CN109508533A - The expansible value of multidimensional matches account password setting method - Google Patents
The expansible value of multidimensional matches account password setting method Download PDFInfo
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- CN109508533A CN109508533A CN201811532799.3A CN201811532799A CN109508533A CN 109508533 A CN109508533 A CN 109508533A CN 201811532799 A CN201811532799 A CN 201811532799A CN 109508533 A CN109508533 A CN 109508533A
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F21/00—Security arrangements for protecting computers, components thereof, programs or data against unauthorised activity
- G06F21/30—Authentication, i.e. establishing the identity or authorisation of security principals
- G06F21/45—Structures or tools for the administration of authentication
- G06F21/46—Structures or tools for the administration of authentication by designing passwords or checking the strength of passwords
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- G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
- G06Q20/00—Payment architectures, schemes or protocols
- G06Q20/38—Payment protocols; Details thereof
- G06Q20/382—Payment protocols; Details thereof insuring higher security of transaction
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Abstract
The present invention is the expansible value matching account password setting method of multidimensional, the present invention considers the divulging a secret property for same amount number input equal length password, the operation factors such as convenience and safety, establish different model of influencing factors (such as personalized model, transaction place environmental model and correlation model), the value of this method is extended from multiple dimension faces, to obtain suitable Password Length according to these models to meet the needs of users.The method that the present invention provides matching account password setting after optimization, the invention belongs to information securities and soft project crossing domain.
Description
Technical field
The invention belongs to information securities and soft project crossing domain.It is mainly influential on Password Length by establishing
Factor influences model, is that account setup is relatively valuable, the higher Password Length of safety.
Background technique
Current payment trend is changed into mobile-phone payment from the payment of card class, network payment, and either market shopping is consumed
Still it has a meal consumption, is all to input account by modes such as handset Wechat, Alipays more easily no more than no change of taking transit bus
Family password is paid.Mobile-phone payment is very convenient, but even if monitoring universal place, close with uniform length
The place that code payment still has its deficiency and has much room for improvement.
It consumes in different places, safety is necessarily different.It may transfer accounts and give opposite credit worthiness higher place,
You can be less to the worry of account security.And the determination of the credit worthiness in place need to consider from many aspects (such as: Ren Yuanjiao
Easy frequency, industrial chain scale, headcount, brand degree etc.).
Payment for the different amount of money will input the password of equal length, if only buying a candy, this phase
As soon as inputting six passwords seems that effect value less convenient and to be achieved is not directly proportional compared with a television set is bought.
Summary of the invention
Technical problem: the invention discloses a kind of expansible values of multidimensional to match account password setting method, mainly solves
Password Length used in user-pay consistent problem be easy to cause the safety issues such as password leakage and also uses with user
Convenience is related.
Technical solution: in order to solve the problems, such as above-mentioned background technique, the invention proposes a kind of multidimensional is expansible
Value matching account password setting method.Personal personalized model is initially set up, according to the occupation of user, hobby, residence
Sphere of consumption and consumption place delimited in residence location etc., and give the expression of its degree；Next establishes transaction place environmental model, according to
Influence factor (such as personnel's trading frequency, industrial chain scale, headcount, brand degree) determines its credit worthiness parameter；Then it builds
Vertical correlation model, including two: first is that demographic associations model, second is that behavior correlation model, so that it is determined that incidence coefficient；So
Consumption place the level of detail is determined afterwards；Then cipher random is obtained；Finally based on amount and the model elaborates that are previously obtained
Parameter value, to obtain determining the setting method of Password Length.The present invention not only can be further improved the safety of mobile-phone payment
Performance can also meet convenience and high efficiency that user pays the Password Length that the different amount of money are inputted.
Architecture
The expansible value matching account password setting method detailed process of multidimensional is as follows:
(1) sphere of consumption and place delimited according to the occupation of user, hobby, inhabitation address etc., establishes personal personalization
Model, gives each place and degree coefficient occurs and be expressed as L:
(wherein Pr, In, Ho respectively indicate the degree of association of occupation and the degree of association of the goods for consumption, hobby and the article with
And the distance degree of inhabitation address and the consumption place, andIndicate weight shared by each factor, i.e. weight
Parameter)
(2) transaction place environment mould is established according to influence factors such as employee's total amount of transaction place, industrial chain number, trading frequencies
Type obtains identity coefficients R:
(wherein Es, Ts, Ds respectively indicate employee's total amount, industrial chain number and trading frequency, andIndicate it is each because
Weight shared by element, i.e. weight parameter)
Note: the transaction place environmental model is due to considering that situation is difficult to accomplish to consider totally, and data have imperfection, accurately
It spends relatively high.
(3) correlation model is established, mainly includes following two part:
1) population model (introducing social networks) is established
According to " Small World Model ", it can know that arriving at the average length of the complete interpersonal chain of target person is six in the result
People.Herein we only analyze two secondary associations, user understanding people and user understanding people understanding people, they respectively association journey
Spending coefficient is α, β
2) behavior model is established
(depth can be carried out to these historical records according to the reasonability for consuming other articles after one article of customer consumption again
Study), obtain reasonable coefficient Y.
