Password verification method, device and equipment and computer readable storage medium

Abstract

The application discloses a password verification method and device, equipment and a computer readable storage medium. Wherein, the method is applied to a wearable smart device, including: in response to the trigger operation of password verification, displaying a password input interface, the password input interface includes a plurality of text type characters and their one-to-one corresponding numerical type characters, and the plurality of text type characters have different pronunciations; in response to the voice input of the user selecting a plurality of target characters in the plurality of text type characters, determining the voice information input by the user; performing voice recognition on the voice information to determine the text type character password; based on the corresponding relationship between the text type character and the numerical type character, converting the text type character password into the numerical type character password; and sending the numerical type character password to the password verification system to enable the password verification system to verify the numerical type character password. According to the embodiment of the application, the password security and the password input convenience can be ensured at the same time in the password verification process.

Description

Technical Field

[0001] The present application belongs to the field of intelligent visual payment technology, and in particular relates to a password verification method, device, equipment and computer-readable storage medium. Background Art

[0002] In smart visual payment scenarios, wearable smart devices can interact with users through eye tracking, gestures, voice, and other methods to collect user payment intent, payment amount, and user identity information. They then verify the user's identity information and, if verified, complete the payment based on the user's payment intent and amount. User identity verification can be achieved through traditional digital password authentication. As a classic, secure, and time-tested authentication method, digital passwords demonstrate strong compatibility and stability in smart visual payment scenarios.

[0003] Traditional digital password verification methods typically verify passwords entered by users on a physical or virtual keyboard. However, these methods carry the risk of password leakage during the input process, resulting in low password security. Furthermore, the limited screen area and compact layout of physical or virtual keyboards can easily lead to accidental touches, making input difficult for users.

[0004] Therefore, there is an urgent need for a password verification method that can simultaneously ensure password security and password input convenience. Summary of the Invention

[0005] The embodiments of the present application provide a password verification method, apparatus, device, computer-readable storage medium, and computer program product, which can simultaneously ensure password security and password input convenience during the password verification process.

[0006] In a first aspect, an embodiment of the present application provides a password verification method, which is applied to a wearable smart device, and the method includes:

[0007] In response to a triggering operation for password verification, displaying a password input interface, the password input interface including a virtual keyboard, the virtual keyboard including a plurality of text characters and their one-to-one corresponding numeric characters, the correspondence between the text characters and the numeric characters being generated based on system time, a target user identifier, and a random number, the target user identifier being a user identifier bound to the wearable smart device, the plurality of text characters having different pronunciations;

[0008] In response to a user's voice input of selecting a plurality of target characters from the plurality of text characters, determining voice information input by the user;

[0009] Performing voice recognition on the voice information to determine a text-based character password;

[0010] Based on the correspondence between the text characters and the numeric characters, converting the text character password into a numeric character password;

[0011] The numerical character password is sent to a password verification system so that the password verification system verifies the numerical character password.

[0012] In one possible implementation, after responding to the triggering operation of password verification and before displaying the password input interface, the method further includes:

[0013] Acquire a text character set, a plurality of numeric characters, the system time, the target user identifier, and the random number, wherein the text character set includes a plurality of the text characters;

[0014] Encrypting the plurality of numerical characters based on the system time, the target user identifier, and the random number to obtain a plurality of first encrypted information;

[0015] Acquire, from the text character set, the plurality of text characters having different pronunciations that respectively correspond to the plurality of first encrypted information;

[0016] Mapping the plurality of numeric characters to the plurality of text characters to obtain a correspondence between the plurality of numeric characters and the plurality of text characters;

[0017] The virtual keyboard is determined based on a correspondence between the plurality of numeric characters and the plurality of text characters.

[0018] In a possible implementation, the encrypting the multiple numeric characters based on the system time, the target user identifier, and the random number to obtain multiple first encrypted information includes:

[0019] Generate a target key based on the system time, the target user identifier and the random number through a hash algorithm;

[0020] Based on the Advanced Encryption Standard algorithm, the target key is used to encrypt the multiple numeric characters to obtain the multiple first encrypted information.

[0021] In a possible implementation, converting the text-based password into a numeric-based password based on the correspondence between the text-based characters and the numeric-based characters includes:

[0022] Based on the correspondence between the text characters and the first encryption information, the text character password is converted into an encryption information sequence, where the encryption information sequence includes the plurality of first encryption information;

[0023] Based on the Advanced Encryption Standard algorithm, the encrypted information sequence is decrypted to obtain the numerical character password.

[0024] In a possible implementation, sending the numeric character password to a password verification system includes:

[0025] Encrypting the numerical character password to obtain second encrypted information;

[0026] The second encrypted information is sent to the password verification system.

[0027] In a possible implementation, in response to a user's voice input of selecting a plurality of target characters from the plurality of text characters, determining the voice information input by the user includes:

[0028] authenticating the user and obtaining a verification result;

[0029] If the verification result is that the verification is passed, receiving a voice input of the user selecting a plurality of target characters from the plurality of text characters;

[0030] In response to the voice input, voice information of the user input is determined.

[0031] In a possible implementation, performing voice recognition on the voice information to determine the text-based character password includes:

[0032] Inputting the speech information into a speech recognition model;

[0033] The voice information is subjected to voice recognition by the voice recognition model to determine the text-based character password.

[0034] In a possible implementation, the speech information is a time domain signal, and inputting the speech information into a speech recognition model includes:

[0035] Converting the speech information from the time domain signal to a frequency domain signal through fast Fourier transform;

[0036] extracting spectral features from the frequency domain signal;

[0037] The spectral features are input into the speech recognition model.

[0038] In one possible implementation, the speech recognition model includes a convolutional layer, an attention layer, a pooling layer, and a fully connected layer; performing speech recognition on the speech information by the speech recognition model to determine the text-based character password includes:

[0039] Performing a convolution operation on the spectral features through the convolution layer to obtain a first feature map;

[0040] Downsampling the first feature map through the pooling layer to obtain a second feature map;

[0041] Determining weights of features in the second feature map by the attention layer;

[0042] Mapping the features in the second feature map to a plurality of text characters and probabilities corresponding to the plurality of text characters based on weights of the features in the second feature map through an activation function in the fully connected layer;

[0043] The text-type character password is determined based on the plurality of text-type characters and the probabilities corresponding to the plurality of text-type characters.

[0044] In a possible implementation, before inputting the speech information into the speech recognition model, the method further includes:

[0045] Acquire multiple training samples, each of the training samples includes a first voice information sample and a corresponding first character label;

[0046] Inputting the first voice information sample into an initial voice recognition model to perform voice recognition on the first voice information sample through the initial voice recognition model to obtain a first predicted character;

[0047] Determining a loss function value based on the similarity between the first predicted character and the first character label;

[0048] When the loss function value does not meet the preset training stop condition, the first model parameter of the initial speech recognition model is adjusted based on the back propagation algorithm, and the process of inputting the first speech information sample into the initial speech recognition model is returned to execute, so as to perform speech recognition on the first speech information sample through the initial speech recognition model to obtain the first predicted character, until the loss function value meets the preset training stop condition, and the trained speech recognition model is obtained.

[0049] In a possible implementation, after obtaining the trained speech recognition model, the method further includes:

[0050] Acquire multiple test samples, each of the test samples including a second voice information sample and its corresponding second character label;

[0051] Inputting the second voice information sample into the voice recognition model to perform voice recognition on the second voice information sample through the voice recognition model to obtain a second predicted character;

[0052] determining a character error rate based on similarities between a plurality of second predicted characters and their corresponding first character labels;

[0053] When the character error rate is greater than a preset threshold, the second model parameter of the speech recognition model is adjusted, and the step of inputting the second speech information sample into the speech recognition model is returned to perform speech recognition on the second speech information sample through the speech recognition model to obtain a second predicted character until the character error rate is less than or equal to the preset threshold.

