CN103533546B - Implicit user verification and privacy protection method based on multi-dimensional behavior characteristics - Google Patents
Implicit user verification and privacy protection method based on multi-dimensional behavior characteristics Download PDFInfo
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Abstract
The invention relates to an implicit user verification and privacy protection method based on multi-dimensional behavior characteristics. The method comprises the steps as follows: a, data of mobile equipment operation behaviors of a legitimate user is collected; b, a legitimate user operation characteristic model is established; c, a support vector machine is utilized for comparing current behavior characteristic vector with the legitimate user operation characteristic model, so that an operation comparing conclusion about whether a current user is legitimate is obtained, and the confidence level of the operation comparing conclusion is obtained; and d, probability that the current user is legitimate is calculated by a confidence level algorithm according to the current behavior characteristic vector and the confidence level, when the probability of the legitimate user is higher than a set threshold value, the current user is confirmed to be legitimate, otherwise, mobile equipment starts a privacy protection protocol which is set in advance. According to the implicit user verification and privacy protection method based on the multi-dimensional behavior characteristics, the power consumption is low, the probability of simulation and attack is low, accurate user identity recognition can be performed under the condition that the user cannot perceive, and a corresponding privacy protective measure is taken.
Description
Technical field
The present invention relates to a kind of privacy user's checking and method for secret protection, especially a kind of to be based on various dimensions behavior characteristicss
Implicit user verification and method for secret protection, belong to the technical field of secret protection.
Background technology
With the development of modern information technologies, people have been increasingly dependent on by various mobile devices, such as mobile phone,
Panel computer etc. comes receiving and dispatching mail, share photos, online transaction, or even smart home etc..However, these complicated functions all can
Some are brought with regard to safety and the hidden danger of privacy leakage.Although these mobile devices are increasingly individualized, but as long as quick
In the case that the personal information of sense is not compromised, many users are still ready for the equipment of oneself to lend other people, such as family into
Member, friend, colleague etc..On the other hand, in order to not show the distrust for other side, in most cases user be will not be in handle
Equipment is applied some and information protection with password etc. before giving other side.In this case, do not examined when user switches
The fast verification of feel and the access control to equipment owner's privacy information become extremely important.
The method of user's checking is traditionally used for mostly by password, or sets up specific agreement to limit other people make
Use specification.This method is excessively detailed and loaded down with trivial details, and many users, particularly cellphone subscriber are reluctant to take such measure
Protection individual privacy.Although the IOS systems of Fructus Mali pumilae provide the access control of some applications, frequently switching is still abnormal
It is inconvenient and time-consuming.The method of another kind of conventional user's checking is the method by facial recognition, and user can be certainly
Definition needs the application program by the method as access control.However, the accuracy of facial recognition always is very big
Challenge, in particular for mobile device；And frequently taking pictures also can largely affect the normal use of user.
Nearest method is identifying and distinguishing between user with a kind of communication mode based on capacitive touch-control.In this method
In, send by the token (such as possessing the ring of communication function) in user's handss while user's Touch screen that to possess user unique
The signal of communication of identification code, so as to carry out the differentiation of user.The shortcoming of this method must use the auxiliary equipment that can be communicated.
The problem that all remaining said methods are present jointly is to be easy to imitated, such as cheat camera by photo, snatch password, steathily
Listen communication of token and equipment etc..Therefore, urgent need is a kind of is difficult imitated and user authentication method that is stealing, and cuts in user
So that user can't discover during changing identification and access control, so as to reach the effect of secret protection.
The content of the invention
The purpose of the present invention is to overcome the deficiencies in the prior art, there is provided a kind of based on the hidden of various dimensions behavior characteristicss
Formula user's checking and method for secret protection, its low-power consumption are difficult imitated and attack, can enter in the case where user cannot discover
The accurate user identity identification of row, makes corresponding secret protection measure.
According to the technical scheme that the present invention is provided, the implicit user verification and privacy based on various dimensions behavior characteristicss is protected
Maintaining method, the implicit user verification and method for secret protection comprise the steps：
A, the behavior to legal user operation mobile device carry out data acquisition, obtain some lawful acts data；It is described
Mode of operation to mobile device and the corresponding operation of the mode of operation are anti-to be included to the lawful acts data of mobile device
Should；
B, lawful acts characteristic vector is obtained according to the above-mentioned lawful acts data to mobile device, to lawful acts feature
Vector sets up validated user performance characteristic model using support vector machine training；
C, data acquisition is carried out to each operation behavior of mobile device to active user, obtain current behavior data, institute
Stating current behavior data includes the operation reaction of the mode of operation to mobile device and the mode of operation；According to current behavior
Data obtain current behavior characteristic vector, using support vector machine by current behavior characteristic vector and validated user performance characteristic mould
Type is compared, with obtain active user whether the operation as validated user compare conclusion and conclusion is compared in the operation can
Reliability；
D, active user is calculated for legal using credibility algorithm according to above-mentioned current behavior characteristic vector and credibility
The probability of user；When the probability of the validated user is higher than given threshold, then confirm that active user is validated user, otherwise,
Mobile device starts secret protection agreement set in advance.