(4) consumption place the level of detail T is determined
(5) cipher random Pwdr=(Pwdpbl, PwdThird) is obtained, includes two algorithms, specific as follows:
1) PwdThird(Person) → (de, Pbl): third party login protocol function PwdThird is related in user social contact relationship
Member Person, obtain degree de of the Person in social networks, find Person cost calculation formula on de degree such as
Under:
(wherein Perde represents the time cost of unit de search,Represent generation average time of all searching routes
Valence summation；After Person agreement, the interface Link and specific protocol action Pbl of third party login are determined；It represents
The average protocol action deadline cost of Pbl；
2) Pwdpbl(Pbl, p) → y │ n: protocol verification function Pwdpbl is right after PwdThird function determines Link and Pbl
Pbl of the Person in corresponding Link is verified, if the Person more than p probability has carried out Pbl movement, protocol verification at
Function y, otherwise unsuccessfully n；Only when output is y, the setting of PwdLength could be continued；
(6) parameter value based on amount S with the model elaborates being previously obtained, to obtain determining Password Length PwdLength's
Setting method.
(whereinThe place for respectively indicating the people of people's understanding of user, the people of user's understanding and user's understanding occurs
Degree coefficient, λ, μ, ε, γ are weight coefficient, and ML is the maximum length of password)
Beneficial effect
(1) different Password Lengths is had according to different consumption and spending amount, for small amount, user-pay is more convenient,
For wholesale, user-pay is safer.
(2) by establishing influence of the different model analysis to Password Length, be conducive to the satisfaction for improving user and close
The safety of code.
Detailed description of the invention
Fig. 1 is the implementation flow chart of the expansible value matching account password setting method of multidimensional
Fig. 2 is the relationship model figure of the expansible value matching account password setting method of multidimensional
Fig. 3 is the expansible value matching account password setting method consumption place the level of detail schematic diagram of multidimensional
Specific embodiment
In order to illustrate the object, technical solutions and advantages of the present invention, below in conjunction with specific example and attached drawing, the present invention is done
It is further described (total model structure is as shown in Figure 2):
(1) correspond to the 001 of Fig. 1 operation, sphere of consumption and field delimited according to the occupation of user, hobby, inhabitation address etc.
Institute establishes personal personalized model, gives each place and degree coefficient occurs and is expressed as L:
(wherein Pr, In, Ho respectively indicate the degree of association of occupation and the degree of association of the goods for consumption, hobby and the article with
And the distance degree of inhabitation address and the consumption place, andIndicate weight shared by each factor, i.e. weight
Parameter)
(2) correspond to the 002 of Fig. 1 operation, according to influence factors such as employee's total amount of transaction place, industrial chain number, trading frequencies
Transaction place environmental model is established, identity coefficients R is obtained:
(wherein Es, Ts, Ds respectively indicate employee's total amount, industrial chain number and trading frequency, andIndicate it is each because
Weight shared by element, i.e. weight parameter)
Note: the transaction place environmental model is due to considering that situation is difficult to accomplish to consider totally, and data have imperfection, accurately
It spends relatively high.
(3) correspond to the 003 of Fig. 1 operation, establish correlation model, mainly include following two part:
1) population model (introducing social networks) is established
According to " Small World Model ", it can know that arriving at the average length of the complete interpersonal chain of target person is six in the result
People.Herein we only analyze two secondary associations, user understanding people and user understanding people understanding people, they respectively association journey
Spending coefficient is α, β
2) behavior model is established
(depth can be carried out to these historical records according to the reasonability for consuming other articles after one article of customer consumption again
Study), obtain reasonable coefficient Y.
(4) according to Fig. 3, consumption Locale information is more detailed, and safe coefficient is higher, determines consumption place the level of detail T
(5) correspond to the 004 of Fig. 1 operation, obtain cipher random Pwdr=(Pwdpbl, PwdThird), include two algorithms,
It is specific as follows:
1) PwdThird(Person) → (de, Pbl): third party login protocol function PwdThird is related in user social contact relationship
Member Person, obtain degree de of the Person in social networks, find Person cost calculation formula on de degree such as
Under:
(wherein Perde represents the time cost of unit de search,Represent generation average time of all searching routes
Valence summation；After Person agreement, the interface Link and specific protocol action Pbl of third party login are determined；It represents
The average protocol action deadline cost of Pbl；
2) Pwdpbl(Pbl, p) → y │ n: protocol verification function Pwdpbl is right after PwdThird function determines Link and Pbl
Pbl of the Person in corresponding Link is verified, if the Person more than p probability has carried out Pbl movement, protocol verification at
Function y, otherwise unsuccessfully n；Only when output is y, the setting of PwdLength could be continued；
(6) correspond to the 005 of Fig. 1 operation, the parameter value based on amount S with the model elaborates being previously obtained, to be determined
The setting method of Password Length PwdLength.
