CN103473492A - Method and user terminal for recognizing permission - Google Patents

Abstract

The invention provides a method and a user terminal for recognizing permission. The method includes that the user terminal acquires signature information of a user, and the signature information comprises fingerprint data and\or signature data; the user terminal determines the permission of the user according to the signature information; the user terminal determines available business according to the permission of the user and displays the available business for the user. The method and the user terminal for recognizing the permission have the advantage that the problem of poor safety of a method for recognizing permission in the prior art can be solved.

Description

Authority recognition method and user terminal

Technical field

The present invention relates to the information processing technology, relate in particular to a kind of authority recognition method and user terminal.

Background technology

Along with the development of electronics, infotech, the problem of the security of electronic equipment and information becomes the major issue of this area.

For user terminal, smart mobile phone for example, the method such as traditional authority recognition adopts password usually, swipe, for example the user input correct password or by correct track, swipe after can use the various functions of this user terminal.

But the method for this authority recognition easily is cracked, security is not high.

Summary of the invention

The invention provides a kind of authority recognition method and user terminal, to overcome the low problem of authority recognition method security of prior art.

First aspect, the invention provides a kind of authority recognition method, comprising:

User terminal gathers user's signing messages, described signing messages comprise finger print data and or signed data;

User terminal is determined described user's authority according to described signing messages;

User terminal is determined available business according to described user's authority, and shows described available business for described user.

Second aspect, the invention provides a kind of user terminal, comprising:

Acquisition module, for gathering user's signing messages, described signing messages comprise finger print data and or signed data;

The authority determination module, for determining described user's authority according to described signing messages;

The service display module, determine available business for the authority according to described user, and show described available business for described user.

The third aspect, the invention provides a kind of user terminal, comprising: storer, for storing instruction;

Processor, with described storer coupling, described processor is configured to carry out and is stored in the instruction in described storer, and described processor is configured to the described authority recognition method of any one for carrying out first aspect.

Authority recognition method of the present invention and user terminal, by the signing messages that gathers the user, the authority of determining the user according to described signing messages, and determine available business according to user's authority, and show described available business for described user, the identification of realization to user right, thereby the security of miscellaneous service on the protection user terminal; Because the finger print data in signing messages or signed data have uniqueness and stability, and signed data has not easy imitation, guaranteed that the identification of authority recognition method of the present invention is accurate, thereby can improve security.

The accompanying drawing explanation

The process flow diagram that Fig. 1 is authority recognition embodiment of the method one of the present invention;

The process flow diagram that Fig. 2 is authority recognition embodiment of the method two of the present invention;

The process flow diagram that Fig. 3 is authority recognition embodiment of the method three of the present invention;

The structural representation that Fig. 4 is user terminal embodiment one of the present invention;

The structural representation that Fig. 5 is user terminal embodiment two of the present invention;

The structural representation that Fig. 6 is user terminal embodiment of the present invention.

Embodiment

The described user terminal of various embodiments of the present invention can be the equipment such as smart mobile phone (Smart Phone), notebook computer, panel computer, portable equipment (Portable Equipment).

The process flow diagram that Fig. 1 is authority recognition embodiment of the method one of the present invention, as shown in Figure 1, the method for the present embodiment can comprise:

Step 101, user terminal gather user's signing messages, described signing messages comprise finger print data and or signed data.

Particularly, signed data can comprise the architectural feature of each word in signature and the behavioral characteristics of signature.

Step 102, user terminal are determined described user's authority according to described signing messages.

Particularly, signing messages in the sample of the signing messages that collects in step 101 and pre-save can be mated, to determine user's authority.

Matching process can be contrasted for the finger print data of the finger print data in the signing messages by collecting and sample, the architectural feature of the architectural feature in the signing messages collected and sample is contrasted, the behavioral characteristics of the behavioral characteristics in the signing messages collected and sample is contrasted particularly, can be set to, in these three kinds of comparing results, the similarity of any one meets the requirements, and can determine that the user has the authority that this sample is corresponding; Also can be set to the similarity of each in these three kinds of comparing results and meet the requirements, just determine that the user has the authority that this sample is corresponding.During specific implementation, can determine according to the demand of product design, the present invention is not construed as limiting this.

Further, in one implementation, step 102 can be: the sample fingerprint that described finger print data is corresponding with each Permission Levels is mated, when the similarity of the described finger print data sample fingerprint corresponding with any one Permission Levels is greater than the first preset value, the authority of determining described user is the Permission Levels that described sample fingerprint is corresponding.

And subscriber equipment can also detect this user's age bracket according to the finger print data collected, then recommends available business according to age bracket for the user, to improve the convenience of user's operation.