[0054] In a second aspect, an embodiment of the present application provides a password verification device, which is applied to a wearable smart device, and the device includes:

[0055] a display module, configured to display a password input interface in response to a triggering operation for password verification, the password input interface including a virtual keyboard, the virtual keyboard including a plurality of text characters and corresponding numeric characters, the correspondence between the text characters and the numeric characters being generated based on system time, a target user identifier, and a random number, the target user identifier being a user identifier bound to the wearable smart device, the plurality of text characters having different pronunciations;

[0056] a first determining module, configured to determine the voice information input by the user in response to a voice input of the user selecting a plurality of target characters from the plurality of text characters;

[0057] A second determining module is used to perform voice recognition on the voice information to determine the text-based character password;

[0058] A conversion module, configured to convert the text-type character password into a numeric character password based on a correspondence between the text-type character and the numeric character;

[0059] The sending module is used to send the numerical character password to a password verification system so that the password verification system verifies the numerical character password.

[0060] In a third aspect, an embodiment of the present application provides an electronic device, the device comprising: a processor and a memory storing computer program instructions;

[0061] When the processor executes the computer program instructions, the method in any possible implementation method of the first aspect described above is implemented.

[0062] In a fourth aspect, an embodiment of the present application provides a computer-readable storage medium having computer program instructions stored thereon. When the computer program instructions are executed by a processor, the method of any possible implementation method in the first aspect described above is implemented.

[0063] In a fifth aspect, an embodiment of the present application provides a computer program product. When the instructions in the computer program product are executed by a processor of an electronic device, the electronic device executes a method as any possible implementation method in the first aspect above.

[0064] The embodiment of the present application can ensure the security of the correspondence between text characters and numerical characters by displaying multiple text characters and their one-to-one corresponding numerical characters in the password input interface of the wearable smart device, and can also enable the user who enters the password to clearly understand the encryption information corresponding to the actual numerical character password (i.e., the text character password). Since multiple text characters have different pronunciations, by responding to the voice input of the user selecting multiple target characters from multiple text characters, determining the voice information input by the user, performing voice recognition on the voice information, determining the text character password, and converting the text character password into a numerical character password based on the correspondence between the text characters and the numerical characters, it is possible to input the password through voice interaction. On the one hand, the user can enter the password without manually operating the password keyboard, thereby improving the convenience of password input; on the other hand, since the user who does not wear the wearable smart device cannot know the correspondence between the text characters and the numerical characters, the password security can be guaranteed. In addition, by generating a correspondence between text characters and numeric characters based on the system time, the target user identifier, and a random number, that is, each time a password verification trigger operation is triggered, the displayed virtual keyboard is different, which increases the difficulty of guessing or cracking the password, and further improves the password security. In this way, by receiving the encrypted password information (i.e., the text character password) input by the user's voice and sending the decrypted numeric character password to the password verification system so that the password verification system verifies the numeric character password, it is possible to simultaneously ensure password security and password input convenience during the password verification process. BRIEF DESCRIPTION OF THE DRAWINGS

[0065] In order to more clearly illustrate the technical solutions of the embodiments of the present application, the following is a brief introduction to the drawings required for use in the embodiments of the present application. For ordinary technicians in this field, other drawings can be obtained based on these drawings without any creative work.

[0066] Figure 1This is a schematic diagram of an embodiment of the present application providing a method of scanning a merchant's QR code using smart glasses and implementing a payment process;

[0067] Figure 2 This is a flowchart of a password verification method provided in an embodiment of the present application;

[0068] Figure 3 This is a schematic diagram of a password verification method provided in an embodiment of the present application;

[0069] Figure 4 This is a schematic diagram of the structure of a password verification device provided in an embodiment of the present application;

[0070] Figure 5 This is a structural diagram of an electronic device provided in an embodiment of the present application. DETAILED DESCRIPTION

[0071] The features and exemplary embodiments of various aspects of the present application will be described in detail below. In order to make the purpose, technical solutions and advantages of the present application clearer, the present application will be further described in detail below in conjunction with the accompanying drawings and specific embodiments. It should be understood that the specific embodiments described herein are only intended to explain the present application, rather than to limit the present application. For those skilled in the art, the present application can be implemented without the need for some of these specific details. The following description of the embodiments is merely to provide a better understanding of the present application by illustrating the examples of the present application.

[0072] It should be noted that, in this document, relational terms such as first and second, etc., are used only to distinguish one entity or operation from another entity or operation, and do not necessarily require or imply any actual relationship or order between these entities or operations. Moreover, the terms "comprises," "comprising," or any other variants thereof are intended to cover non-exclusive inclusion, so that a process, method, article, or device comprising a series of elements includes not only those elements, but also other elements not explicitly listed, or elements inherent to such process, method, article, or device. In the absence of further limitations, the elements defined by the phrase "comprising..." do not exclude the presence of other identical elements in the process, method, article, or device comprising the elements.

[0073] In addition, the acquisition, storage, use, and processing of data in the technical solution of this application comply with the relevant provisions of national laws and regulations.

[0074] As described in the background technology section, in the smart visual payment scenario, wearable smart devices can interact with users through eye tracking, gestures, voice, etc., collect user payment intentions, payment amounts and user identity information, verify user identity information, and complete payment based on user payment intentions and payment amounts if the verification is successful.

[0075] The embodiment of the present application provides a schematic diagram of a payment process based on scanning a merchant QR code with smart glasses, which can be shown as follows: Figure 1 shown.

[0076] like Figure 1 As shown, smart glasses can scan the merchant's QR code to collect the user's payment intention and payment amount. Subsequently, in response to the user's confirmation of the payment intention and payment amount, the smart glasses can collect the user's identity information and send the user's payment intention, payment amount, and user identity information to the backend server. The backend server can analyze the user's payment intention using a large vertical model in the financial payment field, determine key payment information, and verify the user's identity information. If the identity is authenticated, the backend server encapsulates the key payment information and payment amount into a specified protocol format and sends it to the payment server, which then completes the payment process and returns the payment result to the smart glasses, the acquiring institution, and the merchant.

[0077] In the existing technology, user identity information verification can be achieved through traditional digital password verification methods, as well as biometric recognition methods such as fingerprint recognition, face recognition, voiceprint recognition, and iris recognition.

[0078] Specifically, existing user identity information verification methods include:

[0079] (1) Enter a numeric password using a traditional keyboard and verify the numeric password. Traditional keyboards include physical keyboards on standard computers and virtual keyboards on mobile devices.

[0080] (2) Biometric identification method: If supported by specific banks or specific terminal manufacturers, users can authenticate their identities through biometric information such as fingerprints and faces, thereby eliminating the need to enter a payment password.

[0081] The existing technology has the following shortcomings or problems:

[0082] (1) Traditional keyboard input: There is a risk of password leakage. Passwords entered directly through a traditional keyboard are easily recorded by hackers, and peepers may be able to infer the password by observing the position of the keyboard taps. In addition, using a traditional keyboard to enter passwords on mobile devices is prone to accidental touches due to the limited screen area and compact keyboard layout. Some wearable smart devices cannot be equipped with traditional keyboards, making user input difficult.

[0083] (2) Biometric identification method:

[0084] Fingerprint recognition: Fingerprint recognition technology is widely used due to its convenience and high recognition rate. However, its popularity and application are limited by the support of card-issuing banks. Currently, not all banks have integrated or fully support fingerprint verification functions. This lack of uniformity in verification methods can lead to compatibility issues when users use wearable smart devices for payment, thus affecting the universality and user experience of fingerprint recognition. In addition, fingerprint recognition faces security challenges, such as the risk of fingerprint template theft or duplication, and the potential for recognition failure in certain special circumstances (such as injured or wet fingers), which limit its wider application.

[0085] Facial recognition: In the field of digital payment and security verification, facial recognition technology is relatively mature and widely used, but it still has limitations as a single-factor verification condition. Because facial recognition technology is easily affected by factors such as light, angle, and obstructions, it is difficult to ensure sufficient security by relying solely on facial recognition as a means of verification. Therefore, in digital scenarios, facial recognition often needs to be used in combination with other verification methods (such as passwords, SMS verification codes, etc.). In addition, when facial recognition technology is applied to visual intelligent payment scenarios, especially when the camera is integrated into the glasses worn by the user, not only may the wearer's behavior (such as turning the head or lowering the head) cause difficulties in collection, but it may also cause users to worry about privacy leaks, because continuous facial capture may infringe on the user's personal privacy.

