CN101039178A - Method for building hierachical trust model in open system - Google Patents
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- CN101039178A CN101039178A CN 200710051905 CN200710051905A CN101039178A CN 101039178 A CN101039178 A CN 101039178A CN 200710051905 CN200710051905 CN 200710051905 CN 200710051905 A CN200710051905 A CN 200710051905A CN 101039178 A CN101039178 A CN 101039178A
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Abstract
The invention discloses a method for establishing level trust model in an open system. According to the characteristic of trust and the characteristic of the open system, the method divides the element which effects trust into two layers, bottom layer and basic trust layer. The element comprises property, recommendation and experience. The method mainly solves the initial trust creation of a strange entity. The upper layer is a trust layer, determined by application context. The application trust layer is established on the base of the basic trust layer. The invention can be applied in open system for safety decision-making, has the advantages of extensibility and good maneuverability, etc.
Description
Affiliated technical field
The present invention relates to a kind of method for building up of open system trust model, guarantee the safety of open system by the relation of breaking the wall of mistrust.
Background technology
Trust is safe foundation stone.In open system therefore owing to do not have prior trusting relationship between the entity, can not guarantee whether credible with you if carrying out mutual equipment, can user's privacy information be protected, data can safe transmission etc. problem.The relation of breaking the wall of mistrust is the basis that guarantees open system safety.
Trust management is the method that a series of management are trusted.It is a kind of new method that solves large-scale, open distributed system mandate at present.Trust management is according to the mode difference of the relation of breaking the wall of mistrust, and can be divided into based on the trust management of strategy with based on the trust management of reputation.
Be based on the other side based on the foundation of trusting relationship in the trust management of strategy and whether have required letter of credence, just trust the other side if having, if just do not distrust the other side.Entity uses letter of credence to give trusted entity with transfer of right in the system, and the letter of credence chain is represented the belief propagation of inter-entity.Trusting relationship obtains by letter of credence or letter of credence chain.If do not find letter of credence or letter of credence chain, just expression does not have trusting relationship.A normally binary (binary) decision of this trust management methods and results, requestor or trust, or distrust, therefore service or allow visit, or denied access, Here it is traditional trust management.Based on the trust management system of strategy traditional " authentication " being added " access control " pattern unites and is one, directly with PKI as authorized entity, authority and PKI are directly bound, Resource Managers needn't identify requestor's identity exactly, relatively is fit to the authorisation process in the large-scale distributed system.
Trust management has been simplified authorization, relatively is fit to the safety of managing large scale distributed network, but trust management is mainly considered the static factor of trusting, and has ignored dynamic factor.Therefore trust management comes with some shortcomings.
(1) security measure absolutization.Adopt the method for policy consistency checking to carry out security measure and decision-making, this method is too accurate, can not adapt to polytropy and uncertainty under the distributed environment well.
(2) the safety analysis entity is single.Trust management is only considered the safeguard protection of the side of service, does not consider the safety problem of service call side.
(3) trust management has in fact implied trusting relationship, and what is not illustrated as will be trusted.
(4) can't satisfy the variation of dynamic security context in real time, the ability and the efficient of security strategy checking are limited, and most of trust management system must be collected enough safe letter of credence before the policy consistency checking.
(5) formulation process of security strategy is comparatively complicated, has hindered the application of trust management system.
Based on trusting relationship in the trust management of reputation is to set up according to the specific behavior of entity, judges just whether entity can provide the ability of a certain application.Considered the social characteristic of trusting based on the trust management of reputation, the research to trust model is to belong to this class at present.
Trust management based on reputation is mainly studied the relation of how breaking the wall of mistrust, and how to represent to trust and evaluate trust etc. how, so that carry out security decision.Have much about the research based on the trust management of reputation, the main distinction between them is according to the behavior or the trust itself of trusting, and uses different Mathematical Modelings to represent trust and evaluate trust value.
Essence based on the trust management of reputation is to adopt a kind of relative method that security information is measured and assessed, and can reflect polytropy and uncertainty under the distributed environment preferably.But general certain the specific field that only is fit to of current trust model, the main cause that is not suitable for open system is: (1) is not discussed between the strange entity and how to be broken the wall of mistrust.Current trust model generally is based on third-party recommendation to the trust of strange entity, perhaps prearranges a trust value.(2) current trust model all is a planar structure, poor operability.
Summary of the invention
The objective of the invention is in order to overcome above-mentioned deficiency, design a kind of level trust model method for building up.It can be in the strange inter-entity relation of breaking the wall of mistrust, and trust value is dynamic change.This model has all advantages of hierarchical structure.Comprise mainly how trust forms, which element of confidence is arranged and how to assess these element of confidence values, how to calculate the level trust value, how representational level trust, comparison level trust value size and how to upgrade problem such as trust how.Solve simultaneously and how to set up initial trust between the strange entity.
