CN103533546A - 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 rs authentication and method for secret protection, especially a kind of implicit user based on various dimensions behavioural characteristic is verified and method for secret protection, belongs to the technical field of secret protection.
Background technology
Along with the development of modern information technologies, people have more and more depended on by various mobile devices, mobile phone for example, and panel computers etc. carry out receiving and dispatching mail, share photos, online transaction, even Smart Home etc.Yet these complicated functions all can be with the hidden danger of serving about safety and privacy leakage.Although these mobile devices are more and more individualized, as long as in the situation that responsive personal information is not revealed, a lot of users are still ready oneself equipment to lend other people, kinsfolk for example, and friend, works together etc.On the other hand, in order not show the distrust for the other side, in most cases user be can be before not giving the other side equipment with password etc. some application and information protection.The fast verification of not discovered when in this case, user is switched and the access control of equipment owner privacy information is become to extremely important.
Traditional method for user rs authentication is passed through password mostly, or sets up the operating specification that specific agreement limits other people.This method is too detailed and loaded down with trivial details, and a lot of users, particularly cellphone subscriber are reluctant to take such measure to protect individual privacy.Although the IOS system of apple provides the access control of some application, switch frequently still abnormal inconvenient and consuming time.The method of another kind of conventional user rs authentication is the method by face recognition, and user can be self-defined need to be by the method the application program as access control.Yet the accuracy of face recognition is a very large challenge, in particular for mobile device always; And take pictures frequently and also can affect to a great extent user's normal use.
Nearest method is to identify and distinguish user with a kind of communication mode based on capacitive touch-control.In this method, the token in the time of user's touch screen in user's hand (ring that for example possesses communication function) sends the signal of communication that possesses user's unique identifier, thereby carries out user's differentiation.The shortcoming of this method must be used the auxiliary equipment that can communicate by letter.The common problem existing of all the other said methods is to be easy to imitatedly, for example, by photo, cheat camera, snatches password, and eavesdrops communicating by letter of token and equipment etc.Therefore, be badly in need of a kind of imitated and user authentication method that steal of being difficult for, and in user is switched the process of identification and access control, user can't be discovered, thereby reach the effect of secret protection.
Summary of the invention
The object of the invention is to overcome the deficiencies in the prior art; a kind of implicit user checking and method for secret protection based on various dimensions behavioural characteristic is provided; its low-power consumption; be difficult for imitated and attack; in the situation that user cannot discover, can carry out user identity identification accurately, make corresponding secret protection measure.
According to technical scheme provided by the invention, described implicit user checking and method for secret protection based on various dimensions behavioural characteristic, described implicit user checking and method for secret protection comprise the steps:
A, the behavior of validated user operation mobile device is carried out to data acquisition, obtain some lawful acts data; The described lawful acts data to mobile device comprise the mode of operation of mobile device and operant response corresponding to described mode of operation;
B, according to the above-mentioned lawful acts data to mobile device, obtain lawful acts characteristic vector, to lawful acts characteristic vector, utilize SVMs training to set up validated user operating characteristics model;
C, active user is carried out to data acquisition to each operation behavior of mobile device, obtain current behavior data, described current behavior data comprise the operant response to the mode of operation of mobile device and described mode of operation; According to current behavior data, obtain current behavior characteristic vector, utilize SVMs that current behavior characteristic vector and validated user operating characteristics model are compared, take and obtain operation conclusion and the described operation confidence level of conclusion relatively relatively whether active user is validated user;
D, according to above-mentioned current behavior characteristic vector and confidence level, utilize confidence level algorithm to calculate the probability that active user is validated user; When the probability of described validated user is during higher than setting threshold, confirm that active user is validated user, otherwise mobile device starts predefined secret protection agreement.
In described step b, lawful acts characteristic vector is expressed as O<sub TranNum="62">i</sub>={ A<sub TranNum="63">i</sub>, G<sub TranNum="64">i</sub>f<sub TranNum="65">i1</sub>, f<sub TranNum="66">i2</sub>, f<sub TranNum="67">i3</sub>, f<sub TranNum="68">i4</sub>, f<sub TranNum="69">i5</sub>, f<sub TranNum="70">i6</sub>, R<sub TranNum="71">i</sub>, wherein, A<sub TranNum="72">i</sub>represent i application of current mobile device, G<sub TranNum="73">i</sub>the mode of operation that represents described i application, f<sub TranNum="74">ij</sub>(0<j≤6) represent for described i j the feature that application is corresponding, R<sub TranNum="75">i</sub>=1 represents validated user, otherwise, R<sub TranNum="76">i</sub>=-1.
