CN113536272A

CN113536272A - User identity authentication method and device based on user muscle memory

Info

Publication number: CN113536272A
Application number: CN202110892792.8A
Authority: CN
Inventors: 王燕来
Original assignee: Shumao Technology Beijing Co ltd
Current assignee: Shumao Technology Beijing Co ltd
Priority date: 2021-08-04
Filing date: 2021-08-04
Publication date: 2021-10-22

Abstract

The invention discloses a user identity authentication method and a device based on muscle memory of a user, wherein the method comprises the following steps: acquiring a first character string formed by a user through knocking a keyboard within a first preset time period; analyzing characters in the first character string from multiple dimensions to obtain first muscle habits corresponding to the multiple dimensions, and determining multiple verification conditions; in the user identity authentication process, acquiring a second character string formed by a user through knocking a keyboard within a second preset time period; analyzing characters in the second character string from multiple dimensions to obtain second muscle habits corresponding to the multiple dimensions; judging whether the second muscle habits corresponding to the multiple dimensions meet at least two verification conditions; and if so, judging that the user passes the authentication. According to the scheme, the muscle habits corresponding to multiple dimensions of the user in the keyboard knocking process are compared with the verification conditions determined in advance based on the muscle habits of the user, and the user identity verification is conveniently realized.

Description

User identity authentication method and device based on user muscle memory

Technical Field

The invention relates to the technical field of information, in particular to a user identity authentication method and device based on muscle memory of a user.

Background

The existing internet products all face the increasingly high requirements for privacy data confidentiality of users, and most of internet products generally adopt a verification mode in the password verification link of the products: the password obtained by splicing and combining more than 3 types of character strings such as upper and lower case letters, numbers, special symbols and the like is verified. In practice, however, various errors often occur when the complicated password is memorized manually, and sensitive data such as the password of the user can be forgotten due to time circulation or various kinds of used internet products and the like. For a user with multiple wrong password inputs, the internet platform usually forces the user to make password complaints and recovery, at this time, the user needs to verify through personal information such as a mobile phone number, an identification number, a bank card number and the like, and once the password is reset successfully, the user may forget again and go back and forth.

The existing password setting and password retrieving mode brings difficulty to a user to memorize and reset the password, and in the password retrieving process, the personal information of the user has the risk of being maliciously acquired and utilized by a hacker in a remote control mode, but the hacker cannot be effectively prevented from acquiring the personal information of the user in the prior art. How to balance the relationship between the difficulty of password recovery and the security of password recovery to quickly and efficiently protect the personal information and user stickiness of the user becomes a problem that various internet companies need to solve.

Disclosure of Invention

In view of the above, the present invention has been made to provide a user authentication method and apparatus based on user muscle memory that overcomes or at least partially solves the above-mentioned problems.

According to an aspect of the present invention, there is provided a user authentication method based on muscle memory of a user, the method comprising:

acquiring a first character string formed by a user through knocking a keyboard in a keyboard designated area within a first preset time period;

analyzing characters in the first character string from multiple dimensions to obtain first muscle habits corresponding to the multiple dimensions in the keyboard knocking process, and determining multiple verification conditions according to the first muscle habits corresponding to the multiple dimensions;

in the user identity authentication process, acquiring a second character string formed by a user in a designated area of a keyboard in a second preset time period through knocking the keyboard;

analyzing characters in the second character string from multiple dimensions to obtain second muscle habits corresponding to the multiple dimensions in the keyboard knocking process;

judging whether second muscle habits corresponding to the multiple dimensions meet at least two verification conditions in the multiple verification conditions;

and if so, judging that the user passes the authentication.

Further, the plurality of dimensions includes: the character number proportion dimension, the overall character tapping sequence dimension and the inter-character tapping sequence dimension.

Further, analyzing the characters in the first character string from multiple dimensions, and obtaining a first muscle habit corresponding to the multiple dimensions in the process of keyboard tapping further comprises:

searching the same character in the first character string, counting the number of the same character, and calculating the ratio of the number of the same character in the total number of the first character string;

sorting the characters according to the sequence of the ratio from high to low, selecting N characters with the ratio arranged at the front, and obtaining a first muscle habit corresponding to the ratio dimension of the number of the characters in the process of knocking the keyboard; wherein N is a positive integer.

aiming at each character in N characters which are arranged at the front in proportion, calculating the average value of the serial numbers of the knocking sequences according to the serial numbers of the knocking sequences of the characters in the first character string to obtain the average value of the whole knocking sequences corresponding to the characters;

sequencing the N characters according to the sequence of the average value of the overall knocking sequence from low to high, selecting M characters arranged at the front, and obtaining a first muscle habit corresponding to the dimension of the overall knocking sequence of the characters in the keyboard knocking process; wherein M is a positive integer, and M is less than or equal to N.