The thinking that the present invention solves its technical problem is: the level trust model should be able to meet the feature of trust and the characteristics of open system.The feature of trusting mainly contains: subjectivity (different entities is different to the degree of belief of same problem); Condition transitivity (it is with good conditionsi trusting transmission, and promptly trustor is believed nominator's recommendation); The asymmetry of trusting: context dependence (trust is for certain context); The nonmonotonicity of trusting; Dynamic (trust is relevant with environment and time) or the like.The main feature of open system is dynamic and context-aware.
It is a lot of to constitute the key element of trusting, and as experience, trusts third-party recommendation, attributes of entities, application context or the like.These key elements constitute with different forms and trust, if known the other side's interactive history, can rule of thumb carry out trust evaluation, if strange both sides, then can recommend by the third party who trusts, perhaps the attribute that has by entity carries out the trust negotiation relation that progressively breaks the wall of mistrust.The dynamic change of application context decision trust value.We can be divided into these key elements two classes: constitute the key element (as experience, trusting third-party recommendation, attributes of entities etc.) of basic trust and constitute and use the key element (as application context) of trusting.The final purpose of model is to estimate the trust value of an entity owing to break the wall of mistrust.Therefore trust value can be represented with a two-layer structure that bottom is basic trust value (T
b), the upper strata is to use trust value (T
d).The key element of basic trust is the experience by entity oneself, and perhaps the third party recommends and forms, and if there is no the basic trust value between the strange entity of Tui Jianing then obtains by trust negotiation.In case basic trust is set up, just to consider to use to trust, the key element that application is trusted is decided by the context of environment, and change in context is then used trust value and is changed.
How level trust also needs to solve comparison level trust value and evaluate trust key element how.Can be with the trust value discrete representation of each layer, as be expressed as " distrust ", " uncertain ", " low ", " in ", " height ".Obviously the relation between these trust values is a partial ordering relation.Be easy to prove level trust value (T
b, T
d) between relation also be partial ordering relation.
Can use for reference existing appraisal procedure to experience and recommendation trust in the element of confidence.When not having trusting relationship in advance between the entity, generally by the attributes of entities relation of breaking the wall of mistrust.Both sides assess according to the trusted policy of oneself, the attribute difference, and trust value is also different.Context can be divided into: (1) computational context is (as connection situation, communications cost, the bandwidth of communication and near the resource of network; (2) user's context (user's characteristic, position, time, near personnel, current interpersonal relationships etc.); (3) context of physics (as illumination, noise level, transportation condition and temperature etc.).To this element of confidence of context, system is the trusted policy of basis oneself also, different contextual trust values is assessed, and is when oneself and entity in office free time as the trusted policy of a printer in the office, the context trust value be " in "; If when printer busy, its trusted policy may be that any to want to use the trust value of its entity all be " low ", even entity is in office inside.
According to the thinking of above-mentioned its technical problem of solution, the technical solution adopted in the present invention is
A kind of level trust model method for building up of open system is characterized in that may further comprise the steps:
Step 1, set up the level trust model of double-layer structure, bottom is the basic trust layer, and the upper strata is for using trust layer;
Step 2, attributes of entities, experience, third-party recommendation and application context trust factor are divided into two levels, attributes of entities, experience and third-party recommendation trust factor form bottom basic trust layer, and the context trust factor constitutes the upper layer application trust layer.
Also comprise after the described step 2:
Step 3, with the trust value discrete representation be " distrust ", " uncertain ", " low ", " in ", " height ".Here trust value " uncertain " may be to represent uncertainly fully, also may represent to trust value it is low, in still high uncertain, also may represent trust value be high or in uncertain;
The trust value of the level trust model of step 4, described double-layer structure is expressed as T=(T
a, T
c), T wherein
aBe to form T by the bottom trust factor
cConstitute by the upper strata trust factor.