After obtaining validated user operating characteristics model, according to lawful acts data, calculate the probability that uses Another application after an application of operation, set up validated user Markov model; Active user is being carried out after current behavior data acquisition, calculating active user's Markov model; Active user's Markov model and validated user Markov model are compared, obtain auxiliary relatively conclusion; After mobile device mixing operation comparison conclusion and auxiliary comparison conclusion, be confirmed confidence level; Mobile device utilizes confidence level algorithm to calculate the probability that active user is validated user according to current behavior characteristic vector and confirmation confidence level.
In described steps d, mobile device utilizes the method that confidence level algorithm calculating active user is validated user probability to be:
Wherein, X
ibe i mode of operation, ε
k(X
k) represent the confidence level of k mode of operation.
Also comprise step e, utilize dynamic programming method to carry out later observation, the method for described later observation is:
U(E
t，T
t)=max(1-(1-U
cur(E
cur，T
cur))×(1-U(E
t-E
cur，T
t-T
cur)))
Wherein, U (E
t, T
t) be illustrated in energy constantly of t and the effectiveness under time restriction, E
curthe energy that represents current time, T
currepresent current time, U
curthe effectiveness that represents current time, E
trepresent t energy constantly.
In described step a, described lawful acts data also comprise the data characteristics under motion state.
Advantage of the present invention: the method based on user behavior feature has safe, is difficult for feature imitated and that attack; The method can be carried out the subscriber authentication of implicit expression in the situation that user cannot discover, and can effectively defend malicious user to facilitate the use of validated user simultaneously; The method utilizes user's operating data and motion sensor data to verify, has feature low in energy consumption; The method can identify user identity in the short time at the utmost point, and recognition accuracy is high, and time delay is low; The method completely can be supported on mobile device and use, and makes the range of application of the method not be subject to platform constraints.
Accompanying drawing explanation
Fig. 1 is workflow diagram of the present invention.
Embodiment
Below in conjunction with concrete drawings and Examples, the invention will be further described.
Existing password be easy to be stolen or the method for face recognition easily imitated, but different user is used the behavior pattern of mobile device, the application program of using as being accustomed to and the position of clicking screen, dynamics size, time length, have larger difference and be difficult to imitatedly, so the password that user's behavior pattern can be used as a kind of stealth carries out subscriber authentication.For current intelligent touch screen equipment, for example mobile phone, touches in the process of mobile device screen user, conventionally can make equipment produce small position and the variation of attitude.Due to the most integrated motion sensor of current smart machine, these small reactions for touching can well reflect from the data of transducer, and in different user's use procedures, the reaction of mobile phone has different characteristic conventionally.In addition,, when user uses mobile phone in motion process, as walked, the difference of the motor pattern of different user can embody by motion sensor too.
As shown in Figure 1: a kind of implicit user checking and method for secret protection based on user's various dimensions behavioural characteristic that the present invention proposes; this user authentication method is difficult for imitated and attacks; and can in the situation that user cannot discover, carry out quick and precisely user identity identification, described implicit user checking and method for secret protection comprise the steps:
A, the behavior of validated user operation mobile device is carried out to data acquisition, obtain some lawful acts data; The described lawful acts data to mobile device comprise the mode of operation of mobile device and operant response corresponding to described mode of operation;
Lawful acts data mainly comprise operant response two parts of the equipment that validated user brings for mode of operation and this mode of operation of mobile device.For current Intelligent mobile equipment, by the running background at mobile device, gather user's mode of operation, comprise interactive application, touch coordinate, duration of contact, touch pressure size etc.In addition, operation for each user, mobile device can be made corresponding physical reactions, when the running background collection user of mobile device contacts with device screen, cause the slight variation of equipment attitude, comprise vibration and the rotation (be mainly reflected in the variation of acceleration and angular speed) of equipment in locus.
