CN106408401A - Trust negotiation fuzzy control method - Google Patents
Trust negotiation fuzzy control method Download PDFInfo
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Abstract
The invention relates to a trust negotiation fuzzy control method. For the problem that, since existing trust negotiation fails to consider fuzziness, success rate and efficiency of negotiation are influenced, the method is characterized by, to begin with, analyzing fuzzy demands in the trust negotiation process, giving a fuzzy framework of fuzzy trust negotiation, establishing a fuzzy calculating process, and establishing a process model and method of fuzzy negotiation, thereby enabling the trust negotiation in the actual network environment to be established accurately. Compared with the prior art, the method has the advantages of realizing model establishing and analysis for fuzzy negotiation in the trust negotiation, and carrying out accurate calculating guidance on the negotiation process in the actual network environment of negotiation; the method is low in complexity and convenient to operate; and the method can guide negotiation and provide suggestions for negotiation.
Description
Technical field
The present invention relates to a kind of trust negotiation fuzzy control method.
Background technology
Traditional automated trust negotiation is suitable to the Trust Establishment of two strange inter-entity, but inevitably involves in reality
To multi-party situation about participating in, now traditional negotiation only limiting the two is inadequate, and the trust negotiation that many persons participate in is a weight
Will but the problem that less focuses on of current research.Although researcher has done certain work in terms of many persons trust negotiation, such as：Have
A little methods attempt to the mode of logic to set up trust negotiation model, but do not provide many persons to consult to set up the correlation trusted
Theoretical foundation and further investigation.The trust negotiation that an other method proposes that many persons are participated in is analyzed modeling, but this is more
It is in order at theoretic research more, be difficult application and realize.There is a method in which implement angle from algorithm to propose to use petri web form
Description negotiations process and many persons consult, but flexibly cannot be changed and extension according to demands such as applied environments.
In traditional automated trust negotiation, or the requirement for Attribute certificate meets, or being unsatisfactory for, and in association
In business's policy development, the importance of certificate is as broad as long, and this is likely to cause some unnecessary negotiation failures.Actual
In situation, the satisfaction for attribute is not only 0 or 1 it is likely that between meeting and between being unsatisfactory for, and satisfaction degree is different
, need to be treated differently.In addition, the consulting tactical formulated also can enter Mobile state adjustment according to the degree that attribute meets.
Content of the invention
The purpose of the present invention is：On the one hand improve the success rate consulted, be on the other hand more beneficial for the protection of sensitive information.
In order to achieve the above object, the technical scheme is that and provide a kind of trust negotiation fuzzy control method, its
It is characterised by, consulting to carry out between Fang Yiyu negotiation side two, each negotiation side has fuzzy credentials storehouse and fuzzy trust rule
Then storehouse, fuzzy credentials storehouse is used for storing all fuzzy credentials of current negotiation side, and each fuzzy credentials is expressed as c. λ,
Wherein, c represents Attribute certificate, and λ represents Attribute certificate degree of membership, and fuzzy trust rule base is used for storing being used for of current negotiation side
Protect all fuzzy trust rule of each fuzzy credentials, obscure and trust regular pcIt is expressed as pc：s←f(c1, c2...). τ, its
In, s represents resource or fuzzy credentials, c1, c2... represent the fuzzy credentials requiring other side to provide, f represents to c1,
c2... logical operation, τ represents the degree of membership threshold value meeting fuzzy trust rule requirement, and each negotiation side corresponds to a mould
Paste agency, then the method comprising the steps of：
Step 1, negotiation side one are intended to access the certificate resource held negotiation side two, therefore initiate resource request to negotiation side two；