[0086] Voiceprint recognition: As an authentication technology based on voice characteristics, voiceprint recognition, while unique and non-replicable, is currently immature and has yet to achieve the stability and accuracy required for production-grade applications. Voiceprint recognition is susceptible to factors such as ambient noise, recording equipment quality, and speaker emotional fluctuations, resulting in high recognition error rates. Furthermore, the collection, storage, and processing of voiceprint data face stringent privacy protection and legal compliance requirements, all of which hinder the widespread application and commercialization of voiceprint recognition technology.

[0087] Iris recognition: Iris recognition technology, with its exceptionally high accuracy and stability, is considered one of the cutting-edge technologies in the biometrics field. However, its widespread use also carries potential health risks. Long-term, frequent use of iris recognition devices can cause discomfort or damage to the eyes, such as eye fatigue and dryness caused by strong light stimulation. Furthermore, the high cost of iris recognition technology, including equipment procurement, maintenance, and user education, has limited its widespread adoption in the general consumer market. Therefore, despite the unique advantages of iris recognition technology, practical applications still require a balance between security, convenience, and health risks.

[0088] In summary, in smart visual payment scenarios, traditional digital password input methods face the dual challenges of convenience and security. Although biometric recognition methods such as fingerprint recognition, facial recognition, and voiceprint recognition offer the potential for improving the payment experience, their application has certain limitations. Specifically, while fingerprint recognition is convenient, its widespread adoption requires support from the issuing bank. Not all banks nationwide are compatible with this feature, making it lacking universal applicability. Facial recognition cannot serve as a standalone verification method in digital payments, and when cameras are integrated into wearable devices such as glasses, the user's facial features become difficult to capture. Voiceprint recognition technology is still in its early stages of development and has not yet reached the maturity level for large-scale commercial use. As for iris recognition, despite its high accuracy, its potential impact on human health makes the risks of long-term use non-negligible.

[0089] As a classic, secure, and time-tested authentication method, digital passwords have demonstrated strong compatibility and stability in the field of intelligent visual payments, especially in cross-border payment scenarios. They not only effectively guarantee transaction security but also enable seamless integration across diverse payment environments and systems, making them an indispensable security verification method in today's technological landscape.

[0090] However, traditional digital password verification methods carry the risk of password leakage during password entry, resulting in low password security. Furthermore, due to the limited screen area of ​​physical or virtual keyboards and the compact keyboard layout, accidental touches are easily caused, making user input difficult.

[0091] Therefore, there is an urgent need for a password verification method that can simultaneously ensure password security and password input convenience.

[0092] Thus, in order to solve the problems of the prior art, the embodiments of the present application provide a password verification method, apparatus, device, computer-readable storage medium, and computer program product. The password verification method can be applied to scenarios where wearable smart devices are used for payment.

[0093] The following first introduces the password verification method provided in the embodiment of the present application.

[0094] Figure 2 FIG1 shows a flow chart of a password verification method provided by an embodiment of the present application. The password verification method can be executed by a wearable smart device. Figure 2 As shown, the password verification method provided in the embodiment of the present application includes the following steps:

[0095] S210: In response to a triggering operation for password verification, displaying a password input interface, the password input interface including a virtual keyboard, the virtual keyboard including a plurality of text characters and their one-to-one corresponding numeric characters, the correspondence between the text characters and the numeric characters being generated based on system time, a target user identifier, and a random number, the target user identifier being a user identifier bound to the wearable smart device, the plurality of text characters having different pronunciations;

[0096] S220, in response to a user's voice input of selecting a plurality of target characters from a plurality of text characters, determining voice information input by the user;

[0097] S230, performing voice recognition on the voice information to determine the text-based character password;

[0098] S240, based on the correspondence between text characters and numeric characters, convert the text character password into a numeric character password;

[0099] S250: Send the numeric character password to the password verification system, so that the password verification system verifies the numeric character password.

[0100] The embodiment of the present application can ensure the security of the correspondence between text characters and numerical characters by displaying multiple text characters and their one-to-one corresponding numerical characters in the password input interface of the wearable smart device, and can also enable the user who enters the password to clearly understand the encryption information corresponding to the actual numerical character password (i.e., the text character password). Since multiple text characters have different pronunciations, by responding to the voice input of the user selecting multiple target characters from multiple text characters, determining the voice information input by the user, performing voice recognition on the voice information, determining the text character password, and converting the text character password into a numerical character password based on the correspondence between the text characters and the numerical characters, it is possible to input the password through voice interaction. On the one hand, the user can enter the password without manually operating the password keyboard, thereby improving the convenience of password input; on the other hand, since the user who does not wear the wearable smart device cannot know the correspondence between the text characters and the numerical characters, the password security can be guaranteed. In addition, by generating a correspondence between text characters and numeric characters based on the system time, the target user identifier, and a random number, that is, each time a password verification trigger operation is triggered, the displayed virtual keyboard is different, which increases the difficulty of guessing or cracking the password, and further improves the password security. In this way, by receiving the encrypted password information (i.e., the text character password) input by the user's voice and sending the decrypted numeric character password to the password verification system so that the password verification system verifies the numeric character password, it is possible to simultaneously ensure password security and password input convenience during the password verification process.

[0101] The specific implementation methods of the above steps are introduced below.

[0102] In some embodiments, in S210, in the payment scenario, the triggering operation of password verification may be an operation in which the user confirms payment. In addition, the password input interface may be an interface presented on the display panel of a wearable smart device using projection technology. The password input interface may include a virtual keyboard. The virtual keyboard may include a plurality of text characters and their one-to-one corresponding numerical characters, and the plurality of text characters have different pronunciation codes. Specifically, the virtual keyboard may include a plurality of virtual controls, each of which may correspond to a text character and a numerical character corresponding to the text character. The text character may be at least one of Chinese characters and English letters. The numerical characters may include the numbers 0-9.

[0103] In addition, the correspondence between text characters and numeric characters in the virtual keyboard can be generated based on the system time, the target user ID, and a random number. The system time can be the system time of the wearable smart device. The target user ID can be a user ID that is bound to the wearable smart device.

[0104] In the embodiment of the present application, since the system time is constantly changing and the password generated each time may be different, the correspondence between text characters and numeric characters is generated based on the system time, the target user identifier and the random number, that is, each time in response to the triggering operation of password verification, the displayed virtual keyboard is different, which increases the difficulty of guessing or cracking the password and improves the password security.

[0105] Based on this, in order to increase the difficulty of guessing or cracking the password and improve the security of the password, in some embodiments, after the triggering operation in response to the password verification and before displaying the password input interface, the method may further include:

[0106] Obtain a text character set, multiple numeric characters, system time, target user ID, and a random number, where the text character set includes multiple text characters;

[0107] Encrypting multiple numeric characters based on system time, target user identifier, and random number to obtain multiple first encrypted information;

[0108] Acquire, from a text character set, a plurality of text characters having different pronunciations and corresponding to the plurality of first encrypted information;

[0109] Mapping multiple numeric characters to multiple text characters to obtain a correspondence between the multiple numeric characters and the multiple text characters;

[0110] A virtual keyboard is determined based on a correspondence between a plurality of numeric characters and a plurality of text characters.

[0111] Here, the text character set can include multiple Chinese characters and English letters. Based on scenario requirements, the types and number of text characters in the text character set can be continuously adjusted, and symbols can be added to the text character set to meet more complex security requirements and further improve password security. In addition, the multiple numeric characters can be numbers on the numeric keypad. The multiple numeric characters can include the numbers 0-9. In addition, the random number can be generated by a random number generator.

[0112] After obtaining multiple numeric characters, system time, target user identifier and random number, the multiple numeric characters can be encrypted based on the system time, target user identifier and random number to obtain multiple first encrypted information. Each numeric character can correspond to one first encrypted information. After obtaining the first encrypted information, the first encrypted information can be used as an index or seed to randomly select multiple text characters corresponding to the multiple first encrypted information from the text character set. The multiple text characters obtained at this time may have the same pronunciation or may have different pronunciations. If any two text characters have the same pronunciation, the multiple text characters corresponding to the multiple first encrypted information can be reselected until the pronunciations of the multiple text characters are different. The method for determining whether the pronunciations of multiple text characters are the same can be to pre-assign a pronunciation code corresponding to the pronunciation to each text character, and determine whether the pronunciations are the same by checking the pronunciation code.