combining every two of the N characters with the higher occupation arrangement to generate a plurality of first character pairs; each first character pair comprises two characters;

aiming at each first character pair, setting the sequence of knocking two characters according to the integral average value of the knocking sequence corresponding to each character in the two characters of the first character pair to obtain a second character pair corresponding to the first character pair;

and selecting a preset number of second character pairs from the second character pairs corresponding to the first character pairs as a first muscle habit corresponding to the stroke sequence dimension among the characters in the process of knocking the keyboard.

According to another aspect of the present invention, there is provided a user authentication apparatus based on muscle memory of a user, the apparatus including:

the first acquisition module is suitable for acquiring a first character string formed by a user in a keyboard designated area in a first preset time period through knocking a keyboard;

the first analysis module is suitable for analyzing the characters in the first character string from multiple dimensions to obtain first muscle habits corresponding to the multiple dimensions in the keyboard knocking process, and determining multiple verification conditions according to the first muscle habits corresponding to the multiple dimensions;

the second acquisition module is suitable for acquiring a second character string formed by the user through knocking the keyboard in a designated area of the keyboard within a second preset time period in the user identity authentication process;

the second analysis module is suitable for analyzing the characters in the second character string from multiple dimensions to obtain second muscle habits corresponding to the multiple dimensions in the keyboard knocking process;

the judging module is suitable for judging whether the second muscle habits corresponding to the multiple dimensions meet at least two verification conditions in the multiple verification conditions; and if so, judging that the user passes the authentication.

Further, the first analysis module is further adapted to:

According to yet another aspect of the present invention, there is provided a computing device comprising: the processor, the memory and the communication interface complete mutual communication through the communication bus;

the memory is used for storing at least one executable instruction, and the executable instruction causes the processor to execute the operation corresponding to the user identity authentication method based on the muscle memory of the user.

According to still another aspect of the present invention, there is provided a computer storage medium having at least one executable instruction stored therein, the executable instruction causing a processor to perform operations corresponding to the user identity authentication method based on muscle memory of a user as described above.

According to the technical scheme provided by the invention, in the process of identity authentication, a user does not need to input personal information such as an identity card number, a mobile phone number, a bank card number and the like, and does not need to perform face recognition, only the user randomly taps the keyboard in a designated area of the keyboard for a period of time, and the user identity authentication can be conveniently realized by comparing muscle habits corresponding to multiple dimensions of the user in the process of tapping the keyboard with authentication conditions determined in advance based on the muscle habits of the user, so that the personal information of the user is protected, the user can conveniently complete the identity authentication, particularly for old users who are forgetful or are not familiar with operating software application, the convenience of the identity authentication is greatly improved, the speed of finding or resetting the password by the user can be greatly improved, and the user viscosity of an Internet platform is further improved.

The foregoing description is only an overview of the technical solutions of the present invention, and the embodiments of the present invention are described below in order to make the technical means of the present invention more clearly understood and to make the above and other objects, features, and advantages of the present invention more clearly understandable.

Drawings

Various other advantages and benefits will become apparent to those of ordinary skill in the art upon reading the following detailed description of the preferred embodiments. The drawings are only for purposes of illustrating the preferred embodiments and are not to be construed as limiting the invention. Also, like reference numerals are used to refer to like parts throughout the drawings. In the drawings:

FIG. 1a shows a schematic flow diagram of a method of user identity verification based on muscle memory of a user according to an embodiment of the invention;

FIG. 1b shows a schematic diagram of a designated area of a keyboard;

fig. 2 is a block diagram showing a structure of a user authentication apparatus based on muscle memory of a user according to an embodiment of the present invention;

FIG. 3 shows a schematic structural diagram of a computing device according to an embodiment of the invention.

Detailed Description

Exemplary embodiments of the present disclosure will be described in more detail below with reference to the accompanying drawings. While exemplary embodiments of the present disclosure are shown in the drawings, it should be understood that the present disclosure may be embodied in various forms and should not be limited to the embodiments set forth herein. Rather, these embodiments are provided so that this disclosure will be thorough and complete, and will fully convey the scope of the disclosure to those skilled in the art.

Fig. 1a shows a schematic flow chart of a user authentication method based on muscle memory of a user according to an embodiment of the present invention, as shown in fig. 1a, the method comprises the following steps:

step S101, acquiring a first character string formed by a user in a keyboard designated area within a first preset time period through keyboard tapping.