After step 2, negotiation side two receive request, by certificate resource and the fuzzy each fuzzy trust trusting storage in rule base
Rule matches, and is obscured trust rule accordingly, thus obtaining this fuzzy degree of membership threshold value τ trusting rule, if τ=
0 then it represents that negotiation side two is non-sensitive to the protection of certificate resource, directly returns certificate resource to negotiation side one；If τ=1,
Then represent trust rule be non-fuzzy it is desirable to certificate resource strictly meets, entrance non-fuzzy negotiation phase, carry out credentials and drape over one's shoulders
Dew, trusts rule until meeting non-fuzzy, consults successfully, otherwise to fail；If 0 ＜ τ ＜ 1, enter the fuzzy association that step 3 starts
Business's stage；
Step 3, negotiation side two form a fuzzy trust rule and disclose set PB={ PB1, PB2 ... }, and PB1, PB2 ... are
The fuzzy trust rule of storage in the fuzzy trust rule base of negotiation side two, the certificate resource sent according to the side of negotiationing one, elder generation by
The fuzzy agency of negotiation side two obtains Attribute certificate degree of membership λ of certificate resource, if λ >=τ, current negotiation failure, otherwise, root
According to the result of calculation of the Attribute certificate degree of membership of the certificate resource of negotiation side one request, consult Fang Ercong fuzzy trust rule and disclose
The matching fuzzy trust rule of Attribute certificate degree of membership selecting its corresponding fuzzy credentials in set PB is sent to
Negotiation side one；
Step 4, negotiation side one, according to the fuzzy trust rule receiving auto-negotiation side two, drape over one's shoulders from the fuzzy trust rule of oneself
Matching the obscuring of Attribute certificate degree of membership of its corresponding fuzzy credentials is chosen in dew set PA={ PA1, PA2 ... }
Trust rule and be sent to negotiation side two；
Step 5, negotiation Fang Ercong obscure and select the fuzzy credentials that can disclose to form fuzzy set CB=in credentials storehouse
{ CB1, CB2 ... }, CB1, CB2 ... represent fuzzy credentials, and negotiation side two is from fuzzy set CB according to Attribute certificate degree of membership
Size selects to disclose to the fuzzy credentials of negotiation side one successively；
Step 6, negotiation side two calculate current disclosing to negotiation according to the fuzzy trust rule receiving auto-negotiation side one
The satisfaction of the fuzzy credentials of side one, if reaching threshold value, meets condition, present Fuzzy credentials is fed back to negotiation side
One, from fuzzy set CB, otherwise reselect one can disclose to the fuzzy credentials of negotiation side one, repeated execution of steps 6；
Step 7, negotiation Fang Yicong obscure and select the fuzzy credentials that can disclose to form fuzzy set CA=in credentials storehouse
{ CA1, CA2 ... }, CA1, CA2 ... represent fuzzy credentials, and negotiation side one is from fuzzy set CA according to Attribute certificate degree of membership
Size selects to disclose to the fuzzy credentials of negotiation side two successively；
Step 8, negotiation side one calculate current disclosing to negotiation according to the fuzzy trust rule receiving auto-negotiation side two
The satisfaction of the fuzzy credentials of side two, if reaching threshold value, meets condition, present Fuzzy credentials is fed back to negotiation side
Two, from fuzzy set CA, otherwise reselect one can disclose to the fuzzy credentials of negotiation side two, repeated execution of steps 8；
Step 9, circulation above-mentioned steps 3 are to step 8, until it reaches consult termination condition.
Do not account for ambiguity for existing trust negotiation, the problem of this success rate that have impact on negotiation and efficiency, this
Invention analyzes the Fuzzy Demand of trust negotiation process first, gives the fuzzy frame of fuzzy trust negotiation, establishes fuzzy
The process calculating, establishes the process model of Fuzzy Bargaining and method so that the trust negotiation in real network environment can obtain
To accurately setting up.
Compared with prior art, it is an advantage of the current invention that：
1 present invention achieves setting up for the model of Fuzzy Bargaining in consulting to trust and analyzing；
2nd, the present invention makees accurately to calculate to negotiations process in the practical situation consulted and instructs；
3rd, complexity of the present invention is low, is easy to operate；
4th, the present invention can instruct the carrying out of negotiation, advises to consulting to provide.
