Method, device and electronic equipment for improving user login authentication fault tolerance

Abstract

Embodiments of the present disclosure provide a method, device and electronic equipment for improving user login authentication fault tolerance. The method comprises: obtaining user input features according to operations in a user login process; comparing the user input features with pre-stored user input features, wherein the user input features include authentication information characters and input time lengths between adjacent characters; obtaining errors of each group of input time lengths between adjacent characters in the user input features and corresponding input time lengths between adjacent characters in the pre-stored user input features respectively, and performing weighted summation on the obtained errors as a weighted error; and determining whether it is a user login according to a comparison result of the authentication information characters and the weighted error. In this way, user login authentication fault tolerance can be improved while preventing non-user login.

Description

Technical Field

[0001] This disclosure relates to the Internet field, and more specifically, embodiments of this disclosure relate to a method, apparatus, and electronic device for improving the fault tolerance of user login authentication. Background Technology

[0002] Typically, user authentication information consists of multiple characters. Users need to enter these characters sequentially to complete the authentication process. To prevent others from obtaining user authentication information and impersonating users to log in, patterns can be summarized based on the input time between adjacent characters during the user's input process. These patterns can then be used to determine whether the user is logging in.

[0003] In reality, due to the randomness of human beings, users often have significant fluctuations in their input. This leads to either overly strict verification when judging based on user input patterns, making it difficult even for the user to successfully input, or overly lenient verification, making it easy for non-users to pass the verification. Summary of the Invention

[0004] This disclosure provides a method, apparatus, and electronic device for improving the fault tolerance of user login authentication, thereby improving fault tolerance for user login authentication while identifying non-user logins.

[0005] According to a first aspect of this disclosure, a method for improving the fault tolerance of user login authentication is provided. The method includes:

[0006] Based on the user's actions during the login process, obtain user input characteristics;

[0007] The user input features are compared with the pre-stored user input features, which include authentication information characters and the input duration between adjacent characters.

[0008] The error is obtained by comparing the input duration between each group of adjacent characters in the user input features with the corresponding input duration between adjacent characters in the pre-stored user input features, and the resulting errors are weighted and summed to obtain the weighted error.

[0009] Determine whether a user has logged in based on the character comparison results of the authentication information and the weighted error.

[0010] Among the possible implementations of the first aspect, determining whether a user has logged in based on the character comparison results of the authentication information and the weighted error includes:

[0011] If the authentication information contains incorrect characters or the weighted error exceeds a preset value, it will be determined that the user is not logged in.

[0012] If the authentication information is correct and the weighted error is less than or equal to the preset value, then the user is considered logged in.

[0013] In some possible implementations of the first aspect, the weighted summation includes:

[0014] The errors are assigned weight values ​​based on their magnitude, and then the weight values ​​are summed with the error values.

[0015] In some possible implementations of the first aspect, the weight value marking rules include: taking the first few digits in descending error order or descending and ascending error order respectively, marking the smaller error with a weight value, and marking the remaining errors with a larger error with a weight value.

[0016] Among the possible implementations of the first aspect, the error calculation methods include:

[0017] Based on the input duration between adjacent characters obtained multiple times, a threshold is set for the input duration between each group of adjacent characters in the pre-stored user input features. If the input duration between adjacent characters in the user input features is within the threshold range, the corresponding error is 0. If the input duration between adjacent characters in the user input features exceeds the threshold range, the difference between the input duration between adjacent characters in the user input features and the threshold with the smallest difference is taken as the corresponding error.

[0018] In some possible implementations of the first aspect, the weighted summation includes:

[0019] Based on the input duration between adjacent characters obtained multiple times, a threshold is set for the input duration between adjacent characters in each group of pre-stored user input features. The corresponding error is labeled with a weight value according to the size of the threshold range of each group. Then, the weight value and the error value are weighted and summed.

[0020] Some possible implementations of the first aspect also include updating pre-stored user input features, including:

[0021] When it is determined that a user has logged in, the current user input features are combined with the original pre-stored user input features to update the pre-stored user input features.