[0113] Furthermore, to ensure that the multiple text characters corresponding to the multiple first encrypted information have different pronunciations, multiple sub-text character sets may be pre-generated based on the text character set. The sub-text character sets may include multiple text characters with different pronunciations, and the number of text character sets may be the same as the number of first confidential information. In this manner, obtaining multiple text characters with different pronunciations corresponding to the multiple first encrypted information from the text character set may specifically include: selecting a sub-text character set from the multiple sub-text character sets, and randomly determining the correspondence between the multiple text characters in the sub-text character set and the multiple first encrypted information.

[0114] After determining multiple text-type characters with different pronunciations, multiple numeric characters in the numeric keyboard can be mapped to the above-mentioned multiple text-type characters, obtaining a correspondence between the multiple numeric characters and the multiple text-type characters, and determining a virtual keyboard based on the correspondence between the multiple numeric characters and the multiple text-type characters, and displaying the virtual keyboard on the display panel of the wearable smart device.

[0115] The embodiment of the present application first encrypts multiple numeric characters based on the system time, the target user identifier and the random number to obtain multiple first encrypted information, then uses the first encrypted information as an index or seed to randomly select text characters corresponding to the multiple numeric characters in the text character set, and determines the virtual keyboard based on the correspondence between the multiple numeric characters and the multiple text characters. That is, through the dynamic encryption mapping mechanism, it is possible to achieve that each time a trigger operation in response to password verification is triggered, the displayed virtual keyboard is different, which increases the difficulty of guessing or cracking the password and improves the security of the password. In addition, by first generating the first encrypted information of the numeric character and then using the first encrypted information as an index or seed to determine the text character corresponding to the numeric character, the difficulty of password reverse deduction is increased compared to directly determining the correspondence between the numeric character and the text character, thereby improving the security of the password.

[0116] Based on this, in order to ensure the randomness and security of the correspondence between numeric characters and text characters, in some embodiments, the above-mentioned encryption of multiple numeric characters based on the system time, the target user identifier and the random number to obtain multiple first encrypted information may specifically include:

[0117] Generate the target key based on the system time, target user ID and random number through the hash algorithm;

[0118] Based on the Advanced Encryption Standard algorithm, a target key is used to encrypt a plurality of numeric characters to obtain a plurality of first encrypted information.

[0119] Here, the hash algorithm can be, for example, a Secure Hash Algorithm (SHA). Using a hash algorithm (such as SHA-256) with the system time, target user ID, and a random number generator as input, a sufficiently long target key can be generated for subsequent cryptographic mapping generation, ensuring that each operation is unique.

[0120] In addition, the wearable smart device may include a secure storage environment. The secure storage environment may include a hardware security module (HSM) and a secure memory area. A hardware security module is a computer hardware device used to protect and manage keys used in strong authentication systems and provide related cryptographic operations. After generating a target key, the target key may be stored in the secure storage environment to ensure its security. Furthermore, by adding a tamper-proof mechanism to the wearable smart device, the firmware and operating system of the wearable smart device can be protected from tampering.

[0121] For example, by encrypting multiple numeric characters (such as numbers 0-9) using a target key based on the Advanced Encryption Standard (AES) algorithm, first encrypted information corresponding to the numbers 0-9 can be obtained.

[0122] On this basis, when the first encrypted information is used as an index or seed and multiple text characters corresponding to multiple first encrypted information are randomly selected from the text character set, if any two text characters have the same pronunciation, the above-mentioned process of generating the target key and after generating the target key can be returned to execute until the pronunciations of the multiple text characters are all different.

[0123] The embodiment of the present application uses a hash algorithm and an Advanced Encryption Standard algorithm to encrypt multiple numeric characters based on system time, target user identification and random numbers, thereby ensuring the randomness and security of the correspondence between subsequently generated numeric characters and text characters.

[0124] In some embodiments, in S220, after the password input interface is displayed on the wearable smart device, the user can see multiple text characters and their corresponding numeric characters, and enter the text character password by voice. The text character password may include multiple target characters and the order of the multiple target characters. Since the user who is not wearing the wearable smart device has no way of knowing the correspondence between the text characters and the numeric characters, the user's voice input of the text character password will not leak the password.

[0125] As an example, a wearable smart device may be equipped with a microphone, which may collect voice information input by a user.

[0126] Since other people's voice information may also be collected during the process of collecting voice information, in order to improve the success rate of password verification, in some embodiments, the above S220 may specifically include:

[0127] Authenticate the user and obtain the verification result;

[0128] If the verification result is that the verification is passed, receiving a voice input of the user selecting multiple target characters from multiple text characters;

[0129] In response to the voice input, voice information input by the user is determined.

[0130] Here, the identity authentication may include at least one of fingerprint recognition verification and personal identification number (PIN code) two-factor verification.

[0131] The embodiment of the present application receives the text character password input by the user's voice when the user identity authentication is passed, which can ensure that the password obtained in the subsequent password decryption, password transmission, etc. is the password input by the user wearing the wearable smart device, thereby improving the success rate of password verification.

[0132] In some embodiments, in S230 , after the voice information is collected, voice recognition may be performed on the voice information to determine the text character password input by the user.

[0133] To ensure the accuracy of the text-based character password, in some embodiments, the above S230 may specifically include:

[0134] Input the speech information into the speech recognition model;

[0135] The speech information is recognized through the speech recognition model to determine the text-based character password.

[0136] Here, the speech recognition model can be a pre-trained neural network model for speech recognition. The speech recognition model can specifically be a convolutional neural network (CNN) model based on the attention mechanism. The speech recognition model may include a convolutional layer, an attention layer, a pooling layer, and a fully connected layer. Among them, the attention layer can follow the convolutional layer, the pooling layer can follow the attention layer, and the fully connected layer can follow the pooling layer. In addition, the relative position relationship between the convolutional layer, the attention layer, the pooling layer, and the fully connected layer can also be: the pooling layer follows the convolutional layer, the attention layer follows the pooling layer, and the fully connected layer can follow the attention layer, which is not limited here.

[0137] As an example, the above-trained speech recognition model and password security control can be deployed in a wearable smart device. After the user enters voice information using the virtual keyboard, the voice information can be collected in real time through the microphone and input into the speech recognition model for speech recognition. After the speech recognition generates a text-based character password, the text-based character password can be fed back to the password security control in text or other form.

[0138] The embodiment of the present application performs speech recognition on the speech information through the above-mentioned speech recognition model to determine the text-based character password, which can ensure the accuracy of the text-based character password.

[0139] To further improve the accuracy of text-based character passwords, before inputting the speech information into the speech recognition model, filtering technology can be used to remove background noise from the speech information. The continuous speech signal can then be segmented into multiple shorter frames (e.g., 20-30 milliseconds) for subsequent processing. In addition, window functions such as Hamming windows or Hanning windows can be used to weight each frame to reduce discontinuities at frame boundaries.

[0140] On this basis, since the collected speech signal is a time domain signal, and the phonemes, pitch, timbre and other characteristics of the speech signal can be more easily analyzed and identified in the frequency domain, each of the above windowed frames can also be subjected to a Fast Fourier Transform (FFT) to decompose the time domain signal into the sum of a series of sine waves of different frequencies to obtain a frequency domain signal, and then perform speech recognition based on the frequency domain signal.

[0141] Based on this, in order to further improve the accuracy of text-based character passwords, in some embodiments, the above-mentioned input of voice information into the voice recognition model may specifically include:

[0142] Through fast Fourier transform, the speech information is converted from time domain signal to frequency domain signal;

[0143] Extract spectral features from frequency domain signals;

[0144] The spectral features are fed into the speech recognition model.

[0145] Here, the Fast Fourier Transform (FFT) not only converts speech information from the time domain into the frequency domain, but also simultaneously reduces the noise of the speech signal. Since noise is typically distributed over a wide frequency range, while speech signals are concentrated within a specific frequency band, the FFT can also suppress noise by filtering out the noise frequency components in the frequency domain. Furthermore, after obtaining the frequency domain signal, the amplitude and phase of each frequency component can be adjusted to further enhance the clarity and intelligibility of the speech signal.

[0146] In this way, by extracting spectral features from the frequency domain signal and inputting the spectral features into the speech recognition model, and then performing speech recognition on the spectral features through the speech recognition model to determine the text-based character password, the accuracy of the text-based character password can be further improved.