In step b, lawful acts characteristic vector is expressed as Oi={ Ai,Gifi1,fi2,fi3,fi4,fi5,fi6,Ri, its
In, AiRepresent i-th application of current mobile device, GiRepresent the mode of operation of i-th application, fij(0 ＜ j≤6) table
Show for described i-th using corresponding j-th feature, Ri=1 represents validated user, otherwise, Ri=-1.
After validated user performance characteristic model is obtained, being calculated according to lawful acts data makes after an application is operated
The probability applied with another, sets up validated user Markov model；Current behavior data acquisition is being carried out to active user
Afterwards, calculate active user's Markov model；Active user's Markov model is carried out with validated user Markov model
Relatively, obtain auxiliary and compare conclusion；Mobile device mixing operation compares conclusion and is confirmed after aiding in comparing conclusion credible
Degree；Mobile device is according to current behavior characteristic vector and confirms that credibility is legal using credibility algorithm calculating active user
The probability of user.
In step d, mobile device calculates active user using credibility algorithm and for the method for validated user probability is：
Wherein, XiFor i-th mode of operation, εk(Xk) represent k-th mode of operation credibility.
Also including step e, later observation being carried out using dynamic programming method, the method for the later observation is：
U(Et,Tt)=max (1- (1-Ucur(Ecur,Tcur))×(1-U(Et-Ecur,Tt-Tcur)))
Wherein, U (Et,Tt) represent the effectiveness under the energy and time restriction of t, EcurRepresent the energy at current time
Amount, TcurRepresent current time, UcurRepresent the effectiveness at current time, EtRepresent the energy of t.
In step a, the lawful acts data also include the data characteristicses under kinestate.
Advantages of the present invention：Had based on the method for user behavior feature it is safe, be difficult it is imitated and attack spy
Point；The method can cannot carry out the subscriber authentication of implicit expression in user in the case of discovering, can effectively defend malicious user same
When facilitate the use of validated user；The method is verified using the peration data and motion sensor data of user, with work(
The characteristics of consuming low；The method can identify user identity in very short time, and recognition accuracy is high, and time delay is low；The method is complete
All can support to use on the mobile apparatus so that the range of application of the method does not receive therefrom.
Description of the drawings
Fig. 1 is the workflow diagram of the present invention.
Specific embodiment
With reference to concrete drawings and Examples, the invention will be further described.
Existing password is easy to be stolen or the method for facial recognition is easily imitated, but different user is using movement
The behavioral pattern of equipment, application program such as accustomed to using and clicks on the position of screen, dynamics size, time length, have compared with
Big difference and it is difficult imitated, therefore the behavioral pattern of user can carry out user identity as a kind of stealthy password and test
Card.For current intelligent touch screen equipment, such as mobile phone, during user's touching mobile device screen, it will usually so that
Equipment produces the change of small position and attitude.Due to the most integrated motion sensor of current smart machine, these are small
For the reaction for touching can be reflected from the data of sensor well, and during different user's uses, handss
The reaction of machine generally has different characteristic.Additionally, user during mobile phone, such as walks used in motor process, the fortune of different user
The difference of dynamic model formula similarly can be embodied by motion sensor.
As shown in Figure 1：A kind of implicit user verification and privacy based on user's various dimensions behavior characteristicss proposed by the present invention
Guard method, the user authentication method are difficult imitated and attack, and cannot can carry out in the case of discovering quickly in user
Accurate user identity identification, the implicit user verification and method for secret protection comprise the steps：
A, the behavior to legal user operation mobile device carry out data acquisition, obtain some lawful acts data；It is described
Mode of operation to mobile device and the corresponding operation of the mode of operation are anti-to be included to the lawful acts data of mobile device
Should；
Lawful acts data mainly include that validated user is brought for the mode of operation and the mode of operation of mobile device
Two parts are reacted in the operation of equipment.For current Intelligent mobile equipment, gather user's by the running background in mobile device
Mode of operation, including interactive application, touch coordinate, duration of contact, touch pressure size etc..In addition, for
The every time operation of user, mobile device can make corresponding physical reactions, mobile device running background collection user and
The slight change of caused equipment attitude when device screen is contacted, including vibration of the equipment in locus and rotation are (mainly
It is embodied in the change of acceleration and angular velocity).
