[0074] The second physiological signal can be the PPG waveform signal collected by a PPG sensor. For example, popular smartwatches use photoplethysmography (PPG) waves to measure the user's heart rate, which requires close contact with the skin for effective detection. The second physiological signal can also be collected and detected using an ECG sensor, but this is generally used in hospital electrocardiogram (ECG) tests due to its high accuracy and therefore higher cost.

[0075] Step S102: Preprocess the first physiological signal and the second physiological signal respectively to obtain the first time-series signal and the second time-series signal.

[0076] In the specific implementation of step S102, the first physiological signal is taken as a face video signal, and the second physiological signal is taken as a PPG waveform signal. The corresponding preprocessing process is as follows:

[0077] The face video signal is converted into a one-dimensional time-series signal using the rPPG algorithm to obtain the first time-series signal. The PPG waveform signal is then downsampled to obtain the second time-series signal with the same frequency as the face video signal.

[0078] There are many types of rPPG algorithms, including supervised and unsupervised. Supervised algorithms are end-to-end models, while unsupervised algorithms perform signal processing on the face video signal, such as dimensional transformation and averaging. Both methods input video and output waveform. The resulting waveform often needs to be filtered to retain the 0.5Hz-2.5Hz frequency band, corresponding to a heart rate of 30-150 BPM.

[0079] It should be noted that the purpose of downsampling to make the frequencies of the second time-series signal and the face video signal consistent is to facilitate the subsequent correlation calculation between the first and second time-series signals. The frequency of the face video signal is generally 30Hz.

[0080] In one embodiment, a first timestamp recorded by the main device when recording a face video signal is obtained, and a second timestamp recorded by the PPG sensor on the end device when acquiring PPG waveform signals is obtained.

[0081] In the above preprocessing process, adjustments are made based on the first and second timestamps to synchronize the first and second timing signals.

[0082] Step S103: Perform Fourier transform on the first time-series signal and the second time-series signal respectively to obtain the first single-valued signal and the second single-valued signal.

[0083] In step 103, both the first single-value signal and the second single-value signal represent specific numerical values ​​of the user's physiological characteristics, such as heart rate, respiratory rate, etc. In this embodiment of the invention, heart rate is used for illustration.

[0084] In the specific implementation of step 103, Fourier transform is performed on the first time-series signal and the second time-series signal to obtain the first spectrum and the second spectrum, respectively. The frequency of the highest peak of the first spectrum and the second spectrum is multiplied by 60 to obtain the first single-value signal and the second single-value signal representing the heart rate.

[0085] Step S104: Verify whether the first timing signal and the second timing signal are consistent, and whether the first single-value signal and the second single-value signal are consistent. If yes, proceed to step S105; otherwise, proceed to step S106.

[0086] In step S104, consistency checks are performed between the first timing signal and the second timing signal, as well as between the first single-value signal and the second single-value signal, to ensure that the user of the contact device is the same as the user of the main device before unlocking, thus preventing information leakage.

[0087] The specific implementation of step S104 includes the following steps:

[0088] Step S201: Calculate the correlation based on the first time-series signal and the second time-series signal to obtain the correlation coefficient.

[0089] In the specific implementation of step S201, when there is no time delay between the first time-series signal and the second time-series signal, the correlation coefficient is calculated based on the Pearson correlation coefficient calculation formula, the first time-series signal, and the second time-series signal, as follows:

[0090] Correlation calculation typically refers to calculating the degree of statistical association between two sets of data. In statistics, the most commonly used correlation measure is the Pearson correlation coefficient. The Pearson correlation coefficient ranges from -1 to 1, where 1 represents a perfect positive correlation, -1 represents a perfect negative correlation, and 0 represents no linear correlation.

[0091] The formula for calculating the Pearson correlation coefficient is as follows:

[0092]

[0093] Where X and Y correspond to the first and second time-series signals, respectively, and r is the Pearson correlation coefficient. i and Y i These are the observed values ​​of the two variables. and These are the averages of the two variables.

[0094] When there is a time delay between the first time-series signal and the second time-series signal, the correlation coefficient is calculated based on the cross-correlation function, the first time-series signal, and the second time-series signal.