Brief description
Fig. 1 is fuzzy trust negotiation process；
Fig. 2 is the fuzzy trust negotiation process being calculated based on degree of membership.
Specific embodiment
With reference to specific embodiment, the present invention is expanded on further.It should be understood that these embodiments are merely to illustrate the present invention
Rather than restriction the scope of the present invention.In addition, it is to be understood that after having read the content of present invention instruction, people in the art
Member can make various changes or modifications to the present invention, and these equivalent form of values equally fall within the application appended claims and limited
Scope.
In order to illustrate so that those skilled in the art better understood when the present invention, first universal to human society below
The Fuzzy Demand of blooming and trust negotiation process is explained.
The universal blooming of human society
In the long period, accurate mathematical and random mathematics, in the characteristics of motion of the description multiple things of nature, obtain
Remarkable result.But, in objective world, also generally existing substantial amounts of blooming.People avoided it in the past, but, due to
Modern science and technology faced by system increasingly complicated, ambiguity invariably accompany complexity occur.Each door subject, especially humane,
The mathematicization of social studieies and other " soft science ", quantification tend to the Mathematical treatment problem of ambiguity to push Central Position to.
Importantly, with electronic computer, cybernetics, the developing rapidly of systematic science, it is right as human brain to enable a computer to
Complexity has identification ability, is necessary for studying and processes ambiguity.
We study the behavior of human system, or process complication system that can be comparable with human system's behavior, such as navigate
Its system, people's brain system, social system etc., parameter and variable are a lot of, and various factors is interlaced, system very complex, its mould
Paste property is also apparent from.From the perspective of in terms of understanding, ambiguity refers to the uncertainty of concept extension, thus causing judge not know
Property.
In daily life, it is frequently encountered by many fuzzy things, do not have clearly demarcated quantitative limits, be fuzzy using some
Words and phrases are describing, to describe.Such as, relatively younger, tall person, big fatty, good, beautiful, kind, hot, remote ....These concepts are can not
Simply to be represented with, non-or numeral.In the working experience of people, often also there are many fuzzy things.For example,
Determine whether one heat steel water has refined, except it is to be understood that the precise information such as the temperature of molten steel, component ratio and duration of heat
Outer in addition it is also necessary to reference to fuzzy messages such as molten steel color, boiling situations.Therefore, except relating to the computational mathematics of error very early
Outside in addition it is also necessary to fuzzy mathematics, and fuzzy processing method.
For example, the examination of visual acuity problem in daily life, take is exactly fuzzy processing method.Examination of visual acuity be not by
Order according to visual acuity chart exclude successively it was therefore concluded that, but the inspection of saltatory, tied according to the inspection that person under inspection is given every time
The difference of fruit, respectively specify that table of testing eyesight which.If i.e. person under inspection's inspection result several times be all to, toward high
Range of vision detects, conversely, then toward low visual acuity range detection, this method tested eyesight does not have absolute path, but
Take fuzzy strategy, the method can be very good to improve the efficiency of detection, and also ensures that certain accuracy rate.