B, lawful acts characteristic vector is obtained according to the above-mentioned lawful acts data to mobile device, to lawful acts feature
Vector sets up validated user performance characteristic model using support vector machine training；
As the most of applications in current mobile device can have multiple modes of operation, including：Click on, slide, roll
Deng mobile device is also made a big difference for the reaction of the different operating mode of same application.Therefore, connected applications, behaviour
Make the reaction of mode and equipment to represent the behavior characteristicss of a user, lawful acts characteristic vector is expressed as Oi={ Ai,Gifi1,
fi2,fi3,fi4,fi5,fi6,Ri, wherein, AiRepresent i-th application of current mobile device, GiRepresent i-th application
Mode of operation, fij(0 ＜ j≤6) represent for described i-th using corresponding j-th feature (respectively coordinate, the persistent period,
Pressure size, vibrations are rotated), Ri=1 represents validated user, otherwise, Ri=-1.
Above-mentioned lawful acts data are based primarily upon user in implementation process and use mobile device under static state.But work as
User is for example walked in motor process, can not be from sensor information with the interaction mode of equipment under the state such as running
Reflect.Its main cause is because when user is in motor process, and the movable information that device sensor is obtained can be by
The attitudes vibration information of equipment itself is flooded.Therefore, in the embodiment of the present invention, judge that active user is in by sensor information
Resting state or kinestate, to the user under kinestate, by the number for learning motion sensor using support vector machine
According to feature, the motion feature of the validated user is formed, and motion feature is added into user characteristicses vector, carried out user identity and test
Card.
During validated user is using Intelligent mobile equipment, by the peration data that the user is constantly gathered on backstage
The operation model and following Markov models of data, continuous updating and Improving Equipment owner are used with application.
C, data acquisition is carried out to each operation behavior of mobile device to active user, obtain current behavior data, institute
Stating current behavior data includes the operation reaction of the mode of operation to mobile device and the mode of operation；According to current behavior
Data obtain current behavior characteristic vector, using support vector machine by current behavior characteristic vector and validated user performance characteristic mould
Type is compared, with obtain active user whether the operation as validated user compare conclusion and conclusion is compared in the operation can
Reliability；
D, active user is calculated for legal using credibility algorithm according to above-mentioned current behavior characteristic vector and credibility
The probability of user；When the probability of the validated user is higher than given threshold, then confirm that active user is validated user, otherwise,
Mobile device starts secret protection agreement set in advance.
Further, current Intelligent mobile equipment is averagely installed about more than 40 sections of applications, and the use of each application
Frequency is according to individual habit of user, occupation, sex and huge difference.In addition, user is set intelligent mobile is usually used
For the use of application has the sequence accustomed to using of oneself uniqueness in standby process.Therefore the method is by answering to all in system
With usage frequency carry out statistical computation, and calculate the probability that another application is used after application-specific, so as to build
Found the Markov model of each user.After validated user performance characteristic model is obtained, calculated according to lawful acts data
The probability applied using another after one application of operation, sets up validated user Markov model；Active user is being entered
After row current behavior data acquisition, active user's Markov model is calculated；By active user's Markov model and legal use
Family Markov model is compared, and obtains auxiliary and compares conclusion；Mobile device mixing operation compares conclusion and auxiliary compares
Credibility is confirmed after conclusion；Mobile device is according to current behavior characteristic vector and confirms that credibility utilizes credibility algorithm
Calculate probability of the active user for validated user.
Furthermore it is also possible to using the method for photograph and facial recognition as supplementary meanss, for making for current mobile device
User is taken pictures and is analyzed, and to confirm the identity of user, obtains credibility.
Mobile device calculates active user using credibility algorithm：
Wherein, XiFor i-th mode of operation, θiThe probit from first mode of operation to i-th mode of operation is represented,
εk(Xk) represent k-th mode of operation credibility.
Also including step e, later observation being carried out using dynamic programming method, the method for the later observation is：
U(Et,Tt)=max (1- (1-Ucur(Ecur,Tcur))×(1-U(Et-Ecur,Tt-Tcur)))
Wherein, U (Et,Tt) represent the effectiveness under the energy and time restriction of t, EcurRepresent the energy at current time
Amount, TcurRepresent current time, UcurRepresent the effectiveness at current time, EtThe energy of t is represented, Tt represents t.
Due to by photograph and image recognition method come currently used person is identified institute's consumed energy relative to
Judge that by using person's behavioral pattern identity is big, therefore follow quick in the selection of view mode, the principle of low-power consumption.