[0022] Among some possible implementations of the first aspect, user reset is also included, which includes clearing the pre-stored user input features and re-obtaining the pre-stored user input features based on the user input features.

[0023] According to a second aspect of this disclosure, an apparatus for improving the fault tolerance of user login authentication is provided. The apparatus includes: an acquisition unit, configured to acquire user input features based on operations performed during the user login process;

[0024] The comparison unit is used to compare the user input features with the pre-stored user input features, which include authentication information characters and the input duration between adjacent characters.

[0025] The calculation unit is used to obtain the error between the input duration of each group of adjacent characters in the user input features and the corresponding input duration between adjacent characters in the pre-stored user input features, and to perform a weighted summation of the obtained errors as the weighted error;

[0026] The judgment unit is used to determine whether a user has logged in based on the character comparison results of the authentication information and the weighted error.

[0027] According to a third aspect of this disclosure, an electronic device is provided. The electronic device includes: at least one processor; and a memory communicatively connected to said at least one processor; the memory stores instructions executable by said at least one processor, said instructions being executed by said at least one processor to enable said at least one processor to perform the method for improving user login authentication fault tolerance as described in the first aspect of this disclosure.

[0028] In this disclosure, the error is weighted, and whether it is a user login is determined based on the authentication information characters and the weighted error. The weighted error reflects the fluctuation of input time between adjacent characters. Using the weighted error as the judgment standard greatly improves the fault tolerance of user login, and at the same time identifies non-user login.

[0029] It should be understood that the description in the Summary of the Invention is not intended to limit the key or essential features of the embodiments of this disclosure, nor is it intended to restrict the scope of this disclosure. Other features of this disclosure will become readily apparent from the following description. Attached Figure Description

[0030] The above and other features, advantages, and aspects of the embodiments of this disclosure will become more apparent from the accompanying drawings and the following detailed description. The drawings are provided for a better understanding of the invention and are not intended to limit the scope of this disclosure. In the drawings, the same or similar reference numerals denote the same or similar elements, wherein:

[0031] Figure 1 A flowchart of a method for improving the fault tolerance of user login authentication according to an embodiment of the present disclosure is shown;

[0032] Figure 2 A schematic diagram of a user input process according to an embodiment of the present disclosure is shown;

[0033] Figure 3 A logic diagram of a method for further improving the fault tolerance of user login authentication according to an embodiment of the present disclosure is shown;

[0034] Figure 4 A block diagram of an apparatus for improving the fault tolerance of user login authentication according to an embodiment of the present disclosure is shown;

[0035] Figure 5A block diagram of an electronic device for implementing the method for improving the fault tolerance of user login authentication according to embodiments of the present disclosure is shown. Detailed Implementation

[0036] To make the objectives, technical solutions, and advantages of the embodiments of this disclosure clearer, the technical solutions of the embodiments of this disclosure will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of this disclosure, and not all embodiments. Based on the embodiments of this disclosure, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of this disclosure.

[0037] In this disclosure, since there are certain fluctuations in the characters entered by the user for authentication information, the error is weighted to make an intuitive calculation of the fluctuations. The error is then combined with the characters entered for authentication information to determine whether the user has logged in. Since human input habits are unique, the fluctuations in the characters entered by non-users are inconsistent with the fluctuations in the characters entered by the user. Therefore, this method can identify non-users, and because the error weighting fully considers the fluctuations in user input, it improves the fault tolerance of user input.

[0038] Figure 1 A flowchart of a method for improving the fault tolerance of user login authentication according to an embodiment of the present disclosure is shown.

[0039] like Figure 1 As shown, embodiments of this disclosure provide a method for improving the fault tolerance of user login authentication, including:

[0040] S101: Obtain user input features based on the user's actions during the login process;

[0041] S102: Compare the user input features with the pre-stored user input features, which include authentication information characters and the input duration between adjacent characters;

[0042] S103: The error is obtained by comparing the input duration between each group of adjacent characters in the user input features with the corresponding input duration between adjacent characters in the pre-stored user input features, and the resulting errors are weighted and summed to obtain the weighted error.

[0043] S104: Determine whether the user has logged in based on the character comparison results of the authentication information and the weighted error.

