CN110121174B - Implicit identity authentication method of mobile intelligent terminal - Google Patents
Implicit identity authentication method of mobile intelligent terminal Download PDFInfo
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- CN110121174B CN110121174B CN201910409157.2A CN201910409157A CN110121174B CN 110121174 B CN110121174 B CN 110121174B CN 201910409157 A CN201910409157 A CN 201910409157A CN 110121174 B CN110121174 B CN 110121174B
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Abstract
The invention discloses an implicit identity authentication method of a mobile intelligent terminal, which comprises the following steps: the mobile intelligent terminal authentication service system sets a password with a certain length and legal WiFi, collects touch behavior data when the password is set, and stores the touch behavior data into a database after the touch behavior data are processed by a weight-based dynamic normalization algorithm; monitoring the legality of the WiFi environment in real time, enabling a legal WiFi environment user to automatically enter a mobile intelligent terminal to check information without inputting a password, enabling an illegal WiFi environment user to input the password, comparing touch behavior data when the password is input with touch behavior data stored in a database according to a dynamic normalization algorithm based on a weight, determining the legality of the identity of an authenticated user, and enabling the authenticated user to legally enter the mobile intelligent terminal to check information; the invention enhances the existing authentication mechanism in convenience and safety and can avoid the user from frequently inputting the password.
Description
Technical Field
The invention belongs to the identity authentication technology of a mobile intelligent terminal, and particularly relates to an implicit identity authentication method of the mobile intelligent terminal.
Background
Currently, mobile smart terminals represented by smart phones have become very popular. With the rapid development of mobile intelligent terminals, the mobile application downloading service market also grows rapidly, and applications such as mobile office and mobile payment are widely used, but the mobile intelligent terminals bring convenience to people and have own security problem as well as become a challenge.
The identity authentication mechanism serves as a first security level for information security, and can enable the mobile intelligent terminal to authenticate the identity of a user, so as to ensure the use security of equipment and application programs. However, the following disadvantages generally exist in the existing identity authentication mechanism:
(1) the use is inconvenient, for example, a password mechanism requires a user to memorize one or more complex character strings, and the smart card is inconvenient to carry and easy to lose; moreover, the authentication is frequent, the authentication is needed each time the device is awakened, and the user needs to be authenticated even in a safe environment (such as at home);
(2) security defects exist, for example, password reuse, social engineering attack and other problems exist in a password mechanism, and biological characteristics can be imitated and are difficult to cancel or change once cracked; also, when the authentication mechanism is not easy to use, some users are reluctant to set any authentication mechanism, putting the mobile device at risk.
Therefore, there is a need to design an authentication method that is both secure and convenient, and meets the requirements of mobile users.
Disclosure of Invention
Aiming at the problems, the invention provides an implicit identity authentication method of a mobile intelligent terminal, which well solves the problems of inconvenient use and safety defects of the existing identity authentication mechanism.
In order to achieve the purpose, the technical scheme adopted by the invention is as follows: an implicit identity authentication method of a mobile intelligent terminal comprises the following steps:
monitoring the legality of the WiFi environment in real time through a mobile intelligent terminal system;
when the WiFi environment is legal, a user does not need to input a password and automatically enters the mobile intelligent terminal;
when the WiFi environment is illegal, the user needs to input the password, and simultaneously the validity of the touch behavior data information when the password is input is verified through a dynamic normalization algorithm based on the weight,
if the input password and the touch behavior data during the password input are legal, the mobile intelligent terminal can be accessed after the verification is passed,
if the input password or the touch behavior data information during the password input is illegal, the password or the touch behavior data information needs to be input again.
Furthermore, the password is preset through the mobile intelligent terminal, and touch behavior data during password setting are collected through various sensors built in the mobile intelligent terminal.