[0095] It should be noted that the cross-correlation function is a method for measuring the similarity of two signals at different time delays. In the cross-correlation function, the peak (if it exists) indicates the maximum correlation between the two signals. The position of the peak represents the time delay of one signal relative to the other.

[0096] Therefore, if there is a time delay between the master device and the end device, the cross-correlation function is more suitable. If the timestamp can achieve complete synchronization of the first and second time-series signals, the Pearson correlation coefficient mentioned above can be used.

[0097] The cross-correlation function is as follows:

[0098]

[0099] Among them, R xy (r) is the cross-correlation coefficient at a delay of r, where r is the time delay, which can be positive (X is delayed relative to Y) or negative (Y is delayed relative to X). X and Y correspond to the first and second time series signals, respectively, and Xi and Yi are the observed values ​​of the two variables. and These are the averages of the two variables.

[0100] Step S202: Calculate the error based on the first single-value signal and the second single-value signal to obtain the error value.

[0101] It should be noted that the error value ranges from 0 to 0.

[0102] In the specific implementation of step S202, the absolute value of the difference between the first single-value signal and the second single-value signal is calculated to obtain the error value.

[0103] Step S203: Perform consistency verification based on correlation coefficient and error value.

[0104] In the specific implementation of step S203, if the correlation coefficient is greater than the correlation coefficient threshold and the error value is less than the error threshold, then the consistency check is determined to be successful.

[0105] or,

[0106] Multiply the difference between 1 and the correlation coefficient by the error value to obtain the evaluation index value. If the evaluation index value is less than the index threshold, the consistency verification is considered to have passed.

[0107] The formula for calculating the evaluation index value is: (1 - correlation coefficient) * error value.

[0108] It should be noted that the correlation coefficient threshold, error threshold, and index threshold are all set in advance based on the actual situation.

[0109] The threshold value for this indicator is typically 0.05.

[0110] Step S204: If the consistency check passes, it is determined that the first timing signal and the second timing signal are consistent, and the first single-value signal and the second single-value signal are consistent.

[0111] It is understandable that if the consistency check fails, it is determined that the first timing signal and the second timing signal are inconsistent, and / or the first single-value signal and the second single-value signal are inconsistent.

[0112] Step S105: Send authentication information to the terminal device to enable the terminal device to enter the unlocked state.

[0113] In step S105, the identity authentication information is pre-stored in the main device. When the user unlocks the main device after verification such as face recognition or fingerprint recognition, the main device can transmit the identity authentication information to the verified terminal device.

[0114] It should be noted that, whether it is the main device or the terminal device, after contacting the user and entering the unlocked state, when it is separated from the user and no longer in contact with the user, it will automatically enter the waiting unlock state. At this time, the device functions are unavailable. When the user is contacted again, the device will re-verify. The main device will perform facial recognition or fingerprint recognition verification, and the terminal device will perform verification through the above process.

[0115] Step S106: Determined device unlocking failed.

[0116] Based on the cross-device authentication method disclosed in the above embodiments of the present invention, applied to a master device, if no end device is currently in an unlocked state, in response to receiving a contact signal sent by any end device, the master device collects a first physiological signal of the user and receives a second physiological signal of the user collected by a physiological signal sensor on the end device. The contact signal indicates that the user is in contact with the end device. The first and second physiological signals are preprocessed to obtain a first time-series signal and a second time-series signal, respectively. Fourier transforms are performed on the first and second time-series signals to obtain a first single-value signal and a second single-value signal, respectively. The master device verifies whether the first and second time-series signals are consistent and whether the first and second single-value signals are consistent. If the first and second time-series signals are consistent and the first and second single-value signals are consistent, authentication information is sent to the end device, causing the end device to enter an unlocked state. In this scheme, the unlocked master device and the end device connected to the master device are used to collect the user's real-time dynamic and difficult-to-copy physiological signals for unlock verification, so as to achieve the purpose of unlocking using real-time dynamic physiological characteristics and preventing information leakage.