[0147] On this basis, in order to further improve the accuracy of the text-based character password, in some embodiments, the above-mentioned voice recognition of the voice information by the voice recognition model to determine the text-based character password may specifically include:

[0148] Perform convolution operation on the spectral features through the convolution layer to obtain the first feature map;

[0149] Downsample the first feature map through the pooling layer to obtain the second feature map;

[0150] Determine the weights of the features in the second feature map through the attention layer;

[0151] Mapping the features in the second feature map to a plurality of text characters and probabilities corresponding to the plurality of text characters based on the weights of the features in the second feature map through an activation function in the fully connected layer;

[0152] A text character password is determined based on a plurality of text characters and respective corresponding probabilities of the plurality of text characters.

[0153] Here, the convolution layer can use multiple convolution kernels (also called filters) to perform convolution operations on the spectral features to generate a first feature map. The first feature map may include local feature information of the spectral features. The pooling layer can be used to downsample the first feature map to reduce the dimension and computational complexity of the data while retaining key information to obtain a second feature map. The attention layer can dynamically adjust the weights of different time steps or feature channels so that the model pays more attention to important speech segments, and ultimately obtains the weights of the features in the second feature map. In addition, the fully connected layer can be used to map the features in the second feature map to a text-type character password. Specifically, the activation function can be a softmax function, and the fully connected layer can use the softmax function to convert the outputs of the convolution layer and the pooling layer into a probability distribution to represent the possibility of different categories (i.e., which text-type character), and determine the text-type character password based on the probability distribution.

[0154] The embodiment of the present application can further improve the accuracy of the text-based character password by determining the weights of the features in the second feature map based on the attention layer, and determining the text-based character password based on the weights of the features in the second feature map.

[0155] Based on this, in order to determine the text-based character password through the speech recognition model, in some embodiments, before inputting the speech information into the speech recognition model, the method may further include:

[0156] Acquire multiple training samples, each training sample including a first voice information sample and its corresponding first character label;

[0157] Inputting the first voice information sample into an initial voice recognition model to perform voice recognition on the first voice information sample through the initial voice recognition model to obtain a first predicted character;

[0158] Determining a loss function value based on the similarity between the first predicted character and the first character label;

[0159] When the loss function value does not meet the preset training stop condition, the first model parameter of the initial speech recognition model is adjusted based on the back propagation algorithm, and the execution returns to input the first speech information sample into the initial speech recognition model, so as to perform speech recognition on the first speech information sample through the initial speech recognition model to obtain the first predicted character, until the loss function value meets the preset training stop condition, and a trained speech recognition model is obtained.

[0160] Here, the first character label can be a text-type character label, and the first character label can include Chinese characters and English letters. The first voice information sample can be a voice information input by the user based on the first character label. The initial voice recognition model can be a voice recognition model trained using multiple training samples. In addition, the risk of model overfitting can be reduced by adding an L2 policy to the model's loss function. In addition, during the model training process, the generalization ability of the model can be improved by methods such as data enhancement and regularization technology (dropout).

[0161] The embodiment of the present application obtains a trained speech recognition model by training an initial speech recognition model based on a first speech information sample and its corresponding first character label, and can determine a text-based character password through the speech recognition model.

[0162] Based on this, in order to improve the accuracy and robustness of speech recognition, in some embodiments, after obtaining the trained speech recognition model, the method may further include:

[0163] Acquire multiple test samples, each test sample including a second voice information sample and its corresponding second character label;

[0164] Inputting the second voice information sample into the voice recognition model to perform voice recognition on the second voice information sample through the voice recognition model to obtain a second predicted character;

[0165] determining a character error rate based on similarities between the plurality of second predicted characters and their corresponding first character labels;

[0166] When the character error rate is greater than the preset threshold, the second model parameters of the speech recognition model are adjusted, and the execution returns to input the second speech information sample into the speech recognition model to perform speech recognition on the second speech information sample through the speech recognition model to obtain a second predicted character until the character error rate is less than or equal to the preset threshold.

[0167] Here, the second character label may be a text-type character label, and the second character label may include Chinese characters and English letters. The second voice information sample may be voice information entered by the user based on the second character label. In addition, the character error rate may include at least one of a word error rate (WER) and a character error rate (CER).

[0168] The embodiments of the present application evaluate the performance of the model by calculating indicators such as word error rate (WER) or character error rate (CER), and tune the model according to the evaluation results, thereby improving the accuracy and robustness of speech recognition.

[0169] In some embodiments, in S240, as described above, after determining the text-based password, the text-based password may be transmitted to a password security control. The password security control may perform an inverse operation based on the correspondence between the text-based characters and the numeric characters to map the text-based password back to the original numeric character password.

[0170] In addition, as described above, the method for generating the correspondence between text characters and numeric characters can be: first, using the Advanced Encryption Standard algorithm, use the target key to encrypt multiple numeric characters to obtain multiple first encrypted information, and then use the first encrypted information as an index or seed to randomly obtain text characters corresponding to the multiple first encrypted information in the text character set to obtain the correspondence between text characters and numeric characters.

[0171] Therefore, in some embodiments, the above S240 may specifically include:

[0172] Based on the correspondence between the text characters and the first encrypted information, the text character password is converted into an encrypted information sequence, where the encrypted information sequence includes a plurality of first encrypted information;

[0173] Based on the Advanced Encryption Standard algorithm, the encrypted information sequence is decrypted to obtain a numerical character password.

[0174] Here, the password security control may store an Advanced Encryption Standard algorithm. The algorithm used to decrypt the encrypted information sequence may be the same as the algorithm used to encrypt the numeric characters. By first converting the text-based character password into an encrypted information sequence and then decrypting the encrypted information sequence based on the Advanced Encryption Standard algorithm, the text-based character password can be restored to a numeric character password.

[0175] In some embodiments, in S250, if the numeric password is a payment password, the password verification system may be a backend system of the issuing bank. After obtaining the numeric character password, the numeric character password may be sent to the password verification system so that the password verification system verifies and processes the numeric character password.

[0176] Based on this, in order to further improve password security, in some embodiments, the above S250 may specifically include:

[0177] Encrypting the numeric character password to obtain second encrypted information;

[0178] The second encrypted information is sent to the password verification system.

[0179] Here, the second encrypted information can specifically be obtained by encrypting the numerical character password using the Transport Layer Security (TLS) protocol or the Secure Sockets Layer (SSL) protocol. In addition, after obtaining the second encrypted information, the second encrypted information can also be sent to the password verification system through a secure channel.

[0180] In this way, by re-encrypting the numerical password during the password transmission process, the password security can be further improved.

[0181] In addition, the embodiments of the present application can also record key operations such as key access, password decryption and transmission requests during the password verification process for auditing and monitoring.

[0182] In order to better describe the entire solution, some specific examples are given based on the above embodiments.

[0183] For example, Figure 3 As shown, the wearable smart device in the embodiment of the present application may include a dynamic encryption mapping module, a voice recognition module, and a password security protection control. The dynamic encryption mapping module may, in response to a password verification trigger operation, call up a password input interface; generate a dynamic encryption mapping table (including the correspondence between text characters and the numerical characters) based on the system time, the target user identifier, and a random number; map multiple numerical characters on the numeric keypad to multiple text characters based on the dynamic encryption mapping table to obtain a virtual keyboard; and display the virtual keyboard.

[0184] It should be noted that, based on this approach, a new, unique encrypted mapping table is generated each time a user logs in or makes a transaction. The numeric keypad input is then converted in real time into a randomly assigned sequence of Chinese characters or letters, displayed on the wearable smart device's screen. To ensure security and uniqueness, the mapping between each number and corresponding Chinese character / letter is unique and pronounced differently for each transaction.

[0185] The speech recognition module also receives user input. A CNN speech recognition algorithm based on a self-attention mechanism performs a Fourier transform on the speech information to generate a frequency domain signal. Spectral features are extracted from the frequency domain signal. The speech recognition model then performs speech recognition based on the spectral features to generate a text-based character password. The speech recognition model automatically learns and extracts deep information from these spectral features, enabling accurate recognition of speech signals.