Further, the touch behavior data is processed by a dynamic warping algorithm based on a weight, and the processing method of the dynamic warping algorithm based on the weight is as follows:
defining the adopted values of the acquired touch behavior data of each sensor, and setting the weight of each adopted value as q1,q2,…,qn。
The user repeatedly inputs the correct password three times when setting the password,
setting the touch behavior data of each sensor as vector X when the password is input for the first time, wherein X is equal to<X1,X2,…,Xn>，
Wherein the content of the first and second substances,<X1,X2,…,Xn>respectively representing adopted values of the touch behavior data of each sensor;
setting the touch behavior data of each sensor as a vector Y when the password is input for the second time, wherein Y is equal to Y<Y1,Y2,…,Yn>，
Wherein the content of the first and second substances,<Y1,Y2,…,Yn>respectively representing adopted values of the touch behavior data of each sensor;
setting the touch behavior data of each sensor as a vector Z when the password is input for the third time, wherein Z is<Z1,Z2,…,Zn>，
Wherein the content of the first and second substances,<Z1,Z2,…,Zn>respectively representing adopted values of the touch behavior data of each sensor;
then separately X, Y, Z the geometric distance d between the three vectors is calculatedi,j，
Wherein i, j belongs to { X, Y, Z } - [ lambda ] (i ≠ j),
definition d ═ max (d)i,j) The vectors X, Y, Z and d are stored in a database.
Further, the method for verifying the validity of the touch behavior data information when the password is input by the dynamic normalization algorithm based on the weight value comprises the following steps:
the touch behavior data of the user when inputting the password is collected and recorded by each sensor,
defining data collected by each sensor as a vector U, wherein U is equal to<U1,U2,…,Un>，
Wherein the content of the first and second substances,<U1,U2,…,Un>respectively representing adopted values of the touch behavior data of each sensor;
calculating the distance d between U and X, Y, ZU,j，
Wherein j is ∈ { X, Y, Z },
definition d ═ min { d {U,jAnd if d' is less than or equal to d, the authentication is passed.
Furthermore, the sensor comprises a gyroscope, a light intensity sensor, an X-direction sensor, a Y-direction sensor, a Z-direction sensor, a magnetic field sensor and a linear acceleration sensor.
Furthermore, the weight of each sensor needs to be given in advance, and then the weight of the light intensity sensor is 0.01; the weight of the X-direction sensor is 0.35; the weight of the Y-direction sensor is 0.3; the weight of the Z-direction sensor is 0.15; the weight of the gravity sensor is 0.06; the weight of the magnetic field sensor is 0.03; the weight of the gyroscope is 0.05; the weight of the linear acceleration is 0.05.
Further, the legal WiFi is trusted WiFi added through a WiFi setting module of the mobile intelligent terminal system, and the WiFi list of the mobile intelligent terminal system contains the set trusted WiFi, which indicates that the mobile intelligent terminal is in a legal WiFi environment, otherwise, the mobile intelligent terminal is in an illegal WiFi environment.
Compared with the prior art, the invention has the following beneficial effects:
1. the legality of the WiFi environment is monitored in real time, the legal WiFi environment directly enters the mobile intelligent terminal through authentication without inputting a password, and convenience is achieved; when the mobile intelligent terminal is in an illegal WiFi environment, a password needs to be input, the legality of touch behavior data information when the password is input is determined through a dynamic normalization algorithm based on a weight, the legality of the identity of an authenticated user is judged, the mobile intelligent terminal is accessed to check the information, the information safety of the user is guaranteed, information leakage caused by password leakage is prevented, and the safety is high.
2. The dynamic regularization algorithm based on the weight is small in training data, a large amount of storage space is not needed, the time for calculating the distance between the sample to be detected and all samples in the training data set is very short, the influence caused by the unbalanced data samples of the samples can be avoided by setting the weight, the processing efficiency is high, the dynamic regularization algorithm is suitable for being used on mobile equipment, and the dynamic regularization algorithm has the advantages of being simple, rapid and easy to realize.