The Fuzzy Demand of trust negotiation process
In traditional trust negotiation, or the requirement for Attribute certificate meets, or being unsatisfactory for, and in policy development
In, the importance of certificate is as broad as long, and this is likely to cause some unnecessary negotiation failures.And in the case of reality,
Satisfaction for attribute is not only 0 or 1 it is likely that between meeting and between being unsatisfactory for, and satisfaction degree is different.Example
As, in terms of success rate, efficiency, the secret protection from the point of view of, the Fuzzy Demand of trust negotiation process is embodied in the following aspects：
(1) success rate demand.In negotiation, the satisfaction of attribute is not only generally 0 or 1 it is likely that between being satisfied with not
Between satisfaction, and satisfaction degree is different, needs to be treated differently.For example：In negotiation, certain is trusted rule and requires to take in ＞ 10000
Unit, just enjoys the service of discounting.If this two situations are all unsatisfactory for trusting rule when then if other side possesses income=9999 and income=0
Requirement then, but in practice, both of these case be should give and treated with a certain discrimination：If it is considered that ambiguity, the genus of income=9999
Property should possess meet this trust rule requirement, can enjoy discounting service.Accordingly, it is considered to Fuzzy Demand, can properly increase
Consult success rate；
(2) efficiency requirements.Negotiation side, when formulating the trust rule of oneself, is not very either-or requirement attribute
Necessarily whether meet, but be likely to list multiple attributes and meet condition, see the satisfaction degree of other side to decide whether to disclose letter
Breath.For example：What certain website wished to enjoy its discounting meets following condition：Young, earn a large income, enjoy a good reputation, educational background
High.With regard to these conditions, if the extra high words of some satisfaction, even if being unsatisfactory for other conditions it is also possible to reach
Consult successfully；Then this Fuzzy Demand embodies the possibility improving negotiation efficiency；
(3) secret protection demand.In a practical situation, the importance of the Attribute certificate in trust rule is typically different
, need to weight, to show difference, thus the certificate strong to sensitivity is preferably protected by.For example：In a financial institution
Require in the trust rule that website is formulated：The people of 10000 yuan of ＞ of income or academic ＞ undergraduate course could enjoy VIP service.Here is believed
Appoint in rule, take in the significance level of this attribute and degree of privacy is obviously higher than educational background.Therefore, to the Attribute certificate amount of carrying out
Change, treat with a certain discrimination and contribute to secret protection.
The fuzzy trust negotiation of the present invention is built upon in the fuzzy foundation of mathematics, is therefore first given fuzzy in fuzzy mathematics
Set and the related definition of degree of membership：
Define 1 fuzzy set and degree of membership：A given domain U, then of [0,1] is reflected from U to unit interval
Penetrate μA→ [0,1] is referred to as a fuzzy set on U, or a fuzzy subset of U, is designated as A.Mapping (function) μA() is called fuzzy
The membership function of collection A.For each x ∈ U, μAX () is called the degree of membership to fuzzy set A for the element x.
In actual applications, the method for determining the membership function of fuzzy set show diversified, mainly according to problem
Practical significance determining.For example, if setting domain X to represent machinery equipment, ambiguity in definition collection A=" Plant in good condition " on X, then
" equipment availability " can be used as the degree of membership of A.If X represents product, ambiguity in definition collection A=" steady quality " on X, then
" percentage of A-class goods " degree of membership as A of product can be used.
In order to consider the Fuzzy Demand in trust negotiation, consequently facilitating in the analysis of trust negotiation process and consideration in control
Fog property, we are theoretical by traditional fuzzy, on the basis of general property certificate and general trust rule definition, increase
Fog property certificate, the fuzzy definition trusting rule, as follows：
Define 2 Fog property certificates：It is a kind of Attribute certificate, also there is sign certificate sensitivity and important journey simultaneously
The degree of membership of degree, is designated as c. λ, wherein c is Attribute certificate, and λ represents Attribute certificate degree of membership, and it characterizes the weight of this Attribute certificate
Want degree, sensitivity.
Define 3 fuzzy trust rules：It is a kind of trust rule, also having this trust rule of sign disclosure should reach simultaneously
The value of the degree of membership arriving, represents such as pc：s←f(c1, c2...). the form of τ, wherein s ← f (c1, c2...) and it is to trust rule,
Prefix s can be resource or certificate, c in suffixiRepresent the certificate requiring other side to provide, f represents to certificate ciCarry out ∧, ∨,
Deng the function of logical operation, and its value takes true or false；τ represents the degree of membership threshold value meeting trust rule requirement.