When specific implementation, user terminal can only arrange an authority, for example this user terminal is only for a user, at this moment can only preserve a sample, perhaps, can, for this user preserves one group of sample, while being mated, when the information of the signing messages collected and any one sample is complementary, think that this user has rights of using.

User terminal also can arrange a plurality of authorities, the available service that each authority is corresponding different.The smart mobile phone of below take describes as example, and available service corresponding to the number of its authority and each authority can carry out personalized setting by the user.For example a certain smart mobile phone has three authorities: highest weight limit, secondary authority, three grades of authorities, and the owner of this smart mobile phone can have the highest weight limit, and repertoire or the business of this smart mobile phone are available service; Available service corresponding to secondary authority be such as for calling, send note, game function etc., but can't use the functions such as message registration inquiry, document query; Three grades of functions corresponding to authority are for example the part learning software of consulting time and appointment.Under such scene, preferred, each authority can a corresponding sample, and when carrying out authority recognition, the signing messages gathered in step 101 is during with any one sample matches, and definite this user has the authority that this sample is corresponding.

Step 103, user terminal are determined available business according to described user's authority, and show described available business for described user.

The present embodiment, signing messages by gathering the user, the authority that the signing messages that collects and the signing messages in sample are mated to determine the user, and determine available business according to user's authority, and show described available business for described user, the identification of realization to user right, thereby the security of miscellaneous service on the protection user terminal; Because the finger print data in signing messages or signed data have uniqueness and stability, and signed data has not easy imitation, guaranteed that the identification of authority recognition method of the present invention is accurate, thereby can improve security.

Below adopt several specific embodiments, the technical scheme of embodiment of the method shown in Fig. 1 is elaborated.

The process flow diagram that Fig. 2 is authority recognition embodiment of the method two of the present invention, the present embodiment is on basis embodiment illustrated in fig. 1, the method of the signed data according in signing messages being carried out to authority recognition describes in detail, and as shown in Figure 2, the method for the present embodiment can comprise:

Step 201, user terminal gather user's signing messages, and described signing messages comprises signed data.

Particularly, signed data comprises architectural feature and behavioral characteristics.

It should be noted that, the method that the architectural feature that in the present embodiment, introduction comprises according to signed data and behavioral characteristics carry out authority recognition, and can be combined with the method for the present embodiment introduction according to the method that the finger print data in signing messages carries out authority recognition, these two kinds of methods also can be distinguished use separately, and the embodiment of the present invention is not construed as limiting this.

Step 202, identify the architectural feature in described signed data, described architectural feature comprises font and the blur level of each word in described signed data.

Further particularly, the font of each word in described signed data and various standard letter can be compared, select the standard letter the most similar to the word in described signed data, the font of the word using described standard letter in described signed data, standard letter is such as comprising the Song typeface, regular script, rapid style of writing etc.

After having determined font, then calculate each word in described signed data and the blur level between described standard letter.

Further, the word in the described signed data of described calculating and the method for the blur level between described standard letter can comprise the following steps:

Step 1, using the central point of the word in described signed data as true origin, obtain the coordinate of M reference point in the track of the word in described signed data, M is greater than 1 integer;

Step 2, obtain a described M reference point with respect to M blurred length L and the blur direction θ put corresponding in the writing of described standard letter;

Step 3, the average blur length of calculating a described M reference point and average blur direction, as the blur level between the word in described signed data and described standard letter.

Wherein, step 1 can, according to the order of handwriting signature, be obtained M discrete point in described signed data successively; In step 2, can be first according to the order of handwriting signature, obtain successively M discrete point corresponding in the writing of described standard letter, more respectively M discrete point in the compute signature data with respect to blurred length and the blur direction of the discrete point of correspondence in the writing of described standard letter.For example, in described signed data, i(i is the integer between 1～M) individual some P _icoordinate be (x _i, y _i), i some P in the writing of described standard letter _i' coordinate be (x _i', y _i'), i the point blurred length L _ifor P _iwith P _i' distance, that is:

$L_i=\sqrt{{(X_i^{\′}-X_i)}^2+{(Y_i^{\′}-Y_i)}^2};$

The blur direction θ of i point _ifor:

${\mathrm{\θ}}_i=\mathrm{arctg}\left(\frac{Y_i^{\′}-Y_i}{X_i^{\′}-X_i}\right)$

While carrying out the judgement of similarity of architectural feature in follow-up step, the error between the average blur direction of word accordingly in the average blur direction that can distinguish error between the average blur length of corresponding word in the average blur length of the word in the compute signature data and sample, the word in signed data and sample.For convenience, in subsequent step, average blur length and average blur direction are called to blur level, for example, the error of blur level is less than the 3rd preset value, in the average blur direction that refers to error between the average blur length of corresponding word in the average blur length of the word in signed data and sample and the word in signed data and sample accordingly the error between the average blur direction of word all be less than the 3rd preset value.