[0044] Obviously, the pre-stored user input features also include authentication information characters and the input duration between adjacent characters. The user input features are compared with the pre-stored user input features, that is, the input duration between the two sets of authentication information characters and the two sets of adjacent characters are compared respectively.

[0045] The authentication information characters are usually passwords. Since the weighted error reflects the fluctuation of user input habits, it is understandable that the longer the authentication information characters, the better the exclusivity and security of the method for user login authentication, but the lower the fault tolerance.

[0046] Figure 2 A schematic diagram of a user input process according to an embodiment of the present disclosure is shown.

[0047] like Figure 2 As shown, taking a user logging in with the password hide35 as an example, starting from time t0 when the login window is displayed, the user enters each character of the password sequentially from time t1 to time t6, and then clicks the login button at time t7. In addition to recording the password entered by the user, the login system also records eight times from t0 to t7. The login system obtains seven time intervals from Δt0 to Δt6, and the input time between adjacent characters is these seven time intervals.

[0048] According to embodiments of this disclosure, user input patterns are obtained based on the input duration between adjacent characters. These user input patterns are represented by pre-stored user input features. The error is then obtained by comparing each obtained user input feature with the pre-stored user input features. The error directly reflects the difference between a user's input and the user input pattern. It can be understood that the magnitude of the error value can be used to determine if a user is not logged in. By weighting the error, excessive error values ​​due to user habits can be avoided, thereby improving the fault tolerance of user login.

[0049] Figure 3 A logic diagram of a method 200 for further improving the fault tolerance of user login authentication according to an embodiment of the present disclosure is shown.

[0050] like Figure 3 As shown, in some embodiments, determining whether a user has logged in based on the character comparison results of the authentication information and the weighted error includes:

[0051] If the authentication information contains incorrect characters or the weighted error exceeds a preset value, it will be determined that the user is not logged in.

[0052] If the authentication information is correct and the weighted error is less than or equal to the preset value, then the user is considered logged in.

[0053] It is understandable that a user can only be considered logged in if they enter the authentication information characters correctly and the input process follows the user's input pattern. Therefore, a user can only be considered logged in if both the authentication information characters and the weighted error meet the requirements.

[0054] The preset value can be a fixed value defined by the user. For example, if the preset value is set to 5 seconds, then if the calculated weighted error exceeds 5 seconds, it is judged as a non-user login. The preset value can also be adjusted by setting an algorithm. For example, if the preset value is set to 5% of the total input time, then the preset value will fluctuate and be adjusted according to the fluctuation of the user's input habits.

[0055] According to the embodiments of this disclosure, setting a preset value to judge the weighted error can control the size of the preset value to further control the fault tolerance. It can be understood that the higher the preset value, the higher the fault tolerance, and the lower the preset value, the lower the fault tolerance.

[0056] In some embodiments, the weighted summation includes:

[0057] The errors are assigned weight values ​​based on their magnitude, and then the weight values ​​are summed with the error values.

[0058] For example, the pre-stored user input features are:

[0059] ΔT=[Δt0,Δt1,Δt2,...,Δt6];

[0060] And in one instance, the user's input was:

[0061] Δt'=[Δt'0,Δt'1,Δt' 2, ...,Δt'6];

[0062] The difference between the two is:

[0063] D=[dt'0,dt'1,dt'2,...,dt'6];

[0064] Where dt' i =|Δt i -Δt' i |,i=[0,1,..,6].

[0065] Based on the above definition, for dt' i We perform weighting to obtain the weight values ​​W = [w0, w1, w2, ..., w6].

[0066] Then, based on each group's dt' i With W i The sum of the products yields the weighted error. It is understandable that the weight values ​​should be marked according to the importance of each group of errors in reflecting the user input pattern. Errors with a high correlation to the user input pattern should be marked with a larger weight, and vice versa.

[0067] In some embodiments, the weight value marking rule includes: taking the first few digits in descending error order or descending and ascending error order respectively, marking the smaller error value as the weight value, and marking the remaining errors as the larger error value.