Drawings
FIG. 1 is a flow chart of an implementation of the implicit identity authentication method based on a mobile intelligent terminal according to the present invention;
FIG. 2 is a block diagram of a test implicit authentication mechanism of the implicit identity authentication method based on a mobile intelligent terminal according to the present invention;
FIG. 3 is a flow diagram of a log-in module of the system of FIG. 2;
FIG. 4 is a flow chart of the implicit authentication function of the dynamic warping algorithm based on weights in the system module of FIG. 2.
DETAILED DESCRIPTION OF EMBODIMENT (S) OF INVENTION
The technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the drawings in the embodiments of the present invention, and it is obvious that the described embodiments are only a part of the embodiments of the present invention, and not all of the embodiments. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.
As shown in fig. 1, the implicit identity authentication method for a mobile intelligent terminal according to the present invention includes: the mobile intelligent terminal authentication service system sets a password (4 bits or 6 bits) with a certain length and legal WiFi, and the legal WiFi is trusted WiFi added through a WiFi setting module of the mobile intelligent terminal system; when a password is set, touch behavior data at the moment are collected through a gyroscope, a light intensity sensor, a direction sensor (an X direction sensor, a Y direction sensor and a Z direction sensor), a magnetic field sensor and a linear acceleration sensor which are arranged in the mobile intelligent terminal, meanwhile, the digital-analog behavior data are processed through a dynamic regularization algorithm based on weights, different weights are set for the touch behavior data due to different importance of the sensor data in touch behavior judgment, and therefore the identification accuracy is guaranteed, and the dynamic regularization algorithm processing method based on the weights comprises the following steps:
defining the adopted values of the acquired touch behavior data of each sensor, and setting the weight of each adopted value as q1,q2,…,qn。
The user repeatedly inputs the correct password three times when setting the password,
setting the touch behavior data of each sensor as vector X when the password is input for the first time, wherein X is equal to<X1,X2,…,Xn>，
Wherein the content of the first and second substances,<X1,X2,…,Xn>respectively representing adopted values of the touch behavior data of each sensor;
setting the touch behavior data of each sensor as a vector Y when the password is input for the second time, wherein Y is equal to Y<Y1,Y2,…,Yn>，
Wherein the content of the first and second substances,<Y1,Y2,…,Yn>respectively representing adopted values of the touch behavior data of each sensor;
setting the touch behavior data of each sensor as a vector Z when the password is input for the third time, wherein Z is<Z1,Z2,…,Zn>，
Wherein the content of the first and second substances,<Z1,Z2,…,Zn>respectively representing adopted values of the touch behavior data of each sensor;
then separately X, Y, Z the geometric distance d between the three vectors is calculatedi,j；
Wherein i, j belongs to { X, Y, Z } - [ lambda ] (i ≠ j),
definition d ═ max (d)i,j)
The algorithm is a dynamic regularization algorithm based on the weight, the touch behavior data are processed by the dynamic regularization algorithm based on the weight to obtain vectors X, Y, Z and d, the vectors d are stored in a database, and the obtained data are training data.
In the process of using the mobile terminal, the legality of the mobile terminal in a WiFi environment is monitored in real time, namely when the WiFi list of the mobile intelligent terminal contains the set trusted WiFi, the mobile intelligent terminal is in the legal WiFi environment, and in the legal WiFi environment, a user does not need to input a password and automatically enters the mobile intelligent terminal to check information, so that the mobile intelligent terminal is convenient and avoids the tedious and repeated password input; an illegal WiFi environment user needs to input a legal password, touch behavior data when the password is input is compared with touch behavior data stored in a database according to a dynamic normalization algorithm based on a weight, and the legality of the touch behavior data is judged, wherein the method comprises the following steps:
when the password is input for verification, the touch behavior data of the user is collected and recorded by each sensor,
defining parameter vector collected by each sensor as U, wherein U is equal to<U1,U2,…,Un>，
Wherein the content of the first and second substances,<U1,U2,…,Un>respectively representing adopted values of the touch behavior data of each sensor;
calculating the distance d between U and X, Y, ZU,j，
Wherein j is ∈ { X, Y, Z },
definition d ═ min { d {U,jComparing with the training data d, if d' is less than or equal to d, determining that the identity of the authenticated user is legal, and if the identity is verified to be legal, entering the mobile intelligent terminal to check information, so that information leakage caused by password leakage is prevented, and the safety is higher.