In order to facilitate the identity verification of the user based on the muscle memory of the user, the muscle habits of the arm and the palm of the user need to be recorded first. In this embodiment, the character string obtained in the muscle habit recording process is referred to as a first character string, and the obtained muscle habit is referred to as a first muscle habit; the character string obtained in the user identity authentication process is called a second character string, and the obtained muscle habit is called a second muscle habit. In the muscle habit recording process, a first keyboard knocking request can be sent to a user, and the user is requested to randomly knock keys in a designated area of a keyboard for multiple times within a first preset time period. The length of the first preset time period can be set by a person skilled in the art according to actual needs. For example, when the first preset time period is 5 seconds, the user is requested to randomly tap the keys of the keyboard within the designated area of the keyboard by means of muscle memory for 5 seconds, and the user can randomly tap the keys within the designated area of the keyboard within the 5 seconds, and the number of taps may or may not be limited. The first character string tapped by the user is transmitted to the background, and in step S101, the background acquires the first character string formed by tapping the keyboard in the designated area of the keyboard within the first preset time period.

The designated area of the keyboard may be an area in a physical keyboard or a virtual keyboard of a device such as a mobile phone, a notebook Computer, a Personal Computer (PC), a Personal Digital Assistant (PDA), or the like, and specifically, the designated area of the keyboard may include an alphabet key area, a number key area, and a special character key area. Taking the keyboard designation area as an area in the physical keyboard as an example, the keyboard designation area may be shown as a shaded portion in fig. 1 b.

Step S102, analyzing characters in the first character string from multiple dimensions to obtain first muscle habits corresponding to the multiple dimensions in the keyboard knocking process, and determining multiple verification conditions according to the first muscle habits corresponding to the multiple dimensions.

After the first character string is obtained, the characters in the first character string can be analyzed from multiple dimensions, and first muscle habits corresponding to the multiple dimensions in the keyboard knocking process are obtained. Wherein the plurality of dimensions may include: the character number proportion dimension, the overall character tapping sequence dimension and the inter-character tapping sequence dimension. The following describes a specific analysis method for each of these 3 dimensions.

(1) The analysis of the number of characters over dimension may include: searching the same character in the first character string, counting the number of the same character, and calculating the ratio of the number of the same character in the total number of the first character string; sorting the characters according to the sequence of the ratio from high to low, selecting N characters with the ratio arranged at the front, and obtaining a first muscle habit corresponding to the ratio dimension of the number of the characters in the process of knocking the keyboard; wherein N is a positive integer. The value of N can be set by those skilled in the art according to actual needs.

Specifically, the characters in the first string may be letters, numbers, and special characters, such as "; "," - "," ═ and the like. The same characters are searched in the first character string, the number of characters of each same character is counted, and then the ratio of the number of characters of each same character in the total number of characters of the first character string is calculated, for example, the number of characters of a certain character is divided by the total number of characters of the first character string, and the calculation result is used as the ratio. Then, sorting the characters according to the sequence of the proportion from high to low, and when N is 5, selecting 5 characters with the proportion arranged at the front, for example, the 5 characters are "d", "t", and "in sequence; "," o "and" p ", wherein the proportion corresponding to" d "is 20%, the proportion corresponding to" t "is 10%, and"; the proportion corresponding to the character number is 9 percent, the proportion corresponding to the character number is 5 percent, and the proportion corresponding to the character number is 4 percent, so that the first muscle habit corresponding to the dimension of the proportion corresponding to the character number in the process of knocking the keyboard according to the 5 characters can be expressed as { "d", "t", "; "," o "," p "}.

(2) The analysis of the overall character stroke order dimension may include: aiming at each character in the N characters which are arranged at the front in the proportion, calculating the average value of the serial numbers of the knocking sequences according to the serial numbers of the knocking sequences of the characters in the first character string to obtain the average value of the whole knocking sequences corresponding to the characters; sequencing the N characters according to the sequence of the average value of the overall knocking sequence from low to high, selecting M characters arranged at the front, and obtaining a first muscle habit corresponding to the dimension of the overall knocking sequence of the characters in the keyboard knocking process; wherein M is a positive integer, and M is less than or equal to N. The value of M can be set by those skilled in the art according to actual needs.

Specifically, according to the character position of each character in the first character string, the knocking sequence number of the character in the first character string is determined. For example, where the positions of the characters in the 1 st, 3 rd, 5 th, 7 th and 8 th character in the first character string are all the characters "d", then determining the tap sequence number of "d" in the first character string includes: 1. 3, 5, 7 and 8. In this way, the tap order number of each of the N characters preceding the first character string is determined.