[0068] Following the example above, the first one is taken according to the ascending or descending order of the error. D' = [dt'0, dt'1, d't2, ..., dt'6] = [0.05, 0.04, 0.12, 0.5, 0.01, 0.02, 0.05]. The maximum value is taken as 1, that is, the 4th element 0.5, and the minimum value is the 5th element 0.01. The weights for marking the maximum and minimum are 0, and the remaining error is marked as 1. Thus, the weight value W = [1, 1, 1, 0, 0, 1, 1].

[0069] By sorting errors in ascending or descending order, smaller weight values ​​can be assigned to the largest or smallest errors. This helps avoid interference from excessively large or small errors during login authentication, improving the fault tolerance of user login authentication. Since larger errors tend to lead to larger weighted errors, while smaller errors tend to lead to smaller weighted errors, to further improve fault tolerance, only the first few errors in descending order can be assigned smaller weight values.

[0070] It is understandable that, due to fluctuations in user input, the maximum error value may not always be d't4. Therefore, the error weight value corresponding to the input time between each group of adjacent characters will be different for each user input.

[0071] According to embodiments of this disclosure, a smaller weight is assigned to the largest or a subset of the largest and smallest errors to avoid interference from excessively large or small input errors of a few characters during a user's input process, thereby improving the fault tolerance of user login authentication.

[0072] In some embodiments, the error calculation method includes:

[0073] Based on the input duration between adjacent characters obtained multiple times, a threshold is set for the input duration between each group of adjacent characters in the pre-stored user input features. If the input duration between adjacent characters in the user input features is within the threshold range, the corresponding error is 0. If the input duration between adjacent characters in the user input features exceeds the threshold range, the difference between the input duration between adjacent characters in the user input features and the threshold with the smallest difference is taken as the corresponding error.

[0074] To obtain pre-stored user features, during a user's first login authentication, the user is required to input authentication information characters multiple times. The average input duration between each group of adjacent characters is then calculated, and a threshold is applied within a certain range based on the average. Input durations of adjacent characters that differ significantly from the average are discarded. Typically, the user's input of authentication information characters fluctuates greatly in the first few times. After several consecutive inputs, the user's finger technique is trained to a certain extent, and the fluctuations are smaller. Therefore, the user input features obtained in the first few logins can be discarded.

[0075] The threshold can be adjusted based on user input characteristics. Specifically, it involves obtaining the average input duration between adjacent characters from multiple user inputs, discarding discarded values ​​based on a regression curve, and using the largest absolute value of the average fluctuation as the threshold critical point. The greater the fluctuation, the wider the threshold range. It is understood that the method for obtaining the threshold is not unique; replacing the average with the median is also an acceptable way to obtain the threshold.

[0076] The error is calculated based on a threshold. For example, if Δt0 is 0.2-0.4s, and the user inputs Δt'0 for 0.5s, the threshold that is closest to 0.5s is 0.4s, then the error is 0.5-0.4=0.1s. If the user inputs Δt'0 for 0.3s, then the error is 0.

[0077] According to the embodiments of this disclosure, since each user input has a certain range of normal deviation, obtaining the threshold of the input time between each group of adjacent characters can distinguish between normal deviation and error. Calculating the error based on the threshold can greatly reduce the error of each group, further reduce the weighted error, and improve the fault tolerance of user login.

[0078] In some embodiments, the weighted summation includes:

[0079] Based on the input duration between adjacent characters obtained multiple times, a threshold is set for the input duration between adjacent characters in each group of pre-stored user input features. The corresponding error is labeled with a weight value according to the size of the threshold range of each group. Then, the weight value and the error value are weighted and summed.

[0080] Specifically, a smaller weight value can be assigned to the error corresponding to the input duration between adjacent characters with a larger threshold range, and a larger weight value can be assigned to the error corresponding to the input duration between adjacent characters with a smaller threshold range.

[0081] According to the embodiments of this disclosure, there is a certain degree of fluctuation in the user's input process. Generally, the less familiar the user is with a character, the greater the fluctuation in input. Even after multiple training sessions, there may still be a large range of fluctuations in the next input process, and most of the large errors are formed from this. Therefore, assigning a small weight value to the input time between adjacent characters can avoid the large weighted error caused by the user's unfamiliarity with the input time of characters being too long, and further improve the fault tolerance.