B, according to the above-mentioned lawful acts data to mobile device, obtain lawful acts characteristic vector, to lawful acts characteristic vector, utilize SVMs training to set up validated user operating characteristics model;
Because the great majority application in current mobile device can have multiple modes of operation, comprising: click, slide, roll etc., mobile device also makes a big difference for the reaction of the different operating mode of same application.Therefore, represent a user's behavioural characteristic in conjunction with the reaction of application, mode of operation and equipment, lawful acts characteristic vector is expressed as O<sub TranNum="115">i</sub>={ A<sub TranNum="116">i</sub>, G<sub TranNum="117">i</sub>f<sub TranNum="118">i1</sub>, f<sub TranNum="119">i2</sub>, f<sub TranNum="120">i3</sub>, f<sub TranNum="121">i4</sub>, f<sub TranNum="122">i5</sub>, f<sub TranNum="123">i6</sub>, R<sub TranNum="124">i</sub>, wherein, A<sub TranNum="125">i</sub>represent i application of current mobile device, G<sub TranNum="126">i</sub>the mode of operation that represents described i application, f<sub TranNum="127">ij</sub>(0<j≤6) represent for j feature corresponding to described i application (be respectively coordinate, the duration, pressure size, shakes, and rotates), R<sub TranNum="128">i</sub>=1 represents validated user, otherwise, R<sub TranNum="129">i</sub>=-1.
Above-mentioned lawful acts data are mainly under static state used mobile device based on user in implementation process.Yet when user is in motion process, for example walking can not reflect with the interaction mode of equipment under the states such as running from sensor information.Its main cause is because when user is in motion process, the movable information that device sensor obtains can flood the attitude change information of equipment self.Therefore, in the embodiment of the present invention, by sensor information, judge that active user remains static or motion state, to the user under motion state, by adopting the data characteristics of SVMs study motion sensor, form the motion feature of this validated user, and motion feature is added to user characteristics vector, carry out subscriber authentication.
At validated user, use in the process of Intelligent mobile equipment, by constantly gather this user's operating data and application usage data, continuous updating and Improving Equipment owner's operation model and following Markov model on backstage.
C, active user is carried out to data acquisition to each operation behavior of mobile device, obtain current behavior data, described current behavior data comprise the operant response to the mode of operation of mobile device and described mode of operation; According to current behavior data, obtain current behavior characteristic vector, utilize SVMs that current behavior characteristic vector and validated user operating characteristics model are compared, take and obtain operation conclusion and the described operation confidence level of conclusion relatively relatively whether active user is validated user;
D, according to above-mentioned current behavior characteristic vector and confidence level, utilize confidence level algorithm to calculate the probability that active user is validated user; When the probability of described validated user is during higher than setting threshold, confirm that active user is validated user, otherwise mobile device starts predefined secret protection agreement.
Further, current Intelligent mobile equipment is on average installed the approximately application over 40 sections, and the frequency of utilization of each application is according to individual habit of user, occupation, sex and huge difference.In addition, user's use for application in the process of conventionally using Intelligent mobile equipment has own unique custom to use sequence.Therefore the method is by the frequency of utilization of all application in system is carried out to statistical computation, and calculates the probability that uses Another application after application-specific, thereby sets up each user's Markov model.After obtaining validated user operating characteristics model, according to lawful acts data, calculate the probability that uses Another application after an application of operation, set up validated user Markov model; Active user is being carried out after current behavior data acquisition, calculating active user's Markov model; Active user's Markov model and validated user Markov model are compared, obtain auxiliary relatively conclusion; After mobile device mixing operation comparison conclusion and auxiliary comparison conclusion, be confirmed confidence level; Mobile device utilizes confidence level algorithm to calculate the probability that active user is validated user according to current behavior characteristic vector and confirmation confidence level.
In addition, can also adopt take a picture and the method for face recognition as supplementary means, for the user of current mobile device, take pictures and analyze, to confirm user's identity, acquisition confidence level.
Mobile device utilizes confidence level algorithm to calculate the method that active user is validated user probability:
Wherein, X
ibe i mode of operation, θ
ithe probable value of expression from first mode of operation to i mode of operation, ε
k(X
k) represent the confidence level of k mode of operation.
Also comprise step e, utilize dynamic programming method to carry out later observation, the method for described later observation is:
U(E
t，T
t)=max(1-(1-U
cur(E
cur，T
cur))×(1-U(E
t-E
cur，T
t-T
cur)))
Wherein, U (E
t, T
t) be illustrated in energy constantly of t and the effectiveness under time restriction, E
curthe energy that represents current time, T
currepresent current time, U
curthe effectiveness that represents current time, E
trepresent t energy constantly, Tt represents that t constantly.