After determining the tapping sequence number of each character in the first character string in the N characters which are arranged at the front of the first character string, calculating the average value of the tapping sequence numbers according to the tapping sequence number of the character in the first character string aiming at each character in the N characters, and obtaining the overall tapping sequence average value corresponding to the character. For example, the tap order number of "d" in the first string includes: 1. 3, 5, 7 and 8, the average value of the serial numbers of the knocking sequences is (1+3+5+7+8)/5 is 4.8, that is, "d" corresponds to the average value of the whole knocking sequences being 4.8.

Assuming that N is 5, the top 5 characters include "d", "t", and "; the average value of the overall knocking sequence corresponding to the d is 4.8, and the average value of the overall knocking sequence corresponding to the t is 10, "; the mean value of the corresponding overall knocking sequences is 15, the mean value of the corresponding overall knocking sequences is 4, and the mean value of the corresponding overall knocking sequences is 9.5. 5 characters are sorted according to the sequence of the average value of the whole knocking sequence from low to high, and the obtained sorting results are ' o ','d ', ' p ','t ' and '; ". If M is 3, the top 3 characters, i.e., "o", "d", and "p", are selected from the sorting result, and the first muscle habit corresponding to the overall character-tapping sequence dimension during the keyboard-tapping process, which is obtained according to these 5 characters, can be represented as { "o", "d", "p" }.

(3) The analysis of the tap order dimension between characters may include: combining every two of the N characters with the higher proportion to generate a plurality of first character pairs; each first character pair comprises two characters; aiming at each first character pair, setting the sequence of knocking two characters according to the integral average value of the knocking sequence corresponding to each character in the two characters of the first character pair to obtain a second character pair corresponding to the first character pair; and selecting a preset number of second character pairs from the second character pairs corresponding to the first character pairs as a first muscle habit corresponding to the stroke sequence dimension among the characters in the process of knocking the keyboard.

Assuming that N is 5, the top 5 characters include "d", "t", and "; "," o "and" p ", and combining these 5 characters two by two, 10 first character pairs can be generated, each first character pair containing two characters. The 10 first character pairs are ("d", "t"), ("d", ";"), ("d", "o"), ("d", "p"), ("t", ";"), ("t", "o"), ("t", "p"), ("," "p", and ("o", "p"), respectively. And aiming at each first character pair, sequencing the two characters according to the average value of the integral knocking sequence corresponding to each of the two characters of the first character pair from low to high according to the average value of the integral knocking sequence, and setting the knocking sequence of the two characters to obtain a second character pair corresponding to the first character pair. The second character pair contains two characters and the ordinal tap order of the two characters.

Taking a first character pair as ("d", "t") as an example, assuming that the average value of the overall tapping sequence corresponding to "d" is 4.8, and the average value of the overall tapping sequence corresponding to "t" is 10, because the average value of the overall tapping sequence corresponding to "d" is lower than the average value of the overall tapping sequence corresponding to "t", setting the tapping sequence of the two characters as tapping "d" first and then tapping "t", obtaining a second character pair corresponding to the first character pair, wherein the second character pair can be represented as { "d", "t", wherein the left character in { } is the tapping character first, the right character is the tapping character after, and the left-right position of the character in the second character pair reflects the tapping sequence of the two characters, and follows the principle of left front, right back.

After the second character pairs corresponding to the first character pairs are determined, selecting a preset number of second character pairs from the second character pairs corresponding to the first character pairs as first muscle habits corresponding to the beating sequence dimensionality among the characters in the process of beating the keyboard. Specifically, for each second character pair, the difference between the overall tapping order mean values corresponding to two characters in the second character pair can be calculated; considering that the second character pairs with larger difference values of the overall tapping sequence mean values can more accurately reflect the muscle habits of the user compared with the second character pairs with smaller difference values of the overall tapping sequence mean values, the plurality of second character pairs can be sorted according to the sequence of the difference values from large to small, and the second character pairs with the preset number arranged at the front are selected from the sorted plurality of second character pairs to serve as the first muscle habits corresponding to the tapping sequence dimensions among the characters in the process of tapping the keyboard. For example, when the preset number is 3, the first muscle habit corresponding to the stroke order dimension between the characters may include: { "o", "; "}, {" d ","; "} and {" o "," t "}.