[0082] It is understandable that error weighting and threshold weighting can only be chosen as one of the two. The reason is that if both error and threshold are weighted at the same time, the larger error will be marked twice with a smaller weight, resulting in a smaller weighted error value. The smaller error will be magnified too much. Even if non-users log in, the fault tolerance will be greatly improved. Therefore, it is impossible to prevent non-users from passing the authentication, and the security will be greatly reduced.

[0083] In some embodiments, the method further includes updating pre-stored user input features, including:

[0084] When it is determined that a user has logged in, the current user input features are combined with the original pre-stored user input features to update the pre-stored user input features.

[0085] Since users' input habits change over time, such as as their proficiency increases and the time spent inputting adjacent characters decreases, the pre-stored user input features are updated in conjunction with the original pre-stored user input features to make them conform to the user's current input habits.

[0086] In some embodiments, the method further includes user reset, which includes clearing the pre-stored user input features and re-obtaining the pre-stored user input features based on the user input features.

[0087] When user habits change, such as when a user changes to a new device or changes their password, it is necessary to re-enter the pre-stored user input features and then re-execute steps S101-S104 based on the new pre-stored user input features in subsequent user input processes.

[0088] It should be noted that, for the sake of simplicity, the foregoing method embodiments are all described as a series of actions. However, those skilled in the art should understand that this disclosure is not limited to the described order of actions, because according to this disclosure, some steps can be performed in other orders or simultaneously. Furthermore, those skilled in the art should also understand that the embodiments described in the specification are all optional embodiments, and the actions and modules involved are not necessarily essential to this disclosure.

[0089] The above is an introduction to the method embodiments. The following describes the solution described in this disclosure further through device embodiments.

[0090] Figure 4 A block diagram of an apparatus 300 for improving the fault tolerance of user login authentication according to an embodiment of the present disclosure is shown. Apparatus 300 includes:

[0091] The acquisition unit 310 is used to acquire user input features based on the user's actions during the login process;

[0092] The comparison unit 320 is used to compare the user input features with the pre-stored user input features, which include authentication information characters and the input duration between adjacent characters;

[0093] The calculation unit 330 is used to obtain the error between the input duration between each group of adjacent characters in the user input features and the corresponding input duration between adjacent characters in the pre-stored user input features, and to perform a weighted summation of the obtained errors as a weighted error.

[0094] The judgment unit 340 is used to determine whether a user has logged in based on the character comparison result of the authentication information and the weighted error.

[0095] Those skilled in the art will understand that, for the sake of convenience and brevity, the specific working process of the described module can be referred to the corresponding process in the foregoing method embodiments, and will not be repeated here.

[0096] The acquisition, storage, and application of user personal information involved in the technical solution disclosed herein comply with the provisions of relevant laws and regulations and do not violate public order and good morals.

[0097] According to embodiments of this disclosure, this disclosure also provides an electronic device comprising: at least one processor; and a memory communicatively connected to the at least one processor; the memory storing instructions executable by the at least one processor, the instructions being executed by the at least one processor to enable the at least one processor to perform the method for improving user login authentication fault tolerance as described in the first aspect of this disclosure.

[0098] Figure 5A schematic block diagram of an electronic device 400 that can be used to implement embodiments of the present disclosure is shown. The electronic device is intended to represent various forms of digital computers, such as laptop computers, desktop computers, workstations, personal digital assistants, servers, blade servers, mainframe computers, and other suitable computers. The electronic device may also represent various forms of mobile devices, such as personal digital processors, cellular phones, smartphones, wearable devices, and other similar computing devices. The components shown herein, their connections and relationships, and their functions are merely illustrative and are not intended to limit the implementation of the present disclosure described and / or claimed herein.

[0099] Electronic device 400 includes a computing unit 401, which can perform various appropriate actions and processes based on a computer program stored in read-only memory (ROM) 402 or a computer program loaded from storage unit 408 into random access memory (RAM) 403. The RAM 403 may also store various programs and data required for the operation of device 400. The computing unit 401, ROM 402, and RAM 403 are interconnected via bus 404. An input / output (I / O) interface 405 is also connected to bus 404.