[0186] In addition, the password security protection control can receive a text character password; restore the text character password to a numeric character password; encrypt the numeric character password to obtain a second encrypted information; and send the second encrypted information to a password verification system to ensure the security and integrity of the password information.

[0187] In summary, this application proposes a random encryption mapping password input method based on voice interaction. In the payment scenario of wearable smart devices, this method uses projection technology to present the password input interface on the display panel of the wearable smart device, and adopts a dynamic random mapping mechanism to map the numeric keyboard to Chinese characters or English letters. It receives the encrypted characters (i.e., text-type character password) input by the user through efficient voice interaction, restores the text-type character password to the original numeric character password, and sends the numeric character password to the issuing bank for verification under the premise of ensuring full security encryption.

[0188] The invention points are as follows:

[0189] (1) Projection technology presents the password input interface on the display panel of the wearable smart device: Projection technology is used to enable the display panel of the wearable smart device to present the password input interface. This function is developed for the wearable smart device and uses its own display panel to carry the password input related display. It is different from the traditional operation on other fixed screens and is an invention point that is closely integrated with the hardware characteristics of smart glasses.

[0190] (2) Realizing password input on wearable smart devices based on voice interaction: Taking full advantage of the voice interaction feature of wearable smart devices, users can input encrypted characters through voice, which changes the conventional manual password input method. This allows users to complete password-related operations conveniently and efficiently on such wearable devices with relatively limited operation. This closely fits the usage of wearable smart devices and is its unique invention point.

[0191] (3) Dynamic random mapping mechanism is applied to password input of wearable smart devices: The dynamic random mapping mechanism is applied to wearable smart devices, the numeric keyboard is mapped to Chinese characters or English letters, and the encrypted mapping conversion of password input is realized in the display and interaction scenarios of wearable smart devices. This special password conversion mechanism is innovated in combination with wearable smart devices, making password input more secure and innovative.

[0192] Therefore, this application has the following advantages:

[0193] (1) By randomly mapping the numeric keypad to Chinese characters or letters, the mapping relationship is different each time it is used, which increases the difficulty of guessing or cracking the password. The dynamic random mapping mechanism can flexibly adjust the mapping rules.

[0194] (2) Using efficient voice interaction to input passwords, users do not need to manually operate the keyboard, especially on wearable smart devices (such as smart glasses). This method is more convenient and natural, reducing the complexity and inconvenience of manual operation. The built-in voice recognition algorithm combines the context to analyze the user's voice. The user can accurately recognize the user's voice input when inputting encrypted Chinese characters or English letters through voice.

[0195] (3) The encrypted voice input is accepted through the password security protection control, and the same encryption algorithm is used to restore it to the original digital password. The encrypted state is always maintained during the transmission to the issuing bank for verification, ensuring the security of the password information during transmission.

[0196] Based on the password verification method for a wearable smart device provided in the above embodiment, the present application also provides a specific implementation of a password verification apparatus for a wearable smart device. Please refer to the following embodiments.

[0197] like Figure 4 As shown, the password verification device 400 provided in this embodiment of the application includes the following modules:

[0198] Display module 410 is configured to display a password input interface in response to a password verification trigger operation, the password input interface including a virtual keyboard including a plurality of text characters and their corresponding numeric characters, wherein the correspondence between the text characters and the numeric characters is generated based on the system time, a target user identifier, and a random number, wherein the target user identifier is a user identifier associated with the wearable smart device, and the plurality of text characters have different pronunciations;

[0199] A first determining module 420 is configured to determine the voice information input by the user in response to the user's voice input of selecting a plurality of target characters from a plurality of text characters;

[0200] The second determination module 430 is used to perform voice recognition on the voice information to determine the text-based character password;

[0201] A conversion module 440 is configured to convert a text-based password into a numeric-based password based on a correspondence between text-based characters and numeric-based characters;

[0202] The sending module 450 is used to send the numeric character password to the password verification system, so that the password verification system verifies the numeric character password.

[0203] The password verification device 400 is described in detail below.

[0204] In some embodiments, the password verification device 400 may further include:

[0205] A first acquisition module is configured to acquire a text character set, a plurality of numeric characters, a system time, a target user identifier, and a random number after responding to a triggering operation for password verification and before displaying a password input interface, wherein the text character set includes a plurality of text characters;

[0206] An encryption module, configured to encrypt a plurality of numerical characters based on a system time, a target user identifier, and a random number to obtain a plurality of first encrypted information;

[0207] A second acquisition module is used to acquire, from a text character set, a plurality of text characters with different pronunciations corresponding to the plurality of first encrypted information;

[0208] A mapping module, used for mapping a plurality of numeric characters to a plurality of text characters, and obtaining a correspondence between the plurality of numeric characters and the plurality of text characters;

[0209] The third determining module is configured to determine a virtual keyboard based on a correspondence between a plurality of numerical characters and a plurality of text characters.

[0210] In some embodiments, the encryption module may specifically include:

[0211] A generation submodule, for generating a target key based on system time, target user ID and random number through a hash algorithm;

[0212] The first encryption submodule is configured to encrypt a plurality of numerical characters using a target key based on an Advanced Encryption Standard algorithm to obtain a plurality of first encrypted information.

[0213] In some embodiments, the conversion module 440 may specifically include:

[0214] A conversion submodule, configured to convert the text character password into an encrypted information sequence based on a correspondence between the text character and the first encrypted information, wherein the encrypted information sequence includes a plurality of first encrypted information;

[0215] The decryption submodule is used to decrypt the encrypted information sequence based on the Advanced Encryption Standard algorithm to obtain a numerical character password.

[0216] In some embodiments, the sending module 450 may specifically include:

[0217] A second encryption submodule is used to encrypt the numerical character password to obtain second encrypted information;

[0218] The sending submodule is used to send the second encrypted information to the password verification system.

[0219] In some embodiments, the first determining module 420 may specifically include:

[0220] The verification submodule is used to authenticate the user and obtain the verification result;

[0221] A receiving submodule, configured to receive a user's voice input of selecting a plurality of target characters from a plurality of text characters when the verification result is that the verification is passed;

[0222] The first determining submodule is configured to determine the voice information input by the user in response to the voice input.

[0223] In some embodiments, the second determining module 430 may specifically include:

[0224] A first input submodule, used to input speech information into the speech recognition model;

[0225] The second determination submodule is used to perform speech recognition on the speech information through a speech recognition model to determine the text-based character password.

[0226] In some embodiments, the voice information is a time domain signal. Based on this, the first input submodule may specifically include:

[0227] A conversion unit, configured to convert the speech information from a time domain signal into a frequency domain signal by fast Fourier transform;

[0228] An extraction unit, configured to extract spectrum features from a frequency domain signal;

[0229] Input unit, used to input spectral features into the speech recognition model.

[0230] In some embodiments, the speech recognition model includes a convolutional layer, an attention layer, a pooling layer, and a fully connected layer. Based on this, the second determination submodule may specifically include:

[0231] A convolution unit, configured to perform a convolution operation on the spectral features through a convolution layer to obtain a first feature map;

[0232] A sampling unit, configured to downsample the first feature map through a pooling layer to obtain a second feature map;

[0233] A first determining unit, configured to determine weights of features in the second feature map through an attention layer;

[0234] A mapping unit, configured to map the features in the second feature map to a plurality of text characters and probabilities corresponding to the plurality of text characters based on weights of the features in the second feature map through an activation function in the fully connected layer;

[0235] The second determining unit is configured to determine a text character password based on a plurality of text characters and respective probabilities corresponding to the plurality of text characters.

[0236] In some embodiments, the second determining module 430 may specifically include:

[0237] A first acquisition submodule is used to acquire a plurality of training samples before inputting the speech information into the speech recognition model, each training sample including a first speech information sample and its corresponding first character label;

[0238] a second input submodule, configured to input the first voice information sample into the initial voice recognition model, so as to perform voice recognition on the first voice information sample through the initial voice recognition model to obtain a first predicted character;

[0239] a third determination submodule, configured to determine a loss function value based on the similarity between the first predicted character and the first character label;

[0240] The training submodule is used to adjust the first model parameter of the initial speech recognition model based on the back propagation algorithm when the loss function value does not meet the preset training stop condition, and return to execute the input of the first speech information sample into the initial speech recognition model to perform speech recognition on the first speech information sample through the initial speech recognition model to obtain the first predicted character, until the loss function value meets the preset training stop condition, and a trained speech recognition model is obtained.