[0117] Corresponding to the cross-device authentication method disclosed in the above embodiments of the present invention, such as Figure 2 The diagram shows a flowchart of another cross-device authentication method disclosed in an embodiment of the present invention. This method is applied to any end device, which is connected to a master device. The end device is equipped with a physiological signal sensor, which is used to collect real-time dynamic physiological signals of the human body. The master device is pre-unlocked by the user through authentication. The method includes the following steps:

[0118] Step S301: If there is no terminal device currently in the unlocked state, then in response to the user's contact, a contact signal is sent to the master device.

[0119] In step S301, the contact signal indicates that the user is in contact with the terminal device.

[0120] In another embodiment, multiple end devices are interconnected, and when an end device is in an unlocked state, the following unlocking process is performed:

[0121] Step S401: When in the unlocked state, in response to receiving a contact signal sent by the target device in the unlocking state, the user's third physiological signal is collected using a physiological signal sensor, and the user's fourth physiological signal is collected by the target device using a physiological signal sensor.

[0122] In step S401, the contact signal indicates that the user is in contact with the target device.

[0123] The physiological signal sensor is a PPG sensor, and the third and fourth physiological signals can both be the PPG waveform signals mentioned above.

[0124] It should be noted that the third and fourth physiological signals were collected at the same time.

[0125] It is understandable that when there are unlocked terminal devices among the various terminal devices, when any terminal device to be unlocked comes into contact with the user, it will send a contact signal to any unlocked terminal device, and collect the user's third physiological signal using a physiological signal sensor and send it to the unlocked terminal device, so that the unlocked terminal device will perform the unlocking process of steps S401 to S406.

[0126] Step S402: Preprocess the third physiological signal and the fourth physiological signal respectively to obtain the third time-series signal and the fourth time-series signal.

[0127] In step S402, the third physiological signal and the fourth physiological signal are downsampled respectively to obtain the third time-series signal and the fourth time-series signal with the same frequency and time synchronization.

[0128] Step S403: Perform Fourier transforms on the third and fourth time-series signals respectively to obtain the third single-valued signal and the fourth single-valued signal.

[0129] In step 403, both the third single-value signal and the fourth single-value signal represent specific numerical values ​​of the user's physiological characteristics, such as heart rate, respiratory rate, etc. In this embodiment of the invention, heart rate is used for illustration.

[0130] In the specific implementation of step 403, Fourier transform is performed on the third time-series signal and the fourth time-series signal to obtain the third spectrum and the fourth spectrum, respectively. The frequency of the highest peak of the third spectrum and the fourth spectrum is multiplied by 60 to obtain the third single-value signal and the fourth single-value signal representing the heart rate.

[0131] Step S405: Verify whether the third timing signal and the fourth timing signal are consistent, and whether the third single-value signal and the fourth single-value signal are consistent.

[0132] For specific verification methods, please refer to the above embodiments of the present invention, which will not be repeated here.

[0133] Step S406: If the third timing signal and the fourth timing signal are consistent, and the third single-value signal and the fourth single-value signal are consistent, then send authentication information to the target device to enable the target device to enter the unlocked state.

[0134] In step S406, the unlocked terminal device contains the authentication information of the sending autonomous device or other unlocked terminal devices.

[0135] It should be noted that using an unlocked terminal device to unlock the target terminal device does not require the use of the main device. The advantage is that the user does not need to pick up the main device again to cooperate with the collection of facial video signals. The collection of physiological signals using an unlocked terminal device achieves seamless collection, which improves the user experience.

[0136] Step S302: The user's second physiological signal is acquired using a physiological signal sensor and sent to the main device.

[0137] It should be noted that while the second physiological signal is being acquired, the main device is simultaneously acquiring the first physiological signal.

[0138] In step S302, the type of the second physiological signal collected varies depending on the physiological signal sensor. Please refer to the above-described embodiment of the present invention for details.

[0139] Step S303: Receive the authentication information sent by the master device and enter the unlock state.

[0140] In one embodiment, if either device detects that contact with the user has ceased while it is in an unlocked state, it enters a pending unlock state.