Wherein, the Computing Principle of blur level is as follows:

If being original image, f (x, y) makes x ₀and y (t) ₀(t) mean that respectively object component motion t in the x and y direction means that the time T of motion is that the image g (x, y) of time shutter after fuzzy is

$g(x,y)={\∫}_0^{T}f[x-x_0\left(t\right),y-y_0\left(t\right)]\mathrm{dt}---\left(1.1\right)$

From the physical phenomenon motion blur image be exactly in fact same scene image after a series of range delay the more final image formed of stack formula (1.1) is carried out to Fourier transform can obtain

$G(u,v)={\&Integral;}_{-\&infin;}^{\&infin;}{\&Integral;}_{-\&infin;}^{\&infin;}g(x,y)e^{-\mathrm{<figure-callout\; id="2"\; label="j"\; filenames="HDA0000377678030000031.png"\; state="\{\{state\}\}">j</figure-callout>}2\mathrm{\&pi;}(\mathrm{ux}+\mathrm{vy})}\mathrm{dxdy}$

$={\&Integral;}_{-\&infin;}^{\&infin;}{\&Integral;}_{-\&infin;}^{\&infin;}\left[{\&Integral;}_0^{T}f\right[x-x_0\left(t\right),y-y_0\left(t\right)\left]\mathrm{dt}\right]e^{-\mathrm{<figure-callout\; id="2"\; label="j"\; filenames="HDA0000377678030000031.png"\; state="\{\{state\}\}">j</figure-callout>}2\mathrm{\&pi;}(\mathrm{ux}+\mathrm{vy})}\mathrm{dxdy}---\left(1.2\right)$

Transform integrals order formula (1.2) can be write as

$G(u,v)={\&Integral;}_0^T\left[{\&Integral;}_{-\&infin;}^{\&infin;}{\&Integral;}_{-\&infin;}^{\&infin;}f\right[x-x_0\left(t\right),y-y_0\left(t\right)\left]e^{-\mathrm{<figure-callout\; id="2"\; label="j"\; filenames="HDA0000377678030000031.png"\; state="\{\{state\}\}">j</figure-callout>}2\mathrm{\&pi;}(\mathrm{ux}+\mathrm{vy})}\mathrm{dxdy}\right]\mathrm{dt}$

$={\&Integral;}_0^{T}F(u,v)e^{-\mathrm{<figure-callout\; id="2"\; label="j"\; filenames="HDA0000377678030000031.png"\; state="\{\{state\}\}">j</figure-callout>}2\mathrm{\&pi;}[{\mathrm{ux}}_0\left(t\right)+{\mathrm{vy}}_0\left(t\right)]}\mathrm{dt}$

$=F(u,v){\&Integral;}_0^T{e}^{-\mathrm{<figure-callout\; id="2"\; label="j"\; filenames="HDA0000377678030000031.png"\; state="\{\{state\}\}">j</figure-callout>}2\mathrm{\&pi;}[{\mathrm{ux}}_0\left(t\right)+{\mathrm{vy}}_0\left(t\right)]}\mathrm{dt}---\left(1.3\right)$

Definition H(u is v):

$H(u,v)={\&Integral;}_0^T{e}^{-\mathrm{<figure-callout\; id="2"\; label="j"\; filenames="HDA0000377678030000031.png"\; state="\{\{state\}\}">j</figure-callout>}2\mathrm{\&pi;}[{\mathrm{ux}}_0\left(t\right)+{\mathrm{vy}}_0\left(t\right)]}\mathrm{dt}---\left(1.4\right)$

, formula (1.3) can be expressed as:

G(u,v)=H(u,v)*F(u,v) （1.5）

The Fourier transform that wherein G (u, v) is blurred picture g (x, y), the Fourier transform H (u, v) that F (u, v) is original image f (x, y) is the Fourier transform of point spread function h (x, y),

The angle that the transport function hypothesis moving object blurred length in time shutter T that is motion blur is L motion blur direction and x direction is θ

The blurred length that image produces on the x direction is a=Lcos θ, and the blurred length produced on the y direction is b=Lsin θ, and formula 1.1 can be expressed as

$g(x,y)={\&Integral;}_0^{T}f(x-\frac{\mathrm{at}}{T},y-\frac{\mathrm{bt}}{T})\mathrm{dt}---\left(1.6\right)$

Its frequency-domain expression of mathematics degradation model that formula (1.6) is Image Blurred by Motion at Arbitrary Direction is

G(u,v)=H(u,v)*F(u,v) （1.7）

Wherein transfer function H (u, v) is:

$H=(u,v)=\frac{T}{\mathrm{\&pi;}(\mathrm{ua}+\mathrm{vb})}\sin \left[\mathrm{\&pi;}(\mathrm{ua}+\mathrm{vb})\right]e^{-\mathrm{j\&pi;}(\mathrm{ua}+\mathrm{ub})}---\left(1.8\right)$

If can access motion blur direction and blurred length L by above analysis is known, the transport function that just can obtain motion blur according to formula (1.8) is carried out the inverse-Fourier transform original image f (x, y) that just can appear again according to formula (1.7).