For example：Assume a fuzzy trust rule ps：s←f(c1, c2...). τ=c1∨(c2∧c3). τ, there are two kinds of feelings
Condition certificate that referred to as side of negotiation discloses can meet and trust rule：A kind of is exactly set of certificates C that negotiation side disclosesxContain ps
The internal set of certificates requiring of rule；Also a kind of situation is, the certificate collection C that negotiation side disclosesxThe attribute of the certificate being comprised
The value that degree of membership passes through to calculate is more than or equal to trusts regular degree of membership threshold value τ, also can claim set of certificates CxMeet tactful ps.
In general, in fuzzy theory, determine that the method for membership function mainly has subjective experience method, analysis ratiocination
Method, investigation statisticses method etc..To be revised and perfect by continuous practice, thus reaching subjective and objective unification.In order in letter
Appoint in negotiations process and carry out fuzzy analysis and control, need to limit research range according to research environment, the present invention makees to degree of membership
Following hypotheses：
(1) for the λ of the significance level characterizing Fog property certificate c, i.e. the value of Attribute certificate degree of membership, is by third party
Assessing mechanism just specified value when certificate is formulated；
(2) trust regular p for characterizing to obscurecDegree of membership threshold value τ whether being satisfied, be by during Rulemaking by
Formulation side's specified value；
(3) the certificate collection C that negotiation side is disclosedx, judge whether it meets the regular p of trusts：s←f(c1, c2...). τ
Requirement, the result that will be calculated by fuzzy membership is determining.
As figure1It show the general process of a kind of fuzzy trust negotiation of present invention offer, in Fuzzy Bargaining, in negotiation
Each participant have an agency, for managing negotiations process, it is all local that fuzzy credentials storehouse preserves that user has
Fuzzy credentials, fuzzy trust rule base deposits fuzzy trust rule, for protecting the fuzzy letter locally obscuring in credentials storehouse
Appoint card.Fuzzy proxy module is responsible for assessing the significance level of multiple Attribute certificates trusted and be related in rule, thus deciding whether
Carry out Sensitive Attributes disclosure.In negotiations process, when having multiple fuzzy trust rules to can be used for consulting simultaneously, obscure and act on behalf of mould
Block can provide suggestion, that is, which selects trust rule and can improve negotiation efficiency to greatest extent, take into account sensitive information simultaneously
Protection.
As shown in Figure 1：Negotiation side A and negotiation side B has respective Fog property certificate respectively and protects these certificates
Fuzzy trust rule, the Fuzzy Bargaining process between them is as follows：(1) negotiation side A is intended to access the certificate resource that negotiation side B holds
S, therefore initiate to consult；(2) due to the sensitivity of certificate resource s, negotiation side B does not directly disclose certificate resource s to other side, but first
Disclose the fuzzy trust rule that some protect its fuzzy credentials to negotiations side A, after the side of negotiationing A satisfaction, disclose sensitive obscuring again
Credentials；Negotiation side A also will not directly disclose the fuzzy credentials that it is held, and equally can disclose the fuzzy credentials of protection oneself
The fuzzy fuzzy credentials trusted rule, disclose sensitivity after the side of negotiation B meets again；(3) negotiation side A and negotiation side B is according to institute
The fuzzy trust rule given, the fuzzy agency of inquiry, carry out fuzziness calculating；(4) decided whether according to the result that fuzziness calculates
Accept request；(5) negotiation side A and the side of negotiationing B meet situation according to other side's disclosure message, gradually disclose the certificate each held
And rule；Obscure the continuous disclosure trusting regular and fuzzy credentials with both sides, constantly circulate negotiation step, control fuzzy
Negotiations process is until consult to reach termination condition；(6) final, consult successfully, negotiation side B discloses certificate resource s, otherwise consult to lose
Lose.
In above process, present invention employs the fuzzy trust negotiation process calculating based on degree of membership.