[0141] Based on the cross-device authentication method disclosed in the above embodiments of the present invention, applied to an end device, in response to user contact, a contact signal is sent to the master device. The contact signal indicates that the user is in contact with the end device. A second physiological signal of the user is collected using a physiological signal sensor and sent to the master device. The end device receives authentication information sent by the master device and enters an unlocked state. In this scheme, the unlocked master device and the end device connected to the master device are used respectively to collect the user's real-time dynamic and difficult-to-copy physiological signals for unlock verification, so as to achieve the purpose of unlocking using real-time dynamic physiological characteristics and preventing information leakage.

[0142] Based on the cross-device authentication method disclosed in the above embodiments of the present invention, such as... Figure 3 The diagram shown is a structural diagram of a cross-device authentication device disclosed in an embodiment of the present invention. It is applied to a main device, which pre-responds to the user's authentication and enters an unlocked state. The main device connects to multiple end devices, each equipped with a physiological signal sensor for collecting real-time dynamic physiological signals of the human body. The device includes:

[0143] The response unit 301 is configured to, in response to receiving a contact signal from any end device if no end device is currently in an unlocked state, collect the user's first physiological signal and receive the user's second physiological signal collected by the physiological signal sensor on the end device; the contact signal indicates that the user is in contact with the end device.

[0144] The preprocessing unit 302 is used to preprocess the first physiological signal and the second physiological signal respectively to obtain the first time-series signal and the second time-series signal.

[0145] The transformation unit 303 is used to perform Fourier transform on the first time-series signal and the second time-series signal respectively to obtain the first single-valued signal and the second single-valued signal.

[0146] The verification unit 304 is used to verify whether the first timing signal and the second timing signal are consistent, and whether the first single-value signal and the second single-value signal are consistent.

[0147] The unlocking unit 305 is used to send authentication information to the end device if the first timing signal and the second timing signal are consistent, and the first single-value signal and the second single-value signal are consistent, so that the end device enters the unlocked state.

[0148] In one embodiment, the first physiological signal includes a face video signal, and the second physiological signal includes a PPG waveform signal. Correspondingly, the preprocessing unit 302 is specifically used for:

[0149] The face video signal is converted into a one-dimensional time-series signal using the rPPG algorithm, resulting in the first time-series signal.

[0150] The PPG waveform signal is downsampled to obtain a second timing signal with the same frequency as the face video signal.

[0151] In one embodiment, the verification unit 304 includes:

[0152] The correlation coefficient calculation subunit is used to calculate the correlation based on the first time-series signal and the second time-series signal to obtain the correlation coefficient.

[0153] In one embodiment, the correlation coefficient calculation subunit is specifically used for:

[0154] When there is no time delay between the first and second time-series signals, the correlation coefficient is calculated based on the Pearson correlation coefficient formula, the first time-series signal, and the second time-series signal.

[0155] When there is a time delay between the first time-series signal and the second time-series signal, the correlation coefficient is calculated based on the cross-correlation function, the first time-series signal, and the second time-series signal.

[0156] The error value calculation subunit is used to perform error calculation based on the first single-value signal and the second single-value signal to obtain the error value.

[0157] The consistency verification subunit is used to perform consistency verification based on the correlation coefficient and error value.

[0158] The determined sub-unit is used to determine that the first timing signal and the second timing signal are consistent if the consistency check passes, and that the first single-value signal and the second single-value signal are consistent.

[0159] The consistency verification subunit is specifically used for:

[0160] If the correlation coefficient is greater than the correlation coefficient threshold and the error value is less than the error threshold, then the consistency check is considered successful.

[0161] or,

[0162] The evaluation index value is obtained by multiplying the difference between 1 and the correlation coefficient by the error value.

[0163] If the evaluation index value is less than the index threshold, then the consistency verification is considered successful.