If can appear again, original image proves this image recognition success, and the similarity that is equivalent to blur level is greater than the second preset value, can think that the judgement to architectural feature meets the authority that described sample is corresponding in authority recognition.

Step 203, identify the behavioral characteristics in described signed data, described behavioral characteristics comprise each word in described signed data averaging time and or average velocity.

Particularly, identifying the method for the averaging time of each word in described signed data specifically can be as follows:

According to the order of handwriting signature, obtain successively starting to write constantly and a receipts moment in described signed data, then obtain described mistiming of receiving the pen moment and the moment of starting to write, the averaging time using the described mistiming as described signed data.

The method of identifying the average velocity of each word in described signed data is specifically as follows:

According to the order of handwriting signature, obtain successively N discrete point in described signed data, N is more than or equal to 2;

Obtain respectively the speed of the correspondence of every pair of adjacent discrete point, as discrete speed, the number of described discrete speed is N-1;

Obtain the mean value V of N-1 described discrete speed, the average velocity using described mean value V as described signed data.

It should be noted that there is no ordinal relation between above-mentioned step 202 and step 203, when specific implementation, can first perform step 203 and perform step again 202.And, in step 203, identify between averaging time of each word in described signed data and average velocity and there is no strict sequence requirement, usually can carry out simultaneously, also can identify separately the averaging time of each word or identify separately the average velocity of each word.The embodiment of the present invention is not construed as limiting this.

During specific implementation, in step 203, except averaging time and the average velocity of identifying each word, can also identify averaging time and the average velocity of once signed, for example signature comprises three words, identify first character in signed data start to write constantly and triliteral receipts pen constantly, using the triliteral receipts the averaging time of the mistiming in the pen moment and the moment of starting to write of first character as this signature; The method of the computing method of the average velocity of once signed and the average velocity of each word can be similar, be for example: the average velocity that calculates successively each word in this signature, for comprising triliteral signature, can obtain three average velocitys, again these three average velocitys are averaging, have obtained the average velocity of this signature.

Correspondingly, the signing messages of the sample that each Permission Levels are corresponding also can comprise above all parameters, as the architectural feature of sample can comprise font, the blur level of each word in sample; The behavioral characteristics of sample can comprise averaging time and the average velocity of each word in sample, the averaging time of whole sample and average velocity.

Step 204, described architectural feature and described behavioral characteristics are mated with architectural feature and the behavioral characteristics of sample corresponding to each Permission Levels respectively, when described architectural feature and described behavioral characteristics are greater than the second preset value with the similarity of the architectural feature of sample corresponding to any one Permission Levels and behavioral characteristics respectively, the authority of determining described user is the Permission Levels that described sample is corresponding.

Particularly, error in the blur level that can calculate word in described signed data and standard letter and sample between the blur level of corresponding word and standard letter, when the error of described blur level is less than the 3rd preset value, the architectural feature of determining the word in described signed data is greater than the second preset value with the similarity of the architectural feature of word corresponding in sample;

Calculate the error of averaging time and the sample time of described signed data, with or, the error of the average velocity of described signed data and sample speed, error when the described time is less than the 4th preset value, with or, when the error of described speed is less than the 5th preset value, determine that the similarity of the behavioral characteristics of the behavioral characteristics of described signed data and sample is greater than the second preset value;

The authority of determining described user is the Permission Levels that described sample is corresponding.

Wherein, error can adopt the form of number percent, for example the error of the averaging time of signed data and sample time can be: the absolute value of the difference of the averaging time of signed data and the averaging time of sample, with the number percent of averaging time of sample, the 4th preset value can be for example 10%.

The 3rd preset value, the 4th preset value and the 5th preset value can be identical, also can be different, that is to say, the matching condition of parameters can be the same or different, when certain parameter meets matching condition, the similarity of determining this parameter is greater than the second preset value, and the coupling of this parameter meets the requirements.

Correspondingly, in the deterministic process of the similarity of said structure feature and behavioral characteristics, if the similarity of any one feature is less than the second preset value, can determine that described user does not have the authority that described sample is corresponding; Perhaps, when comparatively loose for the requirement of signed data coupling, also can be set to, when the similarity of any one feature is greater than the second preset value, determine that described user's authority is the Permission Levels that described sample is corresponding.