On the basis of foregoing attribute degree of membership calculates, can be according to the result of degree of membership calculating to negotiations process
Implement fuzzy control.Shown in Fig. 2 is the trust negotiation process considering fuzzy membership.Send out when negotiation side B receives negotiation side A
The message of initial request certificate resource s sent, then negotiation side B pass through the rule of trusting of oneself and know certificate resource s is subordinate to
Degree threshold value τ, be segmented into several situations according to the different values of τ, if degree of membership threshold value τ=0, expression negotiation side B for
The protection of certificate resource s is non-sensitive, can direct access certificate resource s, therefore may determine that negotiation directly success；Otherwise
If degree of membership threshold value τ=1 then it represents that trust rule be non-fuzzy it is desirable to certificate strictly meets, hence into tradition negotiation
In the stage, carry out credentials disclosure, reach rule until meeting trust, consult successfully, otherwise to fail；If 0 ＜ τ ＜ 1 then it represents that this
When be fuzzy trust rule, can be according to attribute degree of membership computational methods as shown in Figure 1, in interaction each time, if λ
＞ τ then this interaction success, otherwise fails.
In above process, the present invention additionally uses the trust negotiation process based on Fuzzy Bargaining strategy.
During trust negotiation, fuzzy control can also be embodied in the ambiguity of consulting tactical.According to daily life
The problem of middle vision detection understands, in detection, each step detects which option can be regarded as the step choosing made according to inspection policies
Select.This strategy can make corresponding adjustment according to the reaction of tester：If answering correct, just toward high vision angle detecting, instead
It, to low visual acuity angle detecting；If it is high to answer accuracy in a certain detection range, suitably subtract in the detection number of times of this scope
Few, otherwise to increase detection number of times.This process can be regarded as the control process of Fuzzy strategy guidance.
Equally, in trust negotiation if it is possible under Fuzzy Bargaining strategy instruction, can be according to the calculating of fuzzy membership
As a result, choose suitable fuzzy rule to interact it is possible to skip much unnecessary step with fuzzy certificate, be rapidly reached
Consult target, increased negotiation efficiency；The local emphasis consulted that increase can also needed to consult more simultaneously, be also beneficial to sensitivity
The protection of information.
The message of each step sends, and discloses including strategy, certificate discloses, and is all not necessarily necessary, if can be in negotiation point
The calculating of analysis can direct derivation go out to consult target in deriving, then middle disclosure process all can be omitted, thus increasing negotiation efficiency.
Here negotiation result can more accurately be derived according to the calculating of attribute satisfaction, reduce negotiation step, increase efficiency and one-tenth
Power.
Step 1, negotiation side two form a fuzzy trust rule and disclose set PB={ PB1, PB2 ... }, and PB1, PB2 ... are
The fuzzy trust rule of storage in the fuzzy trust rule base of negotiation side two, the certificate resource sent according to the side of negotiationing one, elder generation by
The fuzzy agency of negotiation side two obtains Attribute certificate degree of membership λ of certificate resource, if λ >=τ, current negotiation failure, otherwise, root
According to the result of calculation of the Attribute certificate degree of membership of the certificate resource of negotiation side one request, consult Fang Ercong fuzzy trust rule and disclose
The matching fuzzy trust rule of Attribute certificate degree of membership selecting its corresponding fuzzy credentials in set PB is sent to
Negotiation side one；
Step 2, negotiation side one, according to the fuzzy trust rule receiving auto-negotiation side two, drape over one's shoulders from the fuzzy trust rule of oneself
Matching the obscuring of Attribute certificate degree of membership of its corresponding fuzzy credentials is chosen in dew set PA={ PA1, PA2 ... }