(whereinThe place for respectively indicating the people of people's understanding of user, the people of user's understanding and user's understanding occurs
Degree coefficient, λ, μ, ε, γ are weight coefficient, and ML is the maximum length of password).
Claims (1)
1. the present invention is the expansible value matching account password setting method of multidimensional, the present invention considers to input for same amount number
Divulging a secret property, the operation factors such as convenience and safety of equal length password, establish different model of influencing factors (such as individual characteies
Change model, transaction place environmental model and correlation model etc.), the value of this method is extended from multiple dimension faces, thus according to this
A little models obtain suitable Password Length to meet the needs of users;The expansible value matching account password setting method tool of multidimensional
Body process is as follows:
(1) sphere of consumption and place delimited according to the occupation of user, hobby, inhabitation address etc., establishes personal personalization
Model, gives each place and degree coefficient occurs and be expressed as L:
(wherein Pr, In, Ho respectively indicate the degree of association of occupation and the degree of association of the goods for consumption, hobby and the article with
And the distance degree of inhabitation address and the consumption place, andIndicate weight shared by each factor, i.e. weight
Parameter)
(2) transaction place environment mould is established according to influence factors such as employee's total amount of transaction place, industrial chain number, trading frequencies
Type obtains identity coefficients R:
(wherein Es, Ts, Ds respectively indicate employee's total amount, industrial chain number and trading frequency, andIndicate each factor
Shared weight, i.e. weight parameter)
Note: the transaction place environmental model is due to considering that situation is difficult to accomplish to consider totally, and data have imperfection, accurately
It spends relatively high；
(3) correlation model is established, mainly includes following two part:
1) population model (introducing social networks) is established
According to " Small World Model ", it can know that arriving at the average length of the complete interpersonal chain of target person is six in the result
People；
Herein we only analyze two secondary associations, user understanding people and user understanding people understanding people, they respectively association
Degree coefficient is α, β
2) behavior model is established
(depth can be carried out to these historical records according to the reasonability for consuming other articles after one article of customer consumption again
Study), obtain reasonable coefficient Y；
(4) consumption Locale information is more detailed, and safe coefficient is higher, determines consumption place the level of detail T
(5) cipher random Pwdr=(Pwdpbl, PwdThird) is obtained, includes two algorithms, specific as follows:
1) PwdThird(Person) → (de, Pbl): third party login protocol function PwdThird is related in user social contact relationship
Member Person, obtain degree de of the Person in social networks, find Person cost calculation formula on de degree such as
Under:
(wherein Perde represents the time cost of unit de search,Represent generation average time of all searching routes
Valence summation；After Person agreement, the interface Link and specific protocol action Pbl of third party login are determined；It represents
The average protocol action deadline cost of Pbl；
2) Pwdpbl(Pbl, p) → y │ n: protocol verification function Pwdpbl is right after PwdThird function determines Link and Pbl
Pbl of the Person in corresponding Link is verified, if the Person more than p probability has carried out Pbl movement, protocol verification at
Function y, otherwise unsuccessfully n；Only when output is y, the setting of PwdLength could be continued；
(6) parameter value based on amount S with the model elaborates being previously obtained, to obtain determining Password Length PwdLength's
Setting method；
(whereinThe place for respectively indicating the people of people's understanding of user, the people of user's understanding and user's understanding occurs
Degree coefficient, λ, μ, ε, γ are weight coefficient, and ML is the maximum length of password).
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| CN201811532799.3A CN109508533A (en) | 2018-12-14 | 2018-12-14 | The expansible value of multidimensional matches account password setting method |
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| CN201811532799.3A CN109508533A (en) | 2018-12-14 | 2018-12-14 | The expansible value of multidimensional matches account password setting method |
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Cited By (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN111754239A (en) * | 2020-06-30 | 2020-10-09 | 海南大学 | Payment password evaluation method and component integrating data, information and knowledge |
Citations (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN104978144A (en) * | 2015-06-26 | 2015-10-14 | 中国工商银行股份有限公司 | Gesture password input device and system and method for transaction based on system |
| US20160241400A1 (en) * | 2015-02-13 | 2016-08-18 | Thomas Wolf | Encryption and authentication method and apparatus |
| CN106815148A (en) * | 2016-12-30 | 2017-06-09 | 中国银联股份有限公司 | A kind of transaction test method and device |
-
2018
- 2018-12-14 CN CN201811532799.3A patent/CN109508533A/en active Pending
Patent Citations (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US20160241400A1 (en) * | 2015-02-13 | 2016-08-18 | Thomas Wolf | Encryption and authentication method and apparatus |
| CN104978144A (en) * | 2015-06-26 | 2015-10-14 | 中国工商银行股份有限公司 | Gesture password input device and system and method for transaction based on system |
| CN106815148A (en) * | 2016-12-30 | 2017-06-09 | 中国银联股份有限公司 | A kind of transaction test method and device |
Cited By (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN111754239A (en) * | 2020-06-30 | 2020-10-09 | 海南大学 | Payment password evaluation method and component integrating data, information and knowledge |
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