[0164] Based on the above-described cross-device authentication device disclosed in this embodiment of the invention, applied to a master device, if no end device is currently in an unlocked state, in response to receiving a contact signal sent by any end device, the device collects a first physiological signal from the user and receives a second physiological signal from the user collected by a physiological signal sensor on the end device. The contact signal indicates that the user is in contact with the end device. The first and second physiological signals are preprocessed to obtain a first time-series signal and a second time-series signal, respectively. Fourier transforms are performed on the first and second time-series signals to obtain a first single-value signal and a second single-value signal, respectively. The device verifies whether the first and second time-series signals are consistent and whether the first and second single-value signals are consistent. If the first and second time-series signals are consistent and the first and second single-value signals are consistent, authentication information is sent to the end device, causing the end device to enter an unlocked state. In this solution, the unlocked master device and the end device connected to the master device are used to collect the user's real-time dynamic and difficult-to-copy physiological signals for unlock verification, so as to achieve the purpose of unlocking using real-time dynamic physiological characteristics and preventing information leakage.

[0165] Based on the cross-device authentication method disclosed in the above embodiments of the present invention, such as... Figure 4 The diagram shown illustrates a structural diagram of another cross-device authentication device disclosed in an embodiment of the present invention. This device is applied to an end device, which is connected to a master device. The end device is equipped with a physiological signal sensor used to collect real-time dynamic physiological signals of the human body. The master device is pre-unlocked by the user through authentication. The device includes:

[0166] The sending unit 401 is used to send a contact signal to the master device in response to the user's contact; the contact signal indicates that the user is in contact with the end device.

[0167] The acquisition unit 402 is used to acquire the user's second physiological signal using a physiological signal sensor and send the second physiological signal to the main device.

[0168] The receiving unit 403 is used to receive the authentication information sent by the master device and enter the unlock state.

[0169] In one embodiment, the device further includes:

[0170] An identity transfer unit is configured to, when in an unlocked state, in response to receiving a contact signal sent by a target device in a pending unlock state, collect a third physiological signal of the user using the physiological signal sensor, and receive a fourth physiological signal of the user collected by the target device using the physiological signal sensor; the contact signal indicates that the user is in contact with the target device.

[0171] The third physiological signal and the fourth physiological signal are preprocessed respectively to obtain the third time-series signal and the fourth time-series signal.

[0172] Fourier transforms are performed on the third time-series signal and the fourth time-series signal respectively to obtain the third single-valued signal and the fourth single-valued signal.

[0173] Verify whether the third timing signal and the fourth timing signal are consistent, and whether the third single-value signal and the fourth single-value signal are consistent.

[0174] If the third timing signal and the fourth timing signal are consistent, and the third single-value signal and the fourth single-value signal are consistent, then the authentication information is sent to the target device, causing the target device to enter the unlocked state.

[0175] In one embodiment, the device further includes:

[0176] The detection unit is used to enter the unlocking state if it detects that the user has stopped contacting the device while it is in the unlocked state.

[0177] Based on the above embodiments of the present invention, a cross-device authentication device is disclosed. Applied to an end device, in response to user contact, it sends a contact signal to a master device. The contact signal indicates that the user is in contact with the end device. A second physiological signal of the user, collected by a physiological signal sensor, is then sent to the master device. The end device receives authentication information from the master device and enters an unlocked state. In this solution, both the unlocked master device and the end device connected to the master device collect real-time, dynamic, and difficult-to-copy physiological signals of the user for unlock verification, thereby achieving unlocking using real-time, dynamic physiological characteristics and preventing information leakage.

[0178] The various embodiments in this specification are described in a progressive manner. Similar or identical parts between embodiments can be referred to mutually. Each embodiment focuses on describing the differences from other embodiments. In particular, for system or system embodiments, since they are basically similar to method embodiments, the description is relatively simple, and relevant parts can be referred to the descriptions in the method embodiments. The systems and system embodiments described above are merely illustrative. The units described as separate components may or may not be physically separate. The components shown as units may or may not be physical units; that is, they may be located in one place or distributed across multiple network units. Some or all of the modules can be selected to achieve the purpose of this embodiment according to actual needs. Those skilled in the art can understand and implement this without creative effort.

[0179] Those skilled in the art will further recognize that the units and algorithm steps of the various examples described in conjunction with the embodiments disclosed herein can be implemented in electronic hardware, computer software, or a combination of both. To clearly illustrate the interchangeability of hardware and software, the components and steps of the various examples have been generally described in terms of functionality in the foregoing description. Whether these functions are implemented in hardware or software depends on the specific application and design constraints of the technical solution. Those skilled in the art can use different methods to implement the described functions for each specific application, but such implementations should not be considered beyond the scope of this invention.