After the first muscle habits corresponding to the multiple dimensions are obtained, multiple verification conditions can be determined according to the first muscle habits corresponding to the multiple dimensions. Specifically, the first muscle habit corresponding to each dimension may be split, for example, 2 verification conditions are split for each dimension, and then a plurality of verification conditions may be conveniently obtained by splitting the first muscle habit corresponding to a plurality of dimensions. One skilled in the art may determine a plurality of verification conditions according to the first muscle habits corresponding to a plurality of dimensions according to actual needs, which is not limited herein. For example, the plurality of verification conditions may include: at least 3 characters in the 5 characters which are the same in the second character string and are higher than the same in the first character string are characters in the first muscle habit corresponding to the character number proportion dimension; sequencing 5 characters which are the same in the second character string and are higher than the former in the ratio according to the sequence of the average value of the integral knocking sequence from low to high, wherein at least 2 characters in the former 3 characters are characters in the first muscle habit corresponding to the dimension of the integral knocking sequence of the characters; and at least 1 character pair in the character pairs which are obtained by combining every two of the 5 characters which are the same in the second character string and are higher than the first character in the character pairs containing the knocking sequence is the second character pair in the first muscle habit corresponding to the knocking sequence dimension between the characters, and the like.

Step S103, in the process of user identity authentication, a second character string formed by the user through keyboard knocking in the designated area of the keyboard within a second preset time period is obtained.

In the case that the user forgets the password and the like needs to perform the authentication, the user identity may be verified according to the plurality of authentication conditions determined in step S102. In the user identity authentication process, a second keyboard knocking request can be sent to the user, and the user is requested to randomly knock keys in the designated area of the keyboard for multiple times within a second preset time period. The length of the second preset time period may be the same as or different from the length of the first preset time period, and is not limited herein. For example, when the second preset time period is 5 seconds, the user is requested to randomly tap the keys of the keyboard within the designated area of the keyboard by means of muscle memory for 5 seconds, and the user can randomly tap the keys within the designated area of the keyboard within the 5 seconds, and the number of taps may or may not be limited. The second character string tapped by the user is transmitted to the background, and in step S103, the background acquires the second character string formed by tapping the keyboard in the designated area of the keyboard within a second preset time period.

And step S104, analyzing the characters in the second character string from multiple dimensions to obtain second muscle habits corresponding to the multiple dimensions in the keyboard knocking process.

After the second character string is obtained, the characters in the second character string can be analyzed from multiple dimensions, and second muscle habits corresponding to the multiple dimensions in the keyboard knocking process are obtained. Wherein the plurality of dimensions may include: the character number proportion dimension, the overall character tapping sequence dimension and the inter-character tapping sequence dimension. For the specific analysis method of these 3 dimensions, the analysis method in step S102 may be referred to.

Specifically, the analysis of the character number ratio dimension may include: searching the same character in the second character string, counting the number of the same character, and calculating the ratio of the number of the same character in the total number of the second character string; and sorting the characters according to the sequence of the ratio from high to low, selecting N characters with the ratio arranged at the front, and obtaining a second muscle habit corresponding to the ratio dimension of the number of the characters in the process of knocking the keyboard.

The analysis of the overall character stroke order dimension may include: aiming at each character in the N characters which are arranged at the front in the proportion, calculating the average value of the serial numbers of the knocking sequences according to the serial numbers of the knocking sequences of the characters in the second character string to obtain the average value of the whole knocking sequences corresponding to the characters; and sequencing the N characters according to the sequence of the average value of the overall knocking sequence from low to high, selecting M characters arranged at the front, and obtaining a second muscle habit corresponding to the dimension of the overall knocking sequence of the characters in the keyboard knocking process.

The analysis of the tap order dimension between characters may include: combining every two of the N characters with the higher proportion to generate a plurality of third character pairs; each third character pair comprises two characters; for each third character pair, setting the sequence of the two characters according to the average value of the integral knocking sequence corresponding to each of the two characters of the third character pair to obtain a fourth character pair corresponding to the third character pair; and selecting a preset number of fourth character pairs from the fourth character pairs corresponding to the third character pairs as a second muscle habit corresponding to the stroke sequence dimension among the characters in the process of knocking the keyboard.

Step S105, judging whether second muscle habits corresponding to multiple dimensions meet at least two verification conditions in multiple verification conditions; if yes, go to step S106; if not, step S107 is executed.