When specific implementation, judgement to the architectural feature of the word in signed data with the similarity of the architectural feature of word corresponding in sample, with the judgement of the similarity of the behavioral characteristics of behavioral characteristics to signed data and sample, can carry out separately, can also only judge the similarity of architectural feature, or only judge the similarity of behavioral characteristics.These two deterministic processes do not have strict sequencing yet.

And in an embodiment therein, can first judge the similarity of the architectural feature of the architectural feature of the first character in signed data and the first word in sample, if the similarity of the sample that the architectural feature of this first character is corresponding with any one authority all is less than the second preset value, can determine that described user is without any rights of using, and, can also determine accordingly that this signature is for illegal operation, the all functions of user terminal are closed, comprise and forbid that this user writes the next word in signature.Certainly, in other embodiment, also can first judge the similarity of the behavioral characteristics of the behavioral characteristics of the first character in signed data and the first word in sample, the embodiment of the present invention is not construed as limiting this.

If this user terminal comprises more than one Permission Levels,, before execution step 204, can first determine a sample that Permission Levels are corresponding.Particularly, an immediate sample in the sample that can select to preserve according to architectural feature or the behavioral characteristics of first character in signed data, in ensuing deterministic process, architectural feature and the behavioral characteristics of the sample of the architectural feature of described signed data and behavioral characteristics and this selection are compared.

The present embodiment, by the architectural feature in the signing messages that gathers the user and or behavioral characteristics, the authority of being mated to determine the user with architectural feature and the behavioral characteristics of sample, and determine available business according to user's authority, and show described available business for described user, the identification of realization to user right, thereby the security of miscellaneous service on the protection user terminal; Because architectural feature and the behavioral characteristics of signed data has not easy imitation, guaranteed that the identification of authority recognition method of the present invention is accurate, thereby can improve security.

Further, please refer to Fig. 3, the process flow diagram that Fig. 3 is authority recognition embodiment of the method three of the present invention, the present embodiment, on basis embodiment illustrated in fig. 2, provides a kind of concrete grammar that judges the similarity of signed data.For convenience of description, suppose that the user terminal of the present embodiment comprises Permission Levels, the corresponding signature sample of these Permission Levels.Only introduce in the present embodiment the similarity determination methods of first character in signed data, when specific implementation, after the similarity of first character meets the requirements, can carry out successively again the method for the similarity of the next word of judgement, if the similarity of all words all meets the requirements, determine that this user has the authority of this user terminal.As shown in Figure 3, the method for the present embodiment can comprise:

Architectural feature and the behavioral characteristics of first character in step 301, collection signed data.

Particularly, comprise the font of determining first character in described signed data.Alternatively, can also in this step, determine the blur level that in described signed data, the first character standard letter corresponding with determined font compared simultaneously.In the main flow of the present embodiment, determine that the process of the blur level of first character is carried out in follow-up step 303.

Behavioral characteristics comprises averaging time and the average velocity of first character in the present embodiment.

Step 302, judge that whether the font of first character in described signed data is identical with the font of first character in sample, if, perform step 303, if not, perform step 304.

Step 303, determine first character in described signed data and the blur level of standard letter, and calculate the error between the blur level of first character and standard letter in the blur level of first character in described signed data and standard letter and sample.

Step 304, the architectural feature of determining the word in described signed data are not mated with the architectural feature of word corresponding in sample.

Further, can determine that this user does not have any authority of user terminal, therefore, closes all functions of user terminal.

Step 305, when described error is less than the 3rd preset value, determine that the architectural feature of first character in the architectural feature of the first character in described signed data and sample is complementary.

Step 306, when the error of described blur level is more than or equal to the 3rd preset value, determine that the architectural feature of first character in the architectural feature of the first character in described signed data and sample is not mated.

Further, can determine that this user does not have any authority of user terminal, therefore, closes all functions of user terminal.

Error in step 307, the averaging time of calculating the first character in described signed data and sample between the averaging time of first character, and calculate the error between the average velocity of first character in the average velocity of the first character in described signed data and sample.

Step 308, the error when described averaging time are less than the 4th preset value, and the error of described average velocity is while being less than the 5th preset value, determine that the behavioral characteristics of first character in the behavioral characteristics of the first character in described signed data and sample is complementary.

During execution of step 308, can determine that the architectural feature of described signed data and behavioral characteristics all are complementary with sample, therefore, can proceed the similarity judgement of next word, the process of judgement and the method for the present embodiment are similar, repeat no more herein.

Step 309, the error when described averaging time are more than or equal to the 4th preset value, perhaps, when the error of described average velocity is more than or equal to the 5th preset value, determine that the behavioral characteristics of first character in the behavioral characteristics of the first character in described signed data and sample does not mate.