[0100] Multiple components in electronic device 400 are connected to I / O interface 405, including: input unit 406, such as keyboard, mouse, etc.; output unit 407, such as various types of displays, speakers, etc.; storage unit 408, such as disk, optical disk, etc.; and communication unit 409, such as network card, modem, wireless transceiver, etc. Communication unit 409 allows device 400 to exchange information / data with other devices through computer networks such as the Internet and / or various telecommunications networks.

[0101] The computing unit 401 can be a variety of general-purpose and / or special-purpose processing components with processing and computing capabilities. Some examples of the computing unit 401 include, but are not limited to, a central processing unit (CPU), a graphics processing unit (GPU), various special-purpose artificial intelligence (AI) computing chips, various computing units running machine learning model algorithms, a digital signal processor (DSP), and any suitable processor, controller, microcontroller, etc. The computing unit 401 performs the various methods and processes described above, such as method 100. For example, in some embodiments, method 100 may be implemented as a computer software program tangibly contained in a machine-readable medium, such as storage unit 408. In some embodiments, part or all of the computer program may be loaded and / or installed on device 400 via ROM 402 and / or communication unit 409. When the computer program is loaded into RAM 403 and executed by the computing unit 401, one or more steps of method 100 described above may be performed. Alternatively, in other embodiments, the computing unit 401 may be configured to perform method 100 by any other suitable means (e.g., by means of firmware).

[0102] Various embodiments of the systems and techniques described above herein can be implemented in digital electronic circuit systems, integrated circuit systems, field-programmable gate arrays (FPGAs), application-specific integrated circuits (ASICs), application-specific standard products (ASSPs), systems-on-a-chip (SoCs), payload-programmable logic devices (CPLDs), computer hardware, firmware, software, and / or combinations thereof. These various embodiments may include implementations in one or more computer programs that can be executed and / or interpreted on a programmable system including at least one programmable processor, which may be a dedicated or general-purpose programmable processor, capable of receiving data and instructions from a storage system, at least one input device, and at least one output device, and transmitting data and instructions to the storage system, the at least one input device, and the at least one output device.

[0103] The program code used to implement the methods of this disclosure may be written in any combination of one or more programming languages. This program code may be provided to a processor or controller of a general-purpose computer, special-purpose computer, or other programmable data processing apparatus, such that when executed by the processor or controller, the program code causes the functions / operations specified in the flowcharts and / or block diagrams to be implemented. The program code may be executed entirely on a machine, partially on a machine, as a standalone software package partially on a machine and partially on a remote machine, or entirely on a remote machine or server.

[0104] To provide interaction with a user, the systems and techniques described herein can be implemented on a computer having: a display device for displaying information to the user (e.g., a CRT (cathode ray tube) or LCD (liquid crystal display) monitor); and a keyboard and pointing device (e.g., a mouse or trackball) through which the user provides input to the computer. Other types of devices can also be used to provide interaction with the user; for example, feedback provided to the user can be any form of sensory feedback (e.g., visual feedback, auditory feedback, or tactile feedback); and input from the user can be received in any form (including sound input, voice input, or tactile input).

[0105] The systems and technologies described herein can be implemented in computing systems that include backend components (e.g., as a data server), or computing systems that include middleware components (e.g., an application server), or computing systems that include frontend components (e.g., a user computer with a graphical user interface or web browser through which a user can interact with embodiments of the systems and technologies described herein), or any combination of such backend, middleware, or frontend components. The components of the system can be interconnected via digital data communication of any form or medium (e.g., a communication network). Examples of communication networks include local area networks (LANs), wide area networks (WANs), and the Internet.

[0106] Computer systems can include clients and servers. Clients and servers are generally located far apart and typically interact via communication networks. Client-server relationships are created by computer programs running on the respective computers and having a client-server relationship with each other. Servers can be cloud servers, servers in distributed systems, or servers incorporating blockchain technology.