[0241] In some embodiments, the second determining module 430 may specifically include:

[0242] A second acquisition submodule is used to acquire a plurality of test samples after obtaining the trained speech recognition model, each test sample including a second speech information sample and its corresponding second character label;

[0243] a third input submodule, configured to input the second voice information sample into the voice recognition model, so as to perform voice recognition on the second voice information sample through the voice recognition model to obtain a second predicted character;

[0244] a fourth determining submodule, configured to determine a character error rate based on similarities between the plurality of second predicted characters and their corresponding first character labels;

[0245] The tuning submodule is used to adjust the second model parameters of the speech recognition model when the character error rate is greater than a preset threshold, and return to execute the second speech information sample input into the speech recognition model to perform speech recognition on the second speech information sample through the speech recognition model to obtain a second predicted character until the character error rate is less than or equal to the preset threshold.

[0246] The embodiment of the present application can ensure the security of the correspondence between text characters and numerical characters by displaying multiple text characters and their one-to-one corresponding numerical characters in the password input interface of the wearable smart device, and can also enable the user who enters the password to clearly understand the encryption information corresponding to the actual numerical character password (i.e., the text character password). Since multiple text characters have different pronunciations, by responding to the voice input of the user selecting multiple target characters from multiple text characters, determining the voice information input by the user, performing voice recognition on the voice information, determining the text character password, and converting the text character password into a numerical character password based on the correspondence between the text characters and the numerical characters, it is possible to input the password through voice interaction. On the one hand, the user can enter the password without manually operating the password keyboard, thereby improving the convenience of password input; on the other hand, since the user who does not wear the wearable smart device cannot know the correspondence between the text characters and the numerical characters, the password security can be guaranteed. In addition, by generating a correspondence between text characters and numeric characters based on the system time, the target user identifier, and a random number, that is, each time a password verification trigger operation is triggered, the displayed virtual keyboard is different, which increases the difficulty of guessing or cracking the password, and further improves the password security. In this way, by receiving the encrypted password information (i.e., the text character password) input by the user's voice and sending the decrypted numeric character password to the password verification system so that the password verification system verifies the numeric character password, it is possible to simultaneously ensure password security and password input convenience during the password verification process.

[0247] Based on the password verification method provided in the above embodiment, the embodiment of the present application also provides a specific implementation of the electronic device. Figure 5 A schematic diagram of an electronic device 500 provided in an embodiment of the present application is shown.

[0248] The electronic device 500 may include a processor 510 and a memory 520 storing computer program instructions.

[0249] Specifically, the processor 510 may include a central processing unit (CPU), or an application-specific integrated circuit (ASIC), or may be configured to implement one or more integrated circuits of the embodiments of the present application.

[0250] The memory 520 may include a large capacity memory for data or instructions. By way of example and not limitation, the memory 520 may include a hard disk drive (HDD), a floppy disk drive, a flash memory, an optical disk, a magneto-optical disk, a magnetic tape, or a universal serial bus (USB) drive, or a combination of two or more of these. Where appropriate, the memory 520 may include removable or non-removable (or fixed) media. Where appropriate, the memory 520 may be internal or external to the electronic device 500. In a particular embodiment, the memory 520 is a non-volatile solid-state memory.

[0251] The memory may include a read-only memory (ROM), a random access memory (RAM), a magnetic disk storage medium device, an optical storage medium device, a flash memory device, an electrical, optical or other physical / tangible memory storage device. Thus, generally, the memory includes one or more tangible (non-transitory) computer-readable storage media (e.g., a memory device) encoded with software including computer-executable instructions, and when the software is executed (e.g., by one or more processors), it is operable to perform the operations described with reference to the method according to the first aspect of the present application.

[0252] The processor 510 implements any one of the password verification methods in the above embodiments by reading and executing computer program instructions stored in the memory 520 .

[0253] In one example, the electronic device 500 may further include a communication interface 530 and a bus 540. Figure 5 As shown, the processor 510 , the memory 520 , and the communication interface 530 are connected via a bus 540 and communicate with each other.

[0254] The communication interface 530 is mainly used to implement communication between various modules, devices, units and / or equipment in the embodiments of the present application.

[0255] Bus 540 comprises hardware, software or both, couples the parts of electronic equipment to each other.For example, and not limitation, bus can comprise accelerated graphics port (AGP) or other graphics bus, enhanced industry standard architecture (EISA) bus, front side bus (FSB), hypertransport (HT) interconnection, industry standard architecture (ISA) bus, infinite bandwidth interconnection, low pin count (LPC) bus, memory bus, micro channel architecture (MCA) bus, peripheral component interconnection (PCI) bus, PCI-Express (PCI-X) bus, serial advanced technology attachment (SATA) bus, video electronics standard association local (VLB) bus or other suitable bus or two or more of these combinations.In suitable cases, bus 540 can comprise one or more buses.Although the present application embodiment describes and shows specific bus, the application considers any suitable bus or interconnection.

[0256] Illustratively, the electronic device 500 may be a mobile phone, a tablet computer, a laptop computer, a PDA, an in-vehicle electronic device, an ultra-mobile personal computer (UMPC), a netbook, or a personal digital assistant (PDA).

[0257] The electronic device can execute the password verification method in the embodiment of the present application, thereby realizing the combination Figures 2 to 4 Described password verification method and device.

[0258] In addition, in conjunction with the password verification method in the above embodiments, the present application embodiment may provide a computer-readable storage medium for implementation. The computer-readable storage medium stores computer program instructions; when the computer program instructions are executed by a processor, any one of the password verification methods in the above embodiments is implemented.

[0259] In combination with the password verification method in the above embodiments, the present application embodiment can provide a computer program product for implementation. When the instructions in the computer program product are executed by a processor of an electronic device, any one of the password verification methods in the above embodiments is implemented.

[0260] It should be understood that the present application is not limited to the specific configurations and processes described above and illustrated in the figures. For the sake of brevity, a detailed description of known methods is omitted here. In the above embodiments, several specific steps are described and illustrated as examples. However, the method process of the present application is not limited to the specific steps described and illustrated. Those skilled in the art can make various changes, modifications, and additions, or change the order of the steps after understanding the spirit of the present application.

[0261] The functional blocks shown in the above-described block diagram can be implemented as hardware, software, firmware or a combination thereof. When implemented in hardware, they can be, for example, electronic circuits, application specific integrated circuits (ASICs), appropriate firmware, plug-ins, function cards, etc. When implemented in software, the elements of the present application are programs or code segments that are used to perform the required tasks. The program or code segment can be stored in a machine-readable medium, or transmitted on a transmission medium or a communication link by a data signal carried in a carrier wave. "Machine-readable medium" can include any medium that can store or transmit information. Examples of machine-readable media include electronic circuits, semiconductor memory devices, ROMs, flash memories, erasable ROMs (EROMs), floppy disks, CD-ROMs, optical disks, hard disks, optical fiber media, radio frequency (RF) links, etc. The code segment can be downloaded via a computer network such as the Internet, an intranet, etc.

[0262] It should also be noted that the exemplary embodiments mentioned in this application describe some methods or systems based on a series of steps or devices. However, this application is not limited to the order of the above steps. In other words, the steps can be performed in the order mentioned in the embodiments, or in a different order, or several steps can be performed simultaneously.

[0263] Aspects of the present application have been described above with reference to the flowcharts and / or block diagrams of the methods, devices (systems) and computer program products according to the embodiments of the present application. It should be understood that each box in the flowchart and / or block diagram and the combination of each box in the flowchart and / or block diagram can be implemented by computer program instructions. These computer program instructions can be provided to the processor of a general-purpose computer, a special-purpose computer or other programmable data processing device to produce a machine so that these instructions executed via the processor of the computer or other programmable data processing device enable the implementation of the function / action specified in one or more boxes of the flowchart and / or block diagram. This processor can be, but is not limited to, a general-purpose processor, a special-purpose processor, a special application processor or a field programmable logic circuit. It is also understood that each box in the block diagram and / or the flowchart and the combination of the boxes in the block diagram and / or the flowchart can also be implemented by the dedicated hardware that performs the specified function or action, or can be implemented by the combination of dedicated hardware and computer instructions.