After the second muscle habits corresponding to the multiple dimensions are obtained through analysis, whether the second muscle habits corresponding to the multiple dimensions meet at least two verification conditions in the multiple verification conditions is judged. If so, it is indicated that the matching degree of the second muscle habit and the pre-recorded first muscle habit is higher, the comparison is successful, and the user corresponding to the second muscle habit is likely to be the same user as the user corresponding to the first muscle habit, then step S106 is executed, and it is determined that the identity authentication of the user passes. If not, it is determined that the second muscle habit is lower in matching degree with the pre-recorded first muscle habit and the comparison fails, and it is likely that the user corresponding to the second muscle habit is not the same as the user corresponding to the first muscle habit, step S107 is performed to determine that the authentication of the user fails.

And step S106, judging that the user passes the authentication.

Optionally, after the identity verification of the user is judged to be passed, the newly summarized second muscle habits can be stored into the system again in a machine learning mode each time to serve as a verification library for the next verification in the future, and dynamic updating of the verification library is achieved. Therefore, the system can still accurately detect the real identity information of the user even if the behavior habit of the user continuously and dynamically changes.

The muscle memory of the arm and the palm can not be changed easily, so the verification mode is reliable and credible, and if the muscle memory resetting password or the password recovery failure is tried for many times, the verification mode can be switched to the conventional verification modes such as the identity card number, the face recognition, the mobile phone number, the bank card number and the like for verification.

Step S107, the authentication of the user is judged not to be passed.

Optionally, in the process that the user randomly taps the keyboard for a preset time period (a first preset time period or a second preset time period) in the designated area of the keyboard by muscle memory, the user may be required to tap the year, month and day of the birthday of the user and the lowercase pinyin of the name as entanglement, for example, the user is required to enter 8 digits of the year, month and day of the birthday before randomly tapping the keyboard for 5 seconds, and then enter the lowercase pinyin of the name after randomly tapping the keyboard for 5 seconds, so as to form a user image in a composite manner, and facilitate subsequent use.

According to the user authentication method based on muscle memory of the user provided by the embodiment, in the authentication process, the user does not need to input personal information such as identification numbers, mobile phone numbers, bank card numbers and the like, does not need to carry out face recognition, only needs to randomly tap the keyboard in a designated area of the keyboard for a period of time, by comparing the muscle habits of the user corresponding to a plurality of dimensions during the keyboard knocking process with the verification conditions determined in advance based on the muscle habits of the user, can realize user authentication conveniently, both protect user's personal information, be convenient for again the user accomplish authentication, especially to forgetful or the old user who is not familiar with operating software application, greatly improved authentication's convenience, the speed that the promotion user got for the password or reset the password by a wide margin, and then improved internet platform's user viscidity.

Fig. 2 is a block diagram showing a structure of a user authentication apparatus based on muscle memory of a user according to an embodiment of the present invention, as shown in fig. 2, the apparatus including: a first obtaining module 210, a first analyzing module 220, a second obtaining module 230, a second analyzing module 240, and a determining module 250.

The first obtaining module 210 is adapted to: acquiring a first character string formed by a user in a keyboard designated area in a first preset time period through keyboard tapping.

The first analysis module 220 is adapted to: analyzing the characters in the first character string from multiple dimensions to obtain first muscle habits corresponding to the multiple dimensions in the keyboard knocking process, and determining multiple verification conditions according to the first muscle habits corresponding to the multiple dimensions.

The second obtaining module 230 is adapted to: in the user identity authentication process, a second character string formed by the user in a designated area of the keyboard through knocking the keyboard within a second preset time period is obtained.

The second analysis module 240 is adapted to: and analyzing the characters in the second character string from multiple dimensions to obtain second muscle habits corresponding to the multiple dimensions in the keyboard knocking process.

The determination module 250 is adapted to: judging whether second muscle habits corresponding to the multiple dimensions meet at least two verification conditions in the multiple verification conditions; and if so, judging that the user passes the authentication.

Optionally, the plurality of dimensions comprises: the character number proportion dimension, the overall character tapping sequence dimension and the inter-character tapping sequence dimension.

Optionally, the first analysis module 220 is further adapted to: searching the same character in the first character string, counting the number of the same character, and calculating the ratio of the number of the same character in the total number of the first character string; sorting the characters according to the sequence of the ratio from high to low, selecting N characters with the ratio arranged at the front, and obtaining a first muscle habit corresponding to the ratio dimension of the number of the characters in the process of knocking the keyboard; wherein N is a positive integer.

Optionally, the first analysis module 220 is further adapted to: aiming at each character in N characters which are arranged at the front in proportion, calculating the average value of the serial numbers of the knocking sequences according to the serial numbers of the knocking sequences of the characters in the first character string to obtain the average value of the whole knocking sequences corresponding to the characters; sequencing the N characters according to the sequence of the average value of the overall knocking sequence from low to high, selecting M characters arranged at the front, and obtaining a first muscle habit corresponding to the dimension of the overall knocking sequence of the characters in the keyboard knocking process; wherein M is a positive integer, and M is less than or equal to N.