For next step is observed on adopted method choice, the invention uses dynamic programming method, in certain energy budget and
In identification reference time delay, result is obtained by most fast observation compound mode.In the embodiment of the present invention, constantly repeat above-mentioned
Identification process, until identifying user identity, realizes the implicit user verification to mobile device, after user's checking, Neng Gouji
Method for secret protection needed for Shi Qidong.
Claims (3)
1. a kind of implicit user verification and method for secret protection based on various dimensions behavior characteristicss, is characterized in that, the implicit expression is used
Family is verified and method for secret protection comprises the steps：
A (), the behavior to legal user operation mobile device carry out data acquisition, obtain some lawful acts data；It is described right
The lawful acts data of mobile device include the mode of operation to mobile device and the corresponding operation reaction of the mode of operation；
(b), obtain lawful acts characteristic vector according to the above-mentioned lawful acts data to mobile device, to lawful acts feature to
Amount sets up validated user performance characteristic model using support vector machine training；
(c), data acquisition is carried out to each operation behavior of mobile device to active user, obtain current behavior data, it is described
Current behavior data include the operation reaction of the mode of operation to mobile device and the mode of operation；According to current behavior number
According to obtaining current behavior characteristic vector, using support vector machine by current behavior characteristic vector and validated user performance characteristic model
It is compared, to obtain active user, conclusion is compared in the operation as validated user and the credible of conclusion is compared in the operation
Degree；
D, (), after validated user performance characteristic model is obtained, being calculated according to lawful acts data makes after an application is operated
The probability applied with another, sets up validated user Markov model；Current behavior data acquisition is being carried out to active user
Afterwards, calculate active user's Markov model；Active user's Markov model is carried out with validated user Markov model
Relatively, obtain auxiliary and compare conclusion；Mobile device mixing operation compares conclusion and is confirmed after aiding in comparing conclusion credible
Degree；Mobile device is according to current behavior characteristic vector and confirms that credibility is legal using credibility algorithm calculating active user
The probability of user；When the probability of the validated user is higher than given threshold, then confirm that active user is validated user, otherwise,
Mobile device starts secret protection agreement set in advance；
In the step (b), lawful acts characteristic vector is expressed as Oi={ Ai,Gifi1,fi2,fi3,fi4,fi5,fi6,Ri, wherein,
AiRepresent i-th application of current mobile device, GiRepresent the mode of operation of i-th application, fij(0 ＜ j≤6) represent right
Corresponding j-th feature, R are applied in described i-thi=1 represents validated user, otherwise, Ri=-1；
In the step (d), mobile device calculates active user using credibility algorithm and for the method for validated user probability is：
Wherein, XiFor i-th mode of operation, εk(Xk) represent k-th mode of operation credibility.
2. the implicit user verification and method for secret protection based on various dimensions behavior characteristicss according to claim 1, which is special
Levying is, also including step (e), carries out later observation using dynamic programming method, and the method for the later observation is：
U(Et,Tt)=max (1- (1-Ucur(Ecur,Tcur))×(1-U(Et-Ecur,Tt-Tcur)))
Wherein, U (Et,Tt) represent the effectiveness under the energy and time restriction of t, EcurRepresent the energy at current time, Tcur
Represent current time, UcurRepresent the effectiveness at current time, EtRepresent the energy of t, TtRepresent t.
3. the implicit user verification and method for secret protection based on various dimensions behavior characteristicss according to claim 1, which is special
Levying is, in the step (a), the lawful acts data also include the data characteristicses under kinestate.
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| CN105843889B (en) * | 2016-03-21 | 2020-08-25 | 华南师范大学 | Credibility-based data acquisition method and system for big data and common data |
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| CN106888204B (en) * | 2016-12-27 | 2022-05-17 | 中国科学院软件研究所 | Implicit identity authentication method based on natural interaction |
| WO2018149497A1 (en) * | 2017-02-16 | 2018-08-23 | Huawei Technologies Co., Ltd. | System and method for authentication of a user |
| CN107122641B (en) * | 2017-04-25 | 2020-06-16 | 杭州义盾信息技术有限公司 | Intelligent equipment owner identification method and intelligent equipment owner identification device based on use habit |
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| CN113632080A (en) * | 2019-04-03 | 2021-11-09 | 思杰系统有限公司 | System and method for protecting remotely hosted applications from malicious attacks |
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Effective date of registration: 20210331 Address after: 215000 5th floor, building 06, 78 Keling Road, science and Technology City, Suzhou high tech Zone, Jiangsu Province Patentee after: Suzhou Meixin Internet Information Technology Co.,Ltd. Address before: No.503, area a, Liye building, Qingyuan Road, science and Technology Park, taikeyuan University, New District, Wuxi City, Jiangsu Province, 214135 Patentee before: WUXI SENSEHUGE TECHNOLOGY Ltd. |