[0180] The above description of the disclosed embodiments enables those skilled in the art to make or use the invention. Various modifications to these embodiments will be readily apparent to those skilled in the art, and the general principles defined herein may be implemented in other embodiments without departing from the spirit or scope of the invention. Therefore, the invention is not to be limited to the embodiments shown herein, but is to be accorded the widest scope consistent with the principles and novel features disclosed herein.

Claims

1. A cross-device identity authentication method, characterized by, The method is applied to a main device, which pre-responds to the user entering an unlocked state after authentication and connects to multiple terminal devices. Each terminal device is equipped with a physiological signal sensor for collecting real-time dynamic physiological signals of the human body. The method includes: If no terminal device is currently in an unlocked state, then in response to receiving a contact signal from any of the terminal devices, the user's first physiological signal is collected, and the user's second physiological signal is collected by the physiological signal sensor on the terminal device; the contact signal indicates that the user is in contact with the terminal device; The first physiological signal and the second physiological signal are preprocessed respectively to obtain the first time-series signal and the second time-series signal; Perform Fourier transforms on the first time-series signal and the second time-series signal respectively to obtain the first single-valued signal and the second single-valued signal; Verify whether the first timing signal and the second timing signal are consistent, and whether the first single-value signal and the second single-value signal are consistent; If the first timing signal and the second timing signal are consistent, and the first single-value signal and the second single-value signal are consistent, then authentication information is sent to the terminal device, causing the terminal device to enter the unlocked state; Wherein, the first physiological signal includes a face video signal, and the second physiological signal includes a PPG waveform signal. Correspondingly, the preprocessing of the first physiological signal and the second physiological signal to obtain the first time-series signal and the second time-series signal includes: The face video signal is converted into a one-dimensional time-series signal using the rPPG algorithm to obtain the first time-series signal. The PPG waveform signal is downsampled to obtain a second timing signal with the same frequency as the face video signal.

2. The method of claim 1, wherein, The step of verifying whether the first timing signal and the second timing signal are consistent, and whether the first single-value signal and the second single-value signal are consistent, includes: Correlation coefficients are obtained by performing correlation calculations based on the first and second time-series signals. Error is calculated based on the first single-valued signal and the second single-valued signal to obtain the error value; A consistency check is performed based on the correlation coefficient and the error value; If the consistency check passes, it is determined that the first timing signal and the second timing signal are consistent, and that the first single-value signal and the second single-value signal are consistent.

3. The method of claim 2, wherein, The correlation calculation based on the first time-series signal and the second time-series signal to obtain the correlation coefficient includes: When there is no time delay between the first time-series signal and the second time-series signal, the correlation coefficient is calculated based on the Pearson correlation coefficient calculation formula, the first time-series signal, and the second time-series signal. When there is a time delay between the first time-series signal and the second time-series signal, the correlation coefficient is calculated based on the cross-correlation function, the first time-series signal, and the second time-series signal.

4. The method of claim 2, wherein, The consistency verification based on the correlation coefficient and the error value includes: If the correlation coefficient is greater than the correlation coefficient threshold and the error value is less than the error threshold, then the consistency check is determined to be successful. or, Multiply the difference between 1 and the correlation coefficient by the error value to obtain the evaluation index value; If the evaluation index value is less than the index threshold, then the consistency verification is deemed successful.