Trust rule and be sent to negotiation side two；
Step 3, negotiation Fang Ercong obscure and select the fuzzy credentials that can disclose to form fuzzy set CB=in credentials storehouse
{ CB1, CB2 ... }, CB1, CB2 ... represent fuzzy credentials, and negotiation side two is from fuzzy set CB according to Attribute certificate degree of membership
Size selects to disclose to the fuzzy credentials of negotiation side one successively；
Step 4, negotiation side two calculate current disclosing to negotiation according to the fuzzy trust rule receiving auto-negotiation side one
The satisfaction of the fuzzy credentials of side one, if reaching threshold value, meets condition, present Fuzzy credentials is fed back to negotiation side
One, from fuzzy set CB, otherwise reselect one can disclose to the fuzzy credentials of negotiation side one, repeated execution of steps 4；
Step 5, negotiation Fang Yicong obscure and select the fuzzy credentials that can disclose to form fuzzy set CA=in credentials storehouse
{ CA1, CA2 ... }, CA1, CA2 ... represent fuzzy credentials, and negotiation side one is from fuzzy set CA according to Attribute certificate degree of membership
Size selects to disclose to the fuzzy credentials of negotiation side two successively；
Step 6, negotiation side one calculate current disclosing to negotiation according to the fuzzy trust rule receiving auto-negotiation side two
The satisfaction of the fuzzy credentials of side two, if reaching threshold value, meets condition, present Fuzzy credentials is fed back to negotiation side
Two, from fuzzy set CA, otherwise reselect one can disclose to the fuzzy credentials of negotiation side two, repeated execution of steps 6；
Step 7, circulation above-mentioned steps 1 are to step 6, until it reaches consult termination condition.
The analysis of fuzzy trust negotiation process：
1st, negotiation success rate can be increased：As policy mandates Attribute certificate identity card, if not being provided that, consult unsuccessfully, but
In the Fuzzy Bargaining with degree of membership, if being provided that association attributes certificate, such as student's identity card, domicile certificate etc., as long as its attribute is subordinate to
Genus degree meets policy mandates, and consulting equally can be successful；
2nd, in negotiation, negotiation side all lists strategy set, the set of certificates being available for disclosing, during analysis, I
Calculated according to degree of membership, select most important, that is, most probable meets other side and requires, and the element that can disclose disclose, Ke Yiyou
The success rate promoting to consult of effect, efficiency.
3rd, in negotiations process, can also be derived according to logical relation, draw some conclusions so that consult in order,
Effectively.
Claims (1)
1. a kind of trust negotiation fuzzy control method is it is characterised in that consulting to carry out between Fang Yiyu negotiation side two, each association
Business side has fuzzy credentials storehouse and fuzzy trust rule base, and fuzzy credentials storehouse is used for storing all fuzzy of current negotiation side
Credentials, each fuzzy credentials is expressed as c. λ, and wherein, c represents Attribute certificate, and λ represents Attribute certificate degree of membership, obscures letter
Appoint rule base to be used for storing all fuzzy trust rule for protecting each fuzzy credentials of current negotiation side, obscure and trust rule
Then pcIt is expressed as pc：s←f(c1, c2...). τ, wherein, s represents resource or fuzzy credentials, c1, c2... represent and require other side
The fuzzy credentials providing, f represents to c1, c2... logical operation, τ represents the degree of membership door meeting fuzzy trust rule requirement
Limit value, and the corresponding fuzzy agency in each negotiation side, then the method comprising the steps of：
Step 1, negotiation side one are intended to access the certificate resource held negotiation side two, therefore initiate resource request to negotiation side two；
After step 2, negotiation side two receive request, by certificate resource and the fuzzy each fuzzy trust rule trusting storage in rule base
Match, obscured trust rule accordingly, thus obtaining this fuzzy degree of membership threshold value τ trusting rule, if τ=0,
Represent that negotiation side two is non-sensitive to the protection of certificate resource, directly return certificate resource to negotiation side one；If τ=1, table