[0264] The above description is only a specific embodiment of the present application. Those skilled in the art will clearly understand that for the convenience and brevity of description, the specific working processes of the systems, modules and units described above can refer to the corresponding processes in the aforementioned method embodiments, and will not be repeated here. It should be understood that the scope of protection of the present application is not limited thereto. Any person skilled in the art can easily think of various equivalent modifications or replacements within the technical scope disclosed in the present application, and these modifications or replacements should be included in the scope of protection of the present application.

Claims

1. A password verification method, characterized in that: Applied to a wearable smart device, the method includes: In response to a triggering operation for password verification, displaying a password input interface, the password input interface including a virtual keyboard, the virtual keyboard including a plurality of text characters and their one-to-one corresponding numeric characters, the correspondence between the text characters and the numeric characters being generated based on system time, a target user identifier, and a random number, the target user identifier being a user identifier bound to the wearable smart device, the plurality of text characters having different pronunciations; In response to a user's voice input of selecting a plurality of target characters from the plurality of text characters, determining voice information input by the user; Performing voice recognition on the voice information to determine a text-based character password; Based on the correspondence between the text characters and the numeric characters, converting the text character password into a numeric character password; Sending the numerical character password to a password verification system so that the password verification system verifies the numerical character password; After responding to the triggering operation of password verification and before displaying the password input interface, the method further includes: Acquire a text character set, a plurality of numeric characters, the system time, the target user identifier, and the random number, wherein the text character set includes a plurality of the text characters; Encrypting the plurality of numerical characters based on the system time, the target user identifier, and the random number to obtain a plurality of first encrypted information; Acquire, from the text character set, the plurality of text characters having different pronunciations that respectively correspond to the plurality of first encrypted information; The plurality of numeric characters are mapped to the plurality of text characters to obtain a correspondence between the plurality of numeric characters and the plurality of text characters.

2. The method according to claim 1, characterized in that After obtaining the correspondence between the plurality of numeric characters and the plurality of text characters, the method further includes: The virtual keyboard is determined based on a correspondence between the plurality of numeric characters and the plurality of text characters.

3. The method according to claim 2, characterized in that The encrypting of the plurality of numeric characters based on the system time, the target user identifier, and the random number to obtain a plurality of first encrypted information includes: Generate a target key based on the system time, the target user identifier and the random number through a hash algorithm; Based on the Advanced Encryption Standard algorithm, the target key is used to encrypt the multiple numeric characters to obtain the multiple first encrypted information.

4. The method according to claim 3, characterized in that The converting the text-type character password into a numeric character password based on the correspondence between the text-type character and the numeric character includes: Based on the correspondence between the text characters and the first encryption information, the text character password is converted into an encryption information sequence, where the encryption information sequence includes the plurality of first encryption information; Based on the Advanced Encryption Standard algorithm, the encrypted information sequence is decrypted to obtain the numerical character password.

5. The method according to any one of claims 1 to 4, characterized in that The sending of the numerical character password to the password verification system includes: Encrypting the numerical character password to obtain second encrypted information; The second encrypted information is sent to the password verification system.

6. The method according to any one of claims 1 to 4, characterized in that The step of determining the voice information input by the user in response to the user's voice input of selecting a plurality of target characters from the plurality of text characters comprises: authenticating the user and obtaining a verification result; If the verification result is that the verification is passed, receiving a voice input of the user selecting a plurality of target characters from the plurality of text characters; In response to the voice input, voice information of the user input is determined.

7. The method according to claim 1, characterized in that The performing voice recognition on the voice information to determine the text-based character password includes: Inputting the speech information into a speech recognition model; The voice information is subjected to voice recognition by the voice recognition model to determine the text-based character password.

8. The method according to claim 7, characterized in that The speech information is a time domain signal, and the step of inputting the speech information into a speech recognition model includes: Converting the speech information from the time domain signal to a frequency domain signal through fast Fourier transform; extracting spectral features from the frequency domain signal; The spectral features are input into the speech recognition model.

9. The method according to claim 8, characterized in that The speech recognition model includes a convolutional layer, an attention layer, a pooling layer, and a fully connected layer; performing speech recognition on the speech information by the speech recognition model to determine the text-based character password includes: Performing a convolution operation on the spectral features through the convolution layer to obtain a first feature map; Downsampling the first feature map through the pooling layer to obtain a second feature map; Determining weights of features in the second feature map by the attention layer; Mapping the features in the second feature map to a plurality of text characters and probabilities corresponding to the plurality of text characters based on weights of the features in the second feature map through an activation function in the fully connected layer; The text-type character password is determined based on the plurality of text-type characters and the probabilities corresponding to the plurality of text-type characters.

10. The method according to any one of claims 7 to 9, characterized in that: Before inputting the speech information into the speech recognition model, the method further includes: Acquire multiple training samples, each of the training samples includes a first voice information sample and a corresponding first character label; Inputting the first voice information sample into an initial voice recognition model to perform voice recognition on the first voice information sample through the initial voice recognition model to obtain a first predicted character; Determining a loss function value based on the similarity between the first predicted character and the first character label; When the loss function value does not meet the preset training stop condition, the first model parameter of the initial speech recognition model is adjusted based on the back propagation algorithm, and the process of inputting the first speech information sample into the initial speech recognition model is returned to execute, so as to perform speech recognition on the first speech information sample through the initial speech recognition model to obtain the first predicted character, until the loss function value meets the preset training stop condition, and the trained speech recognition model is obtained.

11. The method according to claim 10, characterized in that After obtaining the trained speech recognition model, the method further includes: Acquire multiple test samples, each of the test samples including a second voice information sample and its corresponding second character label; Inputting the second voice information sample into the voice recognition model to perform voice recognition on the second voice information sample through the voice recognition model to obtain a second predicted character; determining a character error rate based on similarities between a plurality of second predicted characters and their corresponding first character labels; When the character error rate is greater than a preset threshold, the second model parameter of the speech recognition model is adjusted, and the step of inputting the second speech information sample into the speech recognition model is returned to perform speech recognition on the second speech information sample through the speech recognition model to obtain a second predicted character until the character error rate is less than or equal to the preset threshold.

12. A password verification device, characterized in that: Applied to a wearable smart device, the device comprises: a display module, configured to display a password input interface in response to a triggering operation for password verification, the password input interface including a virtual keyboard, the virtual keyboard including a plurality of text characters and corresponding numeric characters, the correspondence between the text characters and the numeric characters being generated based on system time, a target user identifier, and a random number, the target user identifier being a user identifier bound to the wearable smart device, the plurality of text characters having different pronunciations; a first determining module, configured to determine the voice information input by the user in response to a voice input of the user selecting a plurality of target characters from the plurality of text characters; A second determining module is used to perform voice recognition on the voice information to determine the text-based character password; A conversion module, configured to convert the text-type character password into a numeric character password based on a correspondence between the text-type character and the numeric character; A sending module, configured to send the numerical character password to a password verification system, so that the password verification system verifies the numerical character password; A first acquisition module is configured to acquire a text character set including a plurality of text characters, a plurality of numeric characters, the system time, the target user identifier, and the random number after responding to a triggering operation for password verification and before displaying a password input interface; an encryption module, configured to encrypt the plurality of numerical characters based on the system time, the target user identifier, and the random number to obtain a plurality of first encrypted information; A second acquisition module is configured to acquire, from the text character set, the plurality of text characters having different pronunciations and corresponding to the plurality of first encrypted information; The mapping module is used to map the multiple numeric characters to the multiple text characters to obtain a correspondence between the multiple numeric characters and the multiple text characters.

13. An electronic device, characterized in that: The electronic device includes: a processor and a memory storing computer program instructions; When the processor executes the computer program instructions, the password verification method according to any one of claims 1 to 11 is implemented.

14. A computer-readable storage medium, characterized in that The computer-readable storage medium stores computer program instructions, which, when executed by a processor, implement the password verification method according to any one of claims 1 to 11.

15. A computer program product, characterized in that When the instructions in the computer program product are executed by a processor of an electronic device, the electronic device executes the password verification method according to any one of claims 1 to 11.

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