5. A method of cross-device identity authentication, the method comprising: Applied to any terminal device, the terminal device is connected to a main device, and the terminal device is equipped with a physiological signal sensor for collecting real-time dynamic physiological signals of the human body. The main device is pre-unlocked by the user through authentication. The method includes: If no terminal device is currently in an unlocked state, a contact signal is sent to the master device in response to the user's contact; the contact signal indicates that the user is in contact with the terminal device. The user's second physiological signal is acquired using the physiological signal sensor and sent to the main device; the second physiological signal includes a PPG waveform signal. Receive the authentication information sent by the master device and enter the unlock state; The various terminal devices are interconnected, and the method further includes: When in the unlocked state, in response to receiving a contact signal sent by the target device in the unlocking state, the system uses the physiological signal sensor to collect the user's third physiological signal and receives the fourth physiological signal collected by the target device using the physiological signal sensor; the contact signal indicates that the user is in contact with the target device; both the third and fourth physiological signals are PPG waveform signals. The third physiological signal and the fourth physiological signal are preprocessed respectively to obtain the third time-series signal and the fourth time-series signal; Perform Fourier transforms on the third time-series signal and the fourth time-series signal respectively to obtain the third single-valued signal and the fourth single-valued signal; Verify whether the third timing signal and the fourth timing signal are consistent, and whether the third single-value signal and the fourth single-value signal are consistent; If the third timing signal and the fourth timing signal are consistent, and the third single-value signal and the fourth single-value signal are consistent, then the authentication information is sent to the target device, causing the target device to enter the unlocked state.

6. The method according to claim 5, characterized in that, The method further includes: If the system detects that contact with the user has ceased while it is in the unlocked state, it will enter the pending unlock state.

7. A cross-device authentication device, characterized in that, Applied to a main device, the main device pre-responds to the user entering an unlocked state after authentication and connects to multiple terminal devices. Each terminal device is equipped with a physiological signal sensor for collecting real-time dynamic physiological signals of the human body. The device includes: A response unit is configured to, in response to receiving a contact signal from any of the terminal devices if no terminal device is currently in an unlocked state, acquire a first physiological signal of the user and receive a second physiological signal of the user acquired by the physiological signal sensor on the terminal device; the contact signal indicates that the user is in contact with the terminal device. A preprocessing unit is used to preprocess the first physiological signal and the second physiological signal respectively to obtain a first time-series signal and a second time-series signal; The transformation unit is used to perform Fourier transforms on the first time-series signal and the second time-series signal respectively to obtain a first single-valued signal and a second single-valued signal; The verification unit is used to verify whether the first timing signal and the second timing signal are consistent, and whether the first single-value signal and the second single-value signal are consistent; The unlocking unit is configured to send authentication information to the terminal device if the first timing signal and the second timing signal are consistent, and the first single-value signal and the second single-value signal are consistent, so that the terminal device enters the unlocked state. Wherein, the first physiological signal includes a face video signal, the second physiological signal includes a PPG waveform signal, and correspondingly, the preprocessing unit is specifically used for: The face video signal is converted into a one-dimensional time-series signal using the rPPG algorithm to obtain a first time-series signal; the PPG waveform signal is downsampled to obtain a second time-series signal with the same frequency as the face video signal.

8. A cross-device authentication device, characterized in that, An application is made to a terminal device connected to a main device. The terminal device is equipped with a physiological signal sensor for collecting real-time dynamic physiological signals of the human body. The main device is pre-unlocked by the user through authentication. The device includes: The sending unit is configured to send a contact signal to the master device in response to a user's contact if there is currently no terminal device in an unlocked state; the contact signal indicates that the user is in contact with the terminal device. The acquisition unit is used to acquire the user's second physiological signal using the physiological signal sensor and send the second physiological signal to the main device; the second physiological signal includes a PPG waveform signal. The receiving unit is used to receive the authentication information sent by the master device and enter the unlock state; The various terminal devices are interconnected, and the device further includes: An identity transmission unit, when in an unlocked state, responds to receiving a contact signal from a target device in a pending unlock state, collects a user's third physiological signal using the physiological signal sensor, and receives a fourth physiological signal collected by the target device using the same sensor. The contact signal indicates that the user is in contact with the target device. Both the third and fourth physiological signals are PPG waveform signals. The third and fourth physiological signals are preprocessed to obtain a third time-series signal and a fourth time-series signal. Fourier transforms are performed on the third and fourth time-series signals to obtain a third single-valued signal and a fourth single-valued signal. The unit verifies whether the third and fourth time-series signals are consistent, and whether the third and fourth single-valued signals are consistent. If the third and fourth time-series signals are consistent, and the third and fourth single-valued signals are consistent, the unit sends the identity authentication information to the target device, causing the target device to enter an unlocked state.

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