Owing to current user being identified to institute's consumed energy with respect to judging that by user's behavior pattern identity is large by the method for photograph and image recognition, therefore in the selection of view mode, follow fast the principle of low-power consumption.On the method adopting for next step observation post is selected, dynamic programming method is used in this invention, in certain energy budget and identification reference time delay, by the fastest observation compound mode, obtains result.In the embodiment of the present invention, constantly repeat above-mentioned identifying, until identify user identity, realize the implicit user checking to mobile device, after user rs authentication, can start in time required method for secret protection.
Claims (6)
1. the checking of the implicit user based on various dimensions behavioural characteristic and a method for secret protection, is characterized in that, described implicit user checking and method for secret protection comprise the steps:
(a), the behavior of validated user operation mobile device is carried out to data acquisition, obtain some lawful acts data; The described lawful acts data to mobile device comprise the mode of operation of mobile device and operant response corresponding to described mode of operation;
(b), according to the above-mentioned lawful acts data to mobile device, obtain lawful acts characteristic vector, to lawful acts characteristic vector, utilize SVMs training to set up validated user operating characteristics model;
(c), active user is carried out to data acquisition to each operation behavior of mobile device, obtain current behavior data, described current behavior data comprise the operant response to the mode of operation of mobile device and described mode of operation; According to current behavior data, obtain current behavior characteristic vector, utilize SVMs that current behavior characteristic vector and validated user operating characteristics model are compared, take and obtain operation conclusion and the described operation confidence level of conclusion relatively relatively whether active user is validated user;
(d), according to above-mentioned current behavior characteristic vector and confidence level, utilize confidence level algorithm to calculate the probability that active user is validated user; When the probability of described validated user is during higher than setting threshold, confirm that active user is validated user, otherwise mobile device starts predefined secret protection agreement.
2. implicit user checking and the method for secret protection based on various dimensions behavioural characteristic according to claim 1, is characterized in that: in described step (b), lawful acts characteristic vector is expressed as O<sub TranNum="172">i</sub>={ A<sub TranNum="173">i</sub>, G<sub TranNum="174">i</sub>f<sub TranNum="175">i1</sub>, f<sub TranNum="176">i2</sub>, f<sub TranNum="177">i3</sub>, f<sub TranNum="178">i4</sub>, f<sub TranNum="179">i5</sub>, f<sub TranNum="180">i6</sub>, R<sub TranNum="181">i</sub>, wherein, A<sub TranNum="182">i</sub>represent i application of current mobile device, G<sub TranNum="183">i</sub>the mode of operation that represents described i application, f<sub TranNum="184">ij</sub>(0<j≤6) represent for described i j the feature that application is corresponding, R<sub TranNum="185">i</sub>=1 represents validated user, otherwise, R<sub TranNum="186">i</sub>=-1.
3. the implicit user based on various dimensions behavioural characteristic according to claim 1 is verified and method for secret protection, it is characterized in that: after obtaining validated user operating characteristics model, according to lawful acts data, calculate the probability that uses Another application after an application of operation, set up validated user Markov model; Active user is being carried out after current behavior data acquisition, calculating active user's Markov model; Active user's Markov model and validated user Markov model are compared, obtain auxiliary relatively conclusion; After mobile device mixing operation comparison conclusion and auxiliary comparison conclusion, be confirmed confidence level; Mobile device utilizes confidence level algorithm to calculate the probability that active user is validated user according to current behavior characteristic vector and confirmation confidence level.
4. implicit user checking and the method for secret protection based on various dimensions behavioural characteristic according to claim 1, is characterized in that, in described step (d), mobile device utilizes the method that confidence level algorithm calculating active user is validated user probability to be:
Wherein, X
ibe i mode of operation, ε
k(X
k) represent the confidence level of k mode of operation.
5. implicit user checking and the method for secret protection based on various dimensions behavioural characteristic according to claim 1, is characterized in that, also comprises step (e), utilizes dynamic programming method to carry out later observation, and the method for described later observation is:
U(E
t，T
t)=max(1-(1-U
cur(E
cur，T
cur))×(1-U(E
t-E
cur，T
t-T
cur)))
Wherein, U (E
t, T
t) be illustrated in energy constantly of t and the effectiveness under time restriction, E
curthe energy that represents current time, T
currepresent current time, U
curthe effectiveness that represents current time, E
trepresent t energy constantly.
6. implicit user checking and the method for secret protection based on various dimensions behavioural characteristic according to claim 1, is characterized in that, in described step (a), described lawful acts data also comprise the data characteristics under motion state.
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