Also comprise after the described step 4:
The assessment of step 5, attributes of entities, between the strange entity by the attribute relation of breaking the wall of mistrust; Trusted policy is expressed as: P ← B (A
1... A
K), B (A wherein
1... A
K) be that the other side may have attribute A
1... A
KBoolean expression; And if only if, and the other side has shown A
i, A
iSatisfy; If P ← true, then trust value is the trust value of regulation; If P ← false, then the attribute trust value is less than the trust value of regulation, and this represents the other side or do not have needed attribute, does not perhaps show this attribute;
Step 6, experience assessment, experience are that trusted entities writes down the situation of being finished some tasks by trusted entities, and the process of finishing each task is called an incident, and an incident reduces trust value, the perhaps value of enhancing trust; Therefore experience is divided into and just trusts experience and negative trust experience, because the importance difference of incident, each incident is distributed weights, and the big more presentation of events of weights is important more, and how much empirical value relies on different experience assessment strategies if increasing or reduces;
The assessment of step 7, third-party recommendation trust: between the strange entity by the third-party recommendation relation of breaking the wall of mistrust, each entity is preserved a trust figure who concerns with other entity trusts, in trust figure, there is different trust path, the trust value of every trust path is a trust value minimum on this path, if there are many trust path, recommend comprehensive trust value to depend on the recommendation effect in different paths;
Step 8, context trust evaluation have different trusted policies at different application contexts;
Step 9, when official hour is out-of-date, application context changes or exist malice to recommend, upgrade trust value.
Also comprise after the described step 9:
Step 10, experience assessment strategy 1-fairness policy, calculate its empirical value according to the event number fully, begin most empirical value for uncertain fully, subsequently the incident importance that occurs in special time and the specific context is distributed weights, the variation of total empirical value calculates according to positive and negative trust incident fully;
Step 11, the optimistic strategy of experience assessment strategy-2 in event, are chosen the just trust incident of weights maximum and are calculated its empirical value, and no matter whether there is negative trust incident;
Step 12, the pessimistic strategy of experience assessment strategy 3-in event, are chosen the maximum negative trust incident of weights and are calculated its empirical value, and just trust incident no matter whether exist;
Step 13, experience assessment strategy 4-punishment strategy, in event, to same incident, the weights of negative trust incident are then punished negative trust incident takes place greater than just trusting incident.
By top technical scheme as can be known, the present invention has following beneficial effect:
1, solved initial trust problem, can protect data at foreign environment.
2, the operability of hierarchy Model is good, has simplified the security decision of open system.
Description of drawings
Fig. 1 is a level trust model structure chart.
Embodiment
Mainly comprise following several aspect.
Trust layering: it is a lot of to constitute the key element of trusting, and as experience, trusts third-party recommendation, attributes of entities, application context or the like.These elements of confidence are divided into two levels: the trust formative factor of bottom is: entity attribute, third party recommend and experience; The trust formative element on upper strata is an application context.The trust value of a hierarchical trust model is expressed as T=(T
a, T
c).T wherein
aBe to form T by the low layer trust factor
cConstitute by the upper strata trust factor.
Trust expression: we will trust discretely be expressed as " distrust ", " uncertain ", " low ", " in ", " height "." uncertain " is to represent uncertainly fully, perhaps represents to trust value it is low, in still high uncertain, perhaps show trust value be high or in uncertain.
Trust value (low, height) expression end trust value is " low ", and the upper strata trust value is " height ".
Level trust value size compares: have only as trust value T
1Greater than trust value T
3, and T
2Greater than T
4The time, level trust value (T
1, T
2) greater than (T
3, T
4), as trust value (height, in) greater than trust value (in, in).
Trust evaluation:
(1) experience assessment: experience is that trusted entities writes down the situation of being finished some tasks by trusted entities, and the process of finishing each task is called an incident.An incident may reduce trust value, also may the value of enhancing trust.Therefore experience can be divided into and just trusting experience and negative trust experience.Because we represent trust value with discrete method, so experience can not be represented with probability.Because the importance difference of incident, each incident is distributed weights.The big more presentation of events of weights is important more.An empirical value can be represented with a step function.The experience assessment strategy is that event is provided appraisal procedure.Each incident has different weights, the just trust incident that weights are big, and empirical value increases fast.The opposite big negative trust incident of weights, empirical value reduces fast.How much empirical value relies on different experience assessment strategies if increasing or reduces.Provide several assessment strategies below:
Fairness policy calculates its empirical value according to the event number fully.Begin most empirical value for uncertain fully, subsequently the incident importance that occurs in special time and the specific context is distributed weights, because empirical value is discrete classification, weights can be represented with 1/15,1/10,1/2,1 etc.As when just trusting weights when being 1/15, show 15 so just trust incidents of needs, empirical value just increases one-level.Otherwise, be 1/15 o'clock as individual negative trust weights, show that a rank fell in empirical value when 15 so negative trust incidents took place.The variation of total empirical value calculates according to positive and negative trust incident fully.
Optimistic strategy is in event, chooses the just trust incident of weights maximum and calculates its empirical value.As exist weights be respectively 1/15,1/10,1/2,1 severally just trusting incident, optimistic strategy is that to choose maximum weights be 1 just trust incident, and no matter whether there is negative trust incident, so empirical value increases a rank.