The dynamic regularization algorithm based on the weight is very small in training data, a large amount of storage space is not needed, and the time for calculating the distance between the sample to be detected and all samples in the training data set is very short; the weight of the algorithm needs to be given in advance, and the weight of the light intensity sensor is 0.01; the weight of the X-direction sensor is 0.35; the weight of the Y-direction sensor is 0.3; the weight of the Z-direction sensor is 0.15; the weight of the gravity sensor is 0.06; the weight of the magnetic field sensor is 0.03; the weight of the gyroscope is 0.05; the weight of the linear acceleration is 0.05, the influence caused by unbalanced data in the sample can be avoided by setting the weight, and different weights can be set according to different environments; it can be seen that the algorithm is suitable for use on mobile devices, with the advantages of being simple, fast and easy to implement.
As shown in fig. 2-4, in order to implement the above method, a test process for implementing the method is given below, where the test process is an implicit identity authentication mechanism based on the above method, and includes a login module, an implicit authentication module, and a notepad module, where the implicit authentication module has an implicit authentication function of WiFi setting, obtaining sensor data, password setting, and a dynamic warping algorithm based on weights; the notepad module mainly realizes the increase, deletion, modification and check of data recorded by the user and can store important information of the user.
The main function of the WIFI setting is to add and delete trusted WIFI. The trusted WIFI refers to the safety WIFI set by the user, and if the WIFI in the mobile phone list of the user contains the trusted WIFI set by the user, the current environment where the user is located is very safe; the WiFi setting has a plurality of specific interfaces including ScanResult, WiFi configuration, WiFi info and WiFi manager, and the function descriptions of the interfaces are as follows:
the interface algorithm for the WiFi setup is described as follows:
the login module has the functions that when a user opens a login interface for the first time, the interface prompts the user to input a password, when the user inputs the password repeatedly three times, the system is a registration listener of the sensor, and a registration algorithm set by the sensor is described as follows:
and storing three groups of touch behavior data into a database while setting the password, wherein the corresponding algorithm is described as follows:
the touch behavior data is processed through a dynamic normalization algorithm based on the weight to form specific touch behavior information of the user; the description of the dynamic warping algorithm based on the weight value of the method is as follows:
when the user logs in again, whether the implicit authentication module is started or not is firstly confirmed, if the implicit authentication module is not started, only a password is input during logging in, touch behavior data authentication is not performed, if the implicit authentication module is started, the state of the WiFi environment where the notepad is located can be monitored in real time through the implicit authentication function, and the realized algorithm is described as follows:
therefore, when the user is in a safe WiFi environment, the user can successfully enter the notepad page without logging in; when a user is in a non-secure WiFi environment, the login module can start the implicit authentication function of the implicit authentication module based on the dynamic warping algorithm of the weight to authenticate the touch behavior information, the login success can be calculated only if the password and the touch behavior data when the password is input are authenticated by the user, the notepad page can be accessed to store important information, and the description of calling the corresponding dynamic warping algorithm based on the weight when the implicit authentication module is correspondingly started is as follows:
certainly, the implicit identity authentication mechanism can realize the perception and identification of the user identity by the equipment, can also be applied to other fields, such as smart cities, smart homes, predictive mobile computing and the like, can provide personalized services for the user, and has wide application prospects.
Although the present invention has been described in detail with reference to the foregoing embodiments, it will be apparent to those skilled in the art that various changes in the embodiments and/or modifications of the invention can be made, and equivalents and modifications of some features of the invention can be made without departing from the spirit and scope of the invention.