Further, can determine that this user does not have any authority of user terminal, therefore, closes all functions of user terminal.

Can find out, the present embodiment is comparatively strict authority recognition method, because architectural feature and the behavioral characteristics of signed data has not easy imitation, has guaranteed that the identification of authority recognition method of the present invention is accurate, thereby can improve security.

The structural representation that Fig. 4 is user terminal embodiment one of the present invention, as shown in Figure 4, the user terminal 400 of the present embodiment can comprise: acquisition module 1, authority determination module 2 and service display module 3, wherein,

Acquisition module 1, can be for gathering user's signing messages, described signing messages comprise finger print data and or signed data;

Authority determination module 2, can be for determining described user's authority according to described signing messages;

Service display module 3, can determine available business for the authority according to described user, and show described available business for described user.

Further, described authority determination module 2 specifically can for:

The sample fingerprint that described finger print data is corresponding with each Permission Levels is mated, when the similarity of the described finger print data sample fingerprint corresponding with any one Permission Levels is greater than the first preset value, the authority of determining described user is the Permission Levels that described sample fingerprint is corresponding.

The user terminal of the present embodiment, can be for the technical scheme of embodiment of the method shown in execution graph 1, and it realizes that principle is similar, repeats no more herein.

The user terminal of the present embodiment, signing messages by gathering the user, the authority that the signing messages that collects and the signing messages in sample are mated to determine the user, and determine available business according to user's authority, and show described available business for described user, the identification of realization to user right, thereby the security of miscellaneous service on the protection user terminal; Because the finger print data in signing messages or signed data have uniqueness and stability, and signed data has not easy imitation, guaranteed that the identification of authority recognition method of the present invention is accurate, thereby can improve security.

The structural representation that Fig. 5 is user terminal embodiment two of the present invention, as shown in Figure 5, the user terminal 500 of the present embodiment is on basis embodiment illustrated in fig. 4, and further, described authority determination module 2 can comprise:

Architectural feature identification module 21, can be for identifying the architectural feature of described signed data, and described architectural feature comprises font and the blur level of each word in described signed data;

Behavioral characteristics identification module 22, can be for identifying the behavioral characteristics of described signed data, and described behavioral characteristics comprises averaging time and the average velocity of each word in described signed data;

Matching module 23, can be for described architectural feature and described behavioral characteristics be mated with architectural feature and the behavioral characteristics of sample corresponding to each Permission Levels respectively, when described architectural feature and described behavioral characteristics are greater than the second preset value with the similarity of the architectural feature of sample corresponding to any one Permission Levels and behavioral characteristics respectively, the authority of determining described user is the Permission Levels that described sample is corresponding.

Further, described architectural feature identification module 21 specifically can for:

The font of each word in described signed data and various standard letter are compared, select the standard letter the most similar to the word in described signed data, the font of the word using described standard letter in described signed data;

Calculate each word in described signed data and the blur level between described standard letter.

Further, described architectural feature identification module 21 specifically can for:

Using the central point of the word in described signed data as true origin, obtain the coordinate of M reference point in the track of the word in described signed data, M is greater than 1 integer;

Obtain blurred length L and the blur direction θ of a described M reference point with respect to M point corresponding in the writing of described standard letter;

Calculate average blur length and the average blur direction of a described M reference point, as the blur level between the word in described signed data and described standard letter.

Further, described behavioral characteristics identification module 22 specifically can for:

According to the order of handwriting signature, obtain successively N discrete point in described signed data, N is more than or equal to 2;

Obtain respectively the speed of the correspondence of every pair of adjacent discrete point, as discrete speed, the number of described discrete speed is N-1;

Obtain the mean value V of N-1 described discrete speed, the average velocity using described mean value V as described signed data.

Further, described behavioral characteristics identification module 22 specifically can for:

According to the order of handwriting signature, obtain successively starting to write constantly and receiving pen constantly in described signed data;

Obtain the described mistiming of receiving the pen moment and the moment of starting to write, the averaging time using the described mistiming as described signed data.

Further, described matching module 23 specifically can for:

Error in the blur level of calculating word in described signed data and standard letter and sample between the blur level of corresponding word and standard letter, when the error of described blur level is less than the 3rd preset value, the architectural feature of determining the word in described signed data is greater than the second preset value with the similarity of the architectural feature of word corresponding in sample;

Calculate the error of averaging time and the sample time of described signed data, with or, the error of the average velocity of described signed data and sample speed, error when the described time is less than the 4th preset value, with or, when the error of described speed is less than the 5th preset value, determine that the similarity of the behavioral characteristics of the behavioral characteristics of described signed data and sample is greater than the second preset value;

The authority of determining described user is the Permission Levels that described sample is corresponding.