[0107] It should be understood that the various forms of processes shown above can be used to rearrange, add, or delete steps. For example, the steps described in this disclosure can be executed in parallel, sequentially, or in different orders, as long as the desired result of the technical solution disclosed in this disclosure can be achieved, and this is not limited herein.

[0108] The specific embodiments described above do not constitute a limitation on the scope of protection of this disclosure. Those skilled in the art should understand that various modifications, combinations, sub-combinations, and substitutions can be made according to design requirements and other factors. Any modifications, equivalent substitutions, and improvements made within the spirit and principles of this disclosure should be included within the scope of protection of this disclosure.

Claims

1. A method for improving the fault tolerance of user login authentication, characterized in that, include: Based on the user's actions during the login process, obtain user input characteristics; The user input features are compared with the pre-stored user input features, which include authentication information characters and the input duration between adjacent characters. The error is obtained by comparing the input duration between each group of adjacent characters in the user input features with the corresponding input duration between adjacent characters in the pre-stored user input features, and the resulting errors are weighted and summed to obtain the weighted error. Determine whether the user has logged in based on the character comparison results of the authentication information and the weighted error. Error calculation methods include: Based on the input duration between adjacent characters obtained multiple times, a threshold is set for the input duration between each group of adjacent characters in the pre-stored user input features. If the input duration between adjacent characters in the user input features is within the threshold range, the corresponding error is 0. If the input duration between adjacent characters in the user input features exceeds the threshold range, the difference between the input duration between adjacent characters in the user input features and the threshold with the smallest difference is taken as the corresponding error. The weighted summation includes: The error label weights are assigned based on the size of each threshold range. Specifically, the error label corresponding to the input duration between adjacent characters with a larger threshold range has a smaller weight, and the error label corresponding to the input duration between adjacent characters with a smaller threshold range has a larger weight. Then, the weights and error values ​​are summed in a weighted manner.

2. The method for improving the fault tolerance of user login authentication according to claim 1, characterized in that, Determining whether a user is logged in based on the character comparison results of the authentication information and the weighted error includes: If the authentication information contains incorrect characters or the weighted error exceeds a preset value, it will be determined that the user is not logged in. If the authentication information is correct and the weighted error is less than or equal to the preset value, then the user is considered logged in.

3. The method for improving the fault tolerance of user login authentication according to claim 1, characterized in that, It also includes updating pre-stored user input features, including: When it is determined that a user has logged in, the current user input features are combined with the original pre-stored user input features to update the pre-stored user input features.

4. The method for improving the fault tolerance of user login authentication according to claim 1, characterized in that, It also includes user reset, which includes clearing the pre-stored user input features and re-obtaining the pre-stored user input features based on the user input features.

5. A device for improving the fault tolerance of user login authentication, characterized in that, include: The acquisition unit is used to acquire user input features based on the user's actions during the login process; The comparison unit is used to compare the user input features with the pre-stored user input features, which include authentication information characters and the input duration between adjacent characters. The calculation unit is used to obtain the error between the input duration of each group of adjacent characters in the user input features and the corresponding input duration between adjacent characters in the pre-stored user input features, and to perform a weighted summation of the obtained errors as the weighted error; The judgment unit is used to determine whether a user has logged in based on the character comparison result of the authentication information and the weighted error. Error calculation methods include: Based on the input duration between adjacent characters obtained multiple times, a threshold is set for the input duration between each group of adjacent characters in the pre-stored user input features. If the input duration between adjacent characters in the user input features is within the threshold range, the corresponding error is 0. If the input duration between adjacent characters in the user input features exceeds the threshold range, the difference between the input duration between adjacent characters in the user input features and the threshold with the smallest difference is taken as the corresponding error. The weighted summation includes: The error label weights are assigned based on the size of each threshold range. Specifically, the error label corresponding to the input duration between adjacent characters with a larger threshold range has a smaller weight, and the error label corresponding to the input duration between adjacent characters with a smaller threshold range has a larger weight. Then, the weights and error values ​​are summed in a weighted manner.

6. An electronic device, characterized in that, include: At least one processor; The at least one processor is also connected in communication with a memory; characterized in that the memory stores instructions executable by the at least one processor to enable the at least one processor to perform the method of any one of claims 1-4.

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