Optionally, the first analysis module 220 is further adapted to: combining every two of the N characters with the higher occupation arrangement to generate a plurality of first character pairs; each first character pair comprises two characters; aiming at each first character pair, setting the sequence of knocking two characters according to the integral average value of the knocking sequence corresponding to each character in the two characters of the first character pair to obtain a second character pair corresponding to the first character pair; and selecting a preset number of second character pairs from the second character pairs corresponding to the first character pairs as a first muscle habit corresponding to the stroke sequence dimension among the characters in the process of knocking the keyboard.

According to the user authentication device based on the muscle memory of the user provided by the embodiment, in the authentication process, the user does not need to input personal information such as identification numbers, mobile phone numbers, bank card numbers and the like, does not need to carry out face recognition, only needs to randomly tap the keyboard in a designated area of the keyboard for a period of time, by comparing the muscle habits of the user corresponding to a plurality of dimensions during the keyboard knocking process with the verification conditions determined in advance based on the muscle habits of the user, can realize user authentication conveniently, both protect user's personal information, be convenient for again the user accomplish authentication, especially to forgetful or the old user who is not familiar with operating software application, greatly improved authentication's convenience, the speed that the promotion user got for the password or reset the password by a wide margin, and then improved internet platform's user viscidity.

The invention also provides a nonvolatile computer storage medium, and the computer storage medium stores at least one executable instruction which can execute the user identity authentication method based on the muscle memory of the user in any method embodiment.

Fig. 3 is a schematic structural diagram of a computing device according to an embodiment of the present invention, and the specific embodiment of the present invention does not limit the specific implementation of the computing device.

As shown in fig. 3, the computing device may include: a processor (processor)302, a communication Interface 304, a memory 306, and a communication bus 308.

Wherein:

the processor 302, communication interface 304, and memory 306 communicate with each other via a communication bus 308.

A communication interface 304 for communicating with network elements of other devices, such as clients or other servers.

The processor 302 is configured to execute the program 310, and may specifically execute the relevant steps in the embodiment of the user identity authentication method based on the muscle memory of the user.

In particular, program 310 may include program code comprising computer operating instructions.

The processor 302 may be a central processing unit CPU, or an Application Specific Integrated Circuit (ASIC), or one or more Integrated circuits configured to implement an embodiment of the present invention. The computing device includes one or more processors, which may be the same type of processor, such as one or more CPUs; or may be different types of processors such as one or more CPUs and one or more ASICs.

And a memory 306 for storing a program 310. Memory 306 may comprise high-speed RAM memory and may also include non-volatile memory (non-volatile memory), such as at least one disk memory.

The program 310 may specifically be adapted to cause the processor 302 to perform a user authentication method based on a muscle memory of a user in any of the above-described method embodiments. For specific implementation of each step in the program 310, reference may be made to corresponding steps and corresponding descriptions in units in the above embodiment of user identity authentication based on muscle memory of a user, which are not described herein again. It can be clearly understood by those skilled in the art that, for convenience and brevity of description, the specific working processes of the above-described devices and modules may refer to the corresponding process descriptions in the foregoing method embodiments, and are not described herein again.

The algorithms and displays presented herein are not inherently related to any particular computer, virtual machine, or other apparatus. Various general purpose systems may also be used with the teachings herein. The required structure for constructing such a system will be apparent from the description above. Moreover, the present invention is not directed to any particular programming language. It is appreciated that a variety of programming languages may be used to implement the teachings of the present invention as described herein, and any descriptions of specific languages are provided above to disclose the best mode of the invention.

In the description provided herein, numerous specific details are set forth. It is understood, however, that embodiments of the invention may be practiced without these specific details. In some instances, well-known methods, structures and techniques have not been shown in detail in order not to obscure an understanding of this description.

Similarly, it should be appreciated that in the foregoing description of exemplary embodiments of the invention, various features of the invention are sometimes grouped together in a single embodiment, figure, or description thereof for the purpose of streamlining the disclosure and aiding in the understanding of one or more of the various inventive aspects. However, the disclosed method should not be interpreted as reflecting an intention that: that the invention as claimed requires more features than are expressly recited in each claim. Rather, as the following claims reflect, inventive aspects lie in less than all features of a single foregoing disclosed embodiment. Thus, the claims following the detailed description are hereby expressly incorporated into this detailed description, with each claim standing on its own as a separate embodiment of this invention.