The user terminal of the present embodiment, can be for the technical scheme of embodiment of the method shown in execution graph 2 or Fig. 3, its realize principle and technique effect similar, repeat no more herein.

The structural representation that Fig. 6 is user terminal embodiment of the present invention, the user terminal of the present embodiment can be smart mobile phone, panel computer etc., as shown in Figure 6, the user terminal 600 of the present embodiment can comprise: storer 601 and processor 602, wherein,

Storer 601, for storing instruction;

Processor 602, with described storer coupling, described processor is configured to carry out and is stored in the instruction in described storer, and described processor is configured to the described authority recognition method for the either method embodiment shown in execution graph 1～4.

One of ordinary skill in the art will appreciate that: realize that the hardware that all or part of step of above-mentioned each embodiment of the method can be relevant by programmed instruction completes.Aforesaid program can be stored in a computer read/write memory medium.This program, when carrying out, is carried out the step that comprises above-mentioned each embodiment of the method; And aforesaid storage medium comprises: various media that can be program code stored such as ROM, RAM, magnetic disc or CDs.

Finally it should be noted that: above each embodiment, only in order to technical scheme of the present invention to be described, is not intended to limit; Although with reference to aforementioned each embodiment, the present invention is had been described in detail, those of ordinary skill in the art is to be understood that: its technical scheme that still can put down in writing aforementioned each embodiment is modified, or some or all of technical characterictic wherein is equal to replacement; And these modifications or replacement do not make the essence of appropriate technical solution break away from the scope of various embodiments of the present invention technical scheme.

Claims (17)

1. an authority recognition method, is characterized in that, comprising:

User terminal gathers user's signing messages, described signing messages comprise finger print data and or signed data;

Described user terminal is determined described user's authority according to described signing messages;

Described user terminal is determined available business according to described user's authority, and shows described available business for described user.

2. method according to claim 1, is characterized in that, described user terminal is determined described user's authority according to described signing messages, comprising:

The sample fingerprint that described finger print data is corresponding with each Permission Levels is mated, when the similarity of the described finger print data sample fingerprint corresponding with any one Permission Levels is greater than the first preset value, the authority of determining described user is the Permission Levels that described sample fingerprint is corresponding.

3. method according to claim 1, is characterized in that, described user terminal is determined described user's authority according to described signing messages, comprising:

Identify the architectural feature in described signed data, described architectural feature comprises font and the blur level of each word in described signed data;

Identify the behavioral characteristics in described signed data, described behavioral characteristics comprise each word in described signed data averaging time and or average velocity;

Described architectural feature and described behavioral characteristics are mated with architectural feature and the behavioral characteristics of sample corresponding to each Permission Levels respectively, when described architectural feature and described behavioral characteristics are greater than the second preset value with the similarity of the architectural feature of sample corresponding to any one Permission Levels and behavioral characteristics respectively, the authority of determining described user is the Permission Levels that described sample is corresponding.

4. method according to claim 3, is characterized in that, the architectural feature in the described signed data of described identification comprises:

The font of each word in described signed data and various standard letter are compared, select the standard letter the most similar to the word in described signed data, the font of the word using described standard letter in described signed data;

Calculate each word in described signed data and the blur level between described standard letter.

5. method according to claim 4, is characterized in that, the word in the described signed data of described calculating and the blur level between described standard letter comprise:

Using the central point of the word in described signed data as true origin, obtain the coordinate of M reference point in the track of the word in described signed data, M is greater than 1 integer;

Obtain blurred length L and the blur direction θ of a described M reference point with respect to M point corresponding in the writing of described standard letter;

Calculate average blur length and the average blur direction of a described M reference point, as the blur level between the word in described signed data and described standard letter.

6. method according to claim 3, is characterized in that, the behavioral characteristics in the described signed data of described identification comprises:

According to the order of handwriting signature, obtain successively N discrete point in described signed data, N is more than or equal to 2;

Obtain respectively the speed of the correspondence of every pair of adjacent discrete point, as discrete speed, the number of described discrete speed is N-1;

Obtain the mean value V of N-1 described discrete speed, the average velocity using described mean value V as described signed data.

7. method according to claim 3, is characterized in that, the behavioral characteristics in the described signed data of described identification comprises:

According to the order of handwriting signature, obtain successively starting to write constantly and receiving pen constantly in described signed data;

Obtain the described mistiming of receiving the pen moment and the moment of starting to write, the averaging time using the described mistiming as described signed data.