Pessimistic strategy is in event, chooses the maximum negative trust incident of weights and calculates its empirical value.As existing weights to be respectively 1/15,1/10,1/2,1 several negative trust incident, pessimistic strategy is that to choose weights be 1 negative trust incident, and no matter whether exist and just trust incident, so empirical value reduces a rank.
Punishment strategy is in the event, and to same incident, the weights of negative trust incident are the trust incident greatly just.This is to punish negative trust incident takes place.
(2) attributes of entities assessment: between the strange entity mainly by the attribute relation of breaking the wall of mistrust.Trusted policy can be expressed as: P ← B (A
1... A
K), B (A wherein
1... A
K) be that the other side may have attribute A
1... A
KBoolean expression.A
iSatisfy, and if only if, and the other side has shown A
iIf P ← true, then trust value is the trust value of regulation.If P ← false, then the attribute trust value is less than the trust value of regulation, and this represents the other side or do not have needed attribute, does not perhaps show this attribute.
(3) context trust evaluation: different trusted policies is arranged at different application contexts.As the usage policy of a printer in the office be trust value be " in ".The context trust evaluation carries out trust evaluation according to current contextual information to entity, suppose when printer free time and entity are in office, the context trust value be " in "; Entity is when the office outside, and the context trust value is " low "; During printer busy, the context trust value is " low ".Therefore when the entity out of office or in office, but during printer busy, entity all can not use printer.
(3) recommendation trust assessment: also can be between the strange entity by recommending the relation of breaking the wall of mistrust.Calculated recommendation is trusted integrated value for convenience, has used the trust figure of entity here, and each entity is preserved a trust figure who concerns with other entity trusts.
Trust figure is the unidirectional trusting relationship figure between entity and the entity.In trust figure, exist between an entity and another entity and have many trust path.
The trust value of every trust path is a minimum recommended trust value in this path.
The comprehensive trust value of mulitpath depends on the recommendation effect decision in different paths.
Trust and upgrade:
When following situation takes place, the trust value of should reappraising:
(1) when official hour out-of-date, the basic trust value of reappraising and use trust value;
(2) when application context changes, the application trust value of reappraising;
(3) when having malicious conspiracy (recommending as malice), the basic trust value of reappraising is not considered malice nominator's recommendation results when reappraising, and the nominator is punished, as increasing the punishment weights.
Malice recommend to be judged: if nominator during greater than the malice threshold value stipulated, claims then that this nominator is a malice to the absolute value of the recommendation of an entity and the comprehensive trust value difference of calculating.
Below with reference to the accompanying drawings 1, be described in detail trusting forming process:
Step 1, application layer are to be based upon on the basic layer, and not basic layer is trusted does not just have application layer to trust;
The formation that step 2, basic layer are trusted is made up of experience, recommendation and attributes of entities;
Step 3, at first judge whether to exist historical intersection record, if exist, according to assessment strategy assessment empirical value; Calculated recommendation trust value then; Both calculate the basic trust value according to certain weight;
Step 4, judge that whether the basic trust value satisfies the trusted policy of serving the provider,, if do not satisfy, then require entity to show some attributes, according to attribute assessment basic trust value if satisfy then change step 6;
Step 5, if there is no historical intersection record and recommendation, entity must show some attribute, reaches the trust threshold value of regulation up to the basic trust value;
Step 6, according to user's context, computational context and evaluate application layer trust value hereinafter physically.
Claims (4)
1, a kind of level trust model method for building up of open system is characterized in that may further comprise the steps:
Step 1, set up the level trust model of double-layer structure, bottom is the basic trust layer, and the upper strata is for using trust layer;
Step 2, attributes of entities, experience, third-party recommendation and application context trust factor are divided into two levels, attributes of entities, experience and third-party recommendation trust factor form bottom basic trust layer, and the context trust factor constitutes the upper layer application trust layer.
2, method according to claim 1 is characterized in that also comprising after the described step 2:
Step 3, with the trust value discrete representation be " distrust ", " uncertain ", " low ", " in ", " height ".Here trust value " uncertain " is to represent uncertainly fully, perhaps represents to trust value it is low, in still high uncertain, perhaps represent trust value be high or in uncertain;
The trust value of the level trust model of step 4, described double-layer structure is expressed as T=(T
a, T
c), T wherein
aBe to form T by the bottom trust factor
cConstitute by the upper strata trust factor.