Those skilled in the art will appreciate that the modules in the device in an embodiment may be adaptively changed and disposed in one or more devices different from the embodiment. The modules or units or components of the embodiments may be combined into one module or unit or component, and furthermore they may be divided into a plurality of sub-modules or sub-units or sub-components. All of the features disclosed in this specification (including any accompanying claims, abstract and drawings), and all of the processes or elements of any method or apparatus so disclosed, may be combined in any combination, except combinations where at least some of such features and/or processes or elements are mutually exclusive. Each feature disclosed in this specification (including any accompanying claims, abstract and drawings) may be replaced by alternative features serving the same, equivalent or similar purpose, unless expressly stated otherwise.

Furthermore, those skilled in the art will appreciate that while some embodiments described herein include some features included in other embodiments, rather than other features, combinations of features of different embodiments are meant to be within the scope of the invention and form different embodiments. For example, in the claims, any of the claimed embodiments may be used in any combination.

The various component embodiments of the invention may be implemented in hardware, or in software modules running on one or more processors, or in a combination thereof. Those skilled in the art will appreciate that a microprocessor or Digital Signal Processor (DSP) may be used in practice to implement some or all of the functionality of some or all of the components in accordance with embodiments of the present invention. The present invention may also be embodied as apparatus or device programs (e.g., computer programs and computer program products) for performing a portion or all of the methods described herein. Such programs implementing the present invention may be stored on computer-readable media or may be in the form of one or more signals. Such a signal may be downloaded from an internet website or provided on a carrier signal or in any other form.

It should be noted that the above-mentioned embodiments illustrate rather than limit the invention, and that those skilled in the art will be able to design alternative embodiments without departing from the scope of the appended claims. In the claims, any reference signs placed between parentheses shall not be construed as limiting the claim. The word "comprising" does not exclude the presence of elements or steps not listed in a claim. The word "a" or "an" preceding an element does not exclude the presence of a plurality of such elements. The invention may be implemented by means of hardware comprising several distinct elements, and by means of a suitably programmed computer. In the unit claims enumerating several means, several of these means may be embodied by one and the same item of hardware. The usage of the words first, second and third, etcetera do not indicate any ordering. These words may be interpreted as names.

Claims

1. A method of user identity verification based on user muscle memory, the method comprising:

and if so, judging that the user passes the authentication.

2. The method of claim 1, wherein the plurality of dimensions comprises: the character number proportion dimension, the overall character tapping sequence dimension and the inter-character tapping sequence dimension.

3. The method of claim 2, wherein analyzing the characters in the first character string from a plurality of dimensions to obtain a first muscle habit corresponding to the plurality of dimensions during the keyboard stroke further comprises:

4. The method of claim 3, wherein analyzing the characters in the first character string from a plurality of dimensions to obtain a first muscle habit corresponding to the plurality of dimensions during the keyboard stroke further comprises:

aiming at each character in N characters which are arranged at the front in proportion, calculating the average value of the knocking sequence numbers according to the knocking sequence numbers of the characters in the first character string to obtain the average value of the whole knocking sequence corresponding to the character;

5. The method of claim 3, wherein analyzing the characters in the first character string from a plurality of dimensions to obtain a first muscle habit corresponding to the plurality of dimensions during the keyboard stroke further comprises:

aiming at each first character pair, setting the sequence of knocking of the two characters according to the average value of the integral knocking sequence corresponding to each character in the two characters of the first character pair to obtain a second character pair corresponding to the first character pair;

6. A user authentication apparatus based on muscle memory of a user, the apparatus comprising:

the judging module is suitable for judging whether second muscle habits corresponding to multiple dimensions meet at least two verification conditions in the multiple verification conditions; and if so, judging that the user passes the authentication.

7. The apparatus of claim 6, wherein the plurality of dimensions comprise: the character number proportion dimension, the overall character tapping sequence dimension and the inter-character tapping sequence dimension.

8. The apparatus of claim 7, wherein the first analysis module is further adapted to:

9. A computing device, comprising: the system comprises a processor, a memory, a communication interface and a communication bus, wherein the processor, the memory and the communication interface complete mutual communication through the communication bus;

the memory is used for storing at least one executable instruction, and the executable instruction causes the processor to execute the operation corresponding to the user identity authentication method based on the muscle memory of the user according to any one of claims 1-5.

10. A computer storage medium having stored therein at least one executable instruction for causing a processor to perform operations corresponding to the user identity verification method based on muscle memory of a user according to any one of claims 1-5.