Claims (4)
1. An implicit identity authentication method of a mobile intelligent terminal is characterized in that: the method comprises the following steps:
monitoring the legality of the WiFi environment in real time through a mobile intelligent terminal system;
when the WiFi environment is legal, a user does not need to input a password and automatically enters the mobile intelligent terminal;
when the WiFi environment is illegal, the user needs to input the password, and simultaneously the validity of the touch behavior data information when the password is input is verified through a dynamic normalization algorithm based on the weight,
if the input password and the touch behavior data during the password input are legal, the mobile intelligent terminal can be accessed after the verification is passed,
if the input password or the touch behavior data information during password input is illegal, re-inputting the password or the touch behavior data information;
the password is preset through the mobile intelligent terminal, and touch behavior data during password setting are collected through all sensors built in the mobile intelligent terminal;
the touch behavior data is processed by a dynamic warping algorithm based on weight, and the processing method of the dynamic warping algorithm based on weight is as follows:
defining adopted values of the collected touch behavior data of each sensor, and setting each adopted valueThe weights are q1,q2,…,qn；
The user repeatedly inputs the correct password three times when setting the password,
setting the touch behavior data of each sensor as vector X when the password is input for the first time, wherein X is equal to<X1,X2,…,Xn>，
Wherein<X1,X2,…,Xn>Respectively representing adopted values of the touch behavior data of each sensor;
setting the touch behavior data of each sensor as a vector Y when the password is input for the second time, wherein Y is equal to Y<Y1,Y2,…,Yn>，
Wherein<Y1,Y2,…,Yn>Respectively representing adopted values of the touch behavior data of each sensor;
setting the touch behavior data of each sensor as a vector Z when the password is input for the third time, wherein Z is<Z1,Z2,…,Zn>，
Wherein<Z1,Z2,…,Zn>Respectively representing adopted values of the touch behavior data of each sensor;
then separately X, Y, Z the geometric distance d between the three vectors is calculatedi,j；
Wherein i, j belongs to { X, Y, Z } - [ lambda ] (i ≠ j),
definition d ═ max (d)i,j) Storing vectors X, Y, Z and d in the database;
the method for verifying the legality of the touch behavior data information when the password is input through the dynamic normalization algorithm based on the weight at the same time comprises the following steps:
the touch behavior data of the user when inputting the password is collected and recorded by each sensor,
defining data collected by each sensor as a vector U, wherein U is equal to<U1,U2,…,Un>，
Wherein the content of the first and second substances,<U1,U2,…,Un>respectively representing adopted values of the touch behavior data of each sensor;
calculating the distance d between U and X, Y, ZU,j，
Wherein j is ∈ { X, Y, Z },
definition d ═ min { d {U,jAnd if d' is less than or equal to d, the authentication is passed.
2. The implicit identity authentication method of the mobile intelligent terminal according to claim 1, wherein: the sensor comprises a gyroscope, a light intensity sensor, an X-direction sensor, a Y-direction sensor, a Z-direction sensor, a magnetic field sensor and a linear acceleration sensor.
3. The implicit identity authentication method of the mobile intelligent terminal according to claim 2, wherein: if the weight of each sensor needs to be given in advance, the weight of the light intensity sensor is 0.01; the weight of the X-direction sensor is 0.35; the weight of the Y-direction sensor is 0.3; the weight of the Z-direction sensor is 0.15; the weight of the gravity sensor is 0.06; the weight of the magnetic field sensor is 0.03; the weight of the gyroscope is 0.05; the weight of the linear acceleration is 0.05.
4. The implicit identity authentication method of the mobile intelligent terminal according to claim 1, wherein: the legal WiFi is the trusted WiFi added by the WiFi setting module of the mobile intelligent terminal system, and the WiFi list of the mobile intelligent terminal system contains the set trusted WiFi, which indicates that the mobile intelligent terminal is in a legal WiFi environment, or else, the mobile intelligent terminal is in an illegal WiFi environment.
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