8. according to the described method of any one in claim 3～7, it is characterized in that, described described architectural feature and described behavioral characteristics are mated with architectural feature and the behavioral characteristics of sample corresponding to each Permission Levels respectively, when described architectural feature and described behavioral characteristics are greater than the second preset value with the similarity of the architectural feature of sample corresponding to any one Permission Levels and behavioral characteristics respectively, the authority of determining described user is the Permission Levels that described sample is corresponding, comprising:

Error in the blur level of calculating word in described signed data and standard letter and sample between the blur level of corresponding word and standard letter, when the error of described blur level is less than the 3rd preset value, the architectural feature of determining the word in described signed data is greater than the second preset value with the similarity of the architectural feature of word corresponding in sample;

Calculate the error of averaging time and the sample time of described signed data, with or, the error of the average velocity of described signed data and sample speed, error when the described time is less than the 4th preset value, with or, when the error of described speed is less than the 5th preset value, determine that the similarity of the behavioral characteristics of the behavioral characteristics of described signed data and sample is greater than the second preset value;

The authority of determining described user is the Permission Levels that described sample is corresponding.

9. a user terminal, is characterized in that, comprising:

Acquisition module, for gathering user's signing messages, described signing messages comprise finger print data and or signed data;

The authority determination module, for determining described user's authority according to described signing messages;

The service display module, determine available business for the authority according to described user, and show described available business for described user.

10. user terminal according to claim 9, is characterized in that, described authority determination module specifically for:

The sample fingerprint that described finger print data is corresponding with each Permission Levels is mated, when the similarity of the described finger print data sample fingerprint corresponding with any one Permission Levels is greater than the first preset value, the authority of determining described user is the Permission Levels that described sample fingerprint is corresponding.

11. user terminal according to claim 9, is characterized in that, described authority determination module comprises:

The architectural feature identification module, for identifying the architectural feature of described signed data, described architectural feature comprises font and the blur level of each word in described signed data;

The behavioral characteristics identification module, for identifying the behavioral characteristics of described signed data, described behavioral characteristics comprises averaging time and the average velocity of each word in described signed data;

Matching module, for described architectural feature and described behavioral characteristics are mated with architectural feature and the behavioral characteristics of sample corresponding to each Permission Levels respectively, when described architectural feature and described behavioral characteristics are greater than the second preset value with the similarity of the architectural feature of sample corresponding to any one Permission Levels and behavioral characteristics respectively, the authority of determining described user is the Permission Levels that described sample is corresponding.

12. user terminal according to claim 11, is characterized in that, described architectural feature identification module specifically for:

The font of each word in described signed data and various standard letter are compared, select the standard letter the most similar to the word in described signed data, the font of the word using described standard letter in described signed data;

Calculate each word in described signed data and the blur level between described standard letter.

13. user terminal according to claim 12, is characterized in that, described architectural feature identification module specifically for:

Using the central point of the word in described signed data as true origin, obtain the coordinate of M reference point in the track of the word in described signed data, M is greater than 1 integer;

Obtain blurred length L and the blur direction θ of a described M reference point with respect to M point corresponding in the writing of described standard letter;

Calculate average blur length and the average blur direction of a described M reference point, as the blur level between the word in described signed data and described standard letter.

14. user terminal according to claim 11, is characterized in that, described behavioral characteristics identification module specifically for:

According to the order of handwriting signature, obtain successively N discrete point in described signed data, N is more than or equal to 2;

Obtain respectively the speed of the correspondence of every pair of adjacent discrete point, as discrete speed, the number of described discrete speed is N-1;

Obtain the mean value V of N-1 described discrete speed, the average velocity using described mean value V as described signed data.

15. user terminal according to claim 11, is characterized in that, described behavioral characteristics identification module specifically for:

According to the order of handwriting signature, obtain successively starting to write constantly and receiving pen constantly in described signed data;

Obtain the described mistiming of receiving the pen moment and the moment of starting to write, the averaging time using the described mistiming as described signed data.

16. according to the described user terminal of any one in claim 11～15, it is characterized in that, described matching module specifically for:

Error in the blur level of calculating word in described signed data and standard letter and sample between the blur level of corresponding word and standard letter, when the error of described blur level is less than the 3rd preset value, the architectural feature of determining the word in described signed data is greater than the second preset value with the similarity of the architectural feature of word corresponding in sample;

Calculate the error of averaging time and the sample time of described signed data, with or, the error of the average velocity of described signed data and sample speed, error when the described time is less than the 4th preset value, with or, when the error of described speed is less than the 5th preset value, determine that the similarity of the behavioral characteristics of the behavioral characteristics of described signed data and sample is greater than the second preset value;

The authority of determining described user is the Permission Levels that described sample is corresponding.

17. a user terminal, is characterized in that, comprising: storer, for storing instruction;

Processor, with described storer coupling, described processor is configured to carry out and is stored in the instruction in described storer, and described processor is configured to for carrying out authority recognition method as described as claim 1～8 any one.

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