3, method according to claim 2 is characterized in that also comprising after the described step 4:
The assessment of step 5, attributes of entities, between the strange entity by the attribute relation of breaking the wall of mistrust; Trusted policy is expressed as: P ← B (A
1... A
K), B (A wherein
1... A
K) be that the other side may have attribute A
1... A
KBoolean expression; And if only if, and the other side has shown A
i, A
iSatisfy; If P ← true, then trust value is the trust value of regulation; If P ← false, then the attribute trust value is less than the trust value of regulation, and this represents the other side or do not have needed attribute, does not perhaps show this attribute;
Step 6, experience assessment, experience are that trusted entities writes down the situation of being finished some tasks by trusted entities, and the process of finishing each task is called an incident, and an incident reduces trust value, the perhaps value of enhancing trust; Therefore experience is divided into and just trusts experience and negative trust experience, because the importance difference of incident, each incident is distributed weights, and the big more presentation of events of weights is important more, and how much empirical value relies on different experience assessment strategies if increasing or reduces;
The assessment of step 7, third-party recommendation trust: between the strange entity by the third-party recommendation relation of breaking the wall of mistrust, each entity is preserved a trust figure who concerns with other entity trusts, in trust figure, there is different trust path, the trust value of every trust path is a trust value minimum on this path, if there are many trust path, recommend comprehensive trust value to depend on the recommendation effect in different paths;
Step 8, context trust evaluation have different trusted policies at different application contexts;
Step 9, when official hour is out-of-date, application context changes or exist malice to recommend, upgrade trust value.
4, method according to claim 3 is characterized in that also comprising after the described step 9:
Step 10, experience assessment strategy 1-fairness policy, calculate its empirical value according to the event number fully, begin most empirical value for uncertain fully, subsequently the incident importance that occurs in special time and the specific context is distributed weights, the variation of total empirical value calculates according to positive and negative trust incident fully;
Step 11, the optimistic strategy of experience assessment strategy-2 in event, are chosen the just trust incident of weights maximum and are calculated its empirical value, and no matter whether there is negative trust incident;
Step 12, the pessimistic strategy of experience assessment strategy 3-in event, are chosen the maximum negative trust incident of weights and are calculated its empirical value, and just trust incident no matter whether exist;
Step 13, experience assessment strategy 4-punishment strategy, in event, to same incident, the weights of negative trust incident are then punished negative trust incident takes place greater than just trusting incident.
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Cited By (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN102495978A (en) * | 2011-11-09 | 2012-06-13 | 南京邮电大学 | Computing method for reliability index of task executive and task execution point in open computing environment |
| CN101692676B (en) * | 2009-09-29 | 2012-09-19 | 华中师范大学 | Hybrid trust management system and trust evaluation method thereof under open environment |
| WO2012162873A1 (en) * | 2011-05-27 | 2012-12-06 | Nokia Corporation | Method and apparatus for role-based trust modeling and recommendation |
| CN109711555A (en) * | 2018-12-21 | 2019-05-03 | 北京瀚海星云科技有限公司 | A kind of method and system of predetermined depth learning model single-wheel iteration time |
| CN109711535A (en) * | 2018-12-21 | 2019-05-03 | 北京瀚海星云科技有限公司 | A method of the time is calculated using similar layer predetermined depth learning model middle layer |
-
2007
- 2007-04-18 CN CN200710051905A patent/CN100586059C/en not_active Expired - Fee Related
Cited By (7)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN101692676B (en) * | 2009-09-29 | 2012-09-19 | 华中师范大学 | Hybrid trust management system and trust evaluation method thereof under open environment |
| WO2012162873A1 (en) * | 2011-05-27 | 2012-12-06 | Nokia Corporation | Method and apparatus for role-based trust modeling and recommendation |
| CN102495978A (en) * | 2011-11-09 | 2012-06-13 | 南京邮电大学 | Computing method for reliability index of task executive and task execution point in open computing environment |
| CN102495978B (en) * | 2011-11-09 | 2015-03-04 | 南京邮电大学 | Computing method for reliability index of task executive and task execution point in open computing environment |
| CN109711555A (en) * | 2018-12-21 | 2019-05-03 | 北京瀚海星云科技有限公司 | A kind of method and system of predetermined depth learning model single-wheel iteration time |
| CN109711535A (en) * | 2018-12-21 | 2019-05-03 | 北京瀚海星云科技有限公司 | A method of the time is calculated using similar layer predetermined depth learning model middle layer |
| CN109711535B (en) * | 2018-12-21 | 2021-05-11 | 深圳致星科技有限公司 | Method for predicting layer calculation time in deep learning model by using similar layer |
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| Publication number | Publication date |
|---|---|
| CN100586059C (en) | 2010-01-27 |
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