Show trust rule be non-fuzzy it is desirable to certificate resource strictly meets, entrance non-fuzzy negotiation phase, carry out credentials disclosure,
Trust rule until meeting non-fuzzy, consult successfully, otherwise to fail；If 0 ＜ τ ＜ 1, enter the Fuzzy Bargaining that step 3 starts
Stage；
Step 3, negotiation side two form a fuzzy trust rule and disclose set PB={ PB1, PB2 ... }, and PB1, PB2 ... are for consulting
The fuzzy trust rule of storage in the fuzzy trust rule base of side two, the certificate resource sent according to the side of negotiationing one, elder generation is by consulting
The fuzzy agency of side two obtains Attribute certificate degree of membership λ of certificate resource, if λ >=τ, current negotiation failure, otherwise, according to association
The result of calculation of the Attribute certificate degree of membership of certificate resource of Shang Fangyi request, consults Fang Ercong fuzzy trust rule and discloses set
The matching fuzzy trust rule of Attribute certificate degree of membership selecting its corresponding fuzzy credentials in PB is sent to negotiation
Fang Yi；
Step 4, negotiation side one, according to the fuzzy trust rule receiving auto-negotiation side two, disclose collection from the fuzzy trust rule of oneself
Close the matching fuzzy trust of the Attribute certificate degree of membership of its corresponding fuzzy credentials of selection in PA={ PA1, PA2 ... }
Rule is sent to negotiation side two；
Step 5, consult Fang Ercong obscure select in credentials storehouse the fuzzy credentials that can disclose formed fuzzy set CB=CB1,
CB2 ... }, CB1, CB2 ... represent fuzzy credentials, negotiation side two from fuzzy set CB according to the size of Attribute certificate degree of membership according to
Secondary selection can disclose to the fuzzy credentials of negotiation side one；
Step 6, negotiation side two calculate current disclosing to negotiation side one according to the fuzzy trust rule receiving auto-negotiation side one
Fuzzy credentials satisfaction, if reaching threshold value, meet condition, present Fuzzy credentials fed back to negotiation side one, no
From fuzzy set CB, then reselect one can disclose to the fuzzy credentials of negotiation side one, repeated execution of steps 6；
Step 7, consult Fang Yicong obscure select in credentials storehouse the fuzzy credentials that can disclose formed fuzzy set CA=CA1,
CA2 ... }, CA1, CA2 ... represent fuzzy credentials, negotiation side one from fuzzy set CA according to the size of Attribute certificate degree of membership according to
Secondary selection can disclose to the fuzzy credentials of negotiation side two；
Step 8, negotiation side one calculate current disclosing to negotiation side two according to the fuzzy trust rule receiving auto-negotiation side two
Fuzzy credentials satisfaction, if reaching threshold value, meet condition, present Fuzzy credentials fed back to negotiation side two, no
From fuzzy set CA, then reselect one can disclose to the fuzzy credentials of negotiation side two, repeated execution of steps 8；
Step 9, circulation above-mentioned steps 3 are to step 8, until it reaches consult termination condition.
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Cited By (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN108074169A (en) * | 2017-12-06 | 2018-05-25 | 上海电机学院 | A kind of negotiation degree of belief analysis model method for building up |
| CN108090803A (en) * | 2017-12-06 | 2018-05-29 | 上海电机学院 | A kind of negotiation degree of belief computational methods |
| CN108111488A (en) * | 2017-12-06 | 2018-06-01 | 上海电机学院 | A kind of dynamic threshold consulting tactical method |
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Cited By (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN108074169A (en) * | 2017-12-06 | 2018-05-25 | 上海电机学院 | A kind of negotiation degree of belief analysis model method for building up |
| CN108090803A (en) * | 2017-12-06 | 2018-05-29 | 上海电机学院 | A kind of negotiation degree of belief computational methods |
| CN108111488A (en) * | 2017-12-06 | 2018-06-01 | 上海电机学院 | A kind of dynamic threshold consulting tactical method |
| CN108111488B (en) * | 2017-12-06 | 2021-08-24 | 上海电机学院 | Dynamic threshold negotiation strategy method |
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