CN104038539B - A kind of dynamic mobile P 2 P trust management model system and method - Google Patents
A kind of dynamic mobile P 2 P trust management model system and method Download PDFInfo
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- CN104038539B CN104038539B CN201410240774.1A CN201410240774A CN104038539B CN 104038539 B CN104038539 B CN 104038539B CN 201410240774 A CN201410240774 A CN 201410240774A CN 104038539 B CN104038539 B CN 104038539B
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Abstract
The invention discloses a kind of dynamic mobile P 2 P trust management model system, each node of the system is calculated by local trust value and memory module, indirect reputation value metric module, trade management module are constituted；Local trust value computing module and memory module are that the historical transactional information of integration node calculates the global trust value of egress, and storage had the Transaction Information and trust value of the node of transaction with this node, trade management module is given the trust value of node；Indirect reputation value metric module is to collect the trust value of neighbor node feedback, validation verification is carried out to the trust value fed back to received, exclude incredible value of feedback, selectively converge after calculate node reputation value and the reputation value of the node calculated is sent to trade management module；Trade management module is to select transaction node according to the height of node reputation value or trust value, performs transaction, and the information of the node of this transaction, which is sent to trust value computing, memory module, to be stored.
Description
Technical field
The present invention relates to a kind of dynamic mobile P 2 P trust management model system and method, belong to wireless communication skill
Art field.
Background technology
Peer-to-peer network is (referred to as：P2P successful application) causes numerous researchers to begin to focus on mobile computing field.And with
That the storage of intelligent mobile terminal, computing capability constantly strengthen, battery capacity constantly expands, resource-sharing, community network etc. exist
Line P2P application extensions more and more hold out broad prospects to wireless domain.
But the mobility of mobile P 2 P network interior joint, anonymity, the finiteness of resource, node are dynamically added and left
So that there is a series of unsafe factor in network, such as：Service quality is unreliable, malicious node may provide virus document,
False file, selfish node may be not involved in the interaction of network.These factors can make to lack trust between node, hinder mobile P 2 P
The growth of technology.And the present invention the problem of can solve above well.
The content of the invention
Present invention aims at a kind of dynamic mobile P 2 P trust management model system and method are provided, this method is solved
The problem of trusting relationship between node is set up under mobile P 2 P network, and solve the trusting relationship between node with the time
The problem of change and node provide spurious feedback.
The technical scheme adopted by the invention to solve the technical problem is that：A kind of dynamic mobile P 2 P trust management model
System is (referred to as：DPTM), each node of the system is by local trust value computing module, memory module, indirect reputation value degree
Measure module, trade management module composition.Local trust value computing module and memory module are the historical transactional informations of integration node,
The global trust value of egress is calculated, storage had the Transaction Information and trust value of the node of transaction with this node, node
Trust value give trade management module.Indirect reputation value metric module is to collect the trust value of neighbor node feedback, to receiving
The trust value that feeds back to carry out validation verification, exclude incredible value of feedback, the name of calculate node after selectively converging
The reputation value of the node calculated is simultaneously sent to trade management module by reputation value.The function of trade management module is according to node fame
The height of value or trust value selects transaction node, performs transaction, the information of the node of this transaction be sent to trust value computing,
Memory module is stored.
System of the present invention is mobile P 2 P trust management model system, will be whole in the local trust value of calculate node
The individual time is divided into several transaction intervals, in the trust value of the interval interior calculate node in real time of each transaction, then by each transaction
Trust value in interval is weighted, and finally gives the global trust value of node.The trust value so calculated can more reflect section
The current behavior of point.On this basis, the trust value of neighbor node feedback is collected, spurious feedback is excluded, finally calculates section
The reputation value of point.
The node of system of the present invention more believes the trust value calculated by the direct dealing experience of oneself, rather than
The reputation value calculated by iterative manner.Because substantial amounts of flooding query messages can be produced in an iterative process, and node
Spoofing may be received.Trust and fame is measured with as node is credible, when requesting node knows service node
During trust value just not by way of the whole network iteration calculate node reputation value, but trust value is used as to the credible amount of node
Degree.
The present invention also provides a kind of execution method of dynamic mobile P 2 P trust management model system, and this method is included such as
Lower step：
Step 1：File request node sends the trust value inquiry request to service node, if service node is neighbours' section
Point is then calculated to local trust value and memory module inquires about trust value, and the trust value then is sent into trade management module；
Step 2：Otherwise, indirect reputation value metric module is inquired about, i.e., neighbor node is collected by indirect reputation value metric module
The trust value to service section of feedback, weeds out spurious feedback, then calculates reputation value of the requesting node to service node.Most
The reputation value is sent to trade management module afterwards；
Step 3：Trust value and reputation value that trade management module is relatively received, selection have maximum local trust value or
The node of indirect reputation value is traded.After the completion of transaction will transaction success or failure situation be sent to local trust value calculate and
Memory module, by trust value of the module computation requests node to service node.
Beneficial effect：
1st, feature of the present invention with dynamic and personalization.
2nd, the present invention can suppress malicious node some node is excessively exaggerated or slandered.
3rd, the present invention preferably solves the problems, such as strategy attack and calumny attack, improves the file in mobile P 2 P network
Download into
Power.
Brief description of the drawings
Fig. 1 is system structure diagram of the invention.
Fig. 2 is execution method flow diagram of the invention.
Embodiment
The invention is described in further detail below in conjunction with Figure of description.
As shown in figure 1, the present invention provides a kind of dynamic mobile P 2 P trust management model system (referred to as：DPTM), this is
Each node of system is calculated by local trust value and memory module, indirect reputation value metric module, trade management module are constituted.
Local trust value computing module and memory module are the historical transactional informations of integration node, calculate the global trust value of egress,
Storage had the Transaction Information and trust value of the node of transaction with this node, and trade management mould is given the trust value of node
Block.Indirect reputation value metric module is to collect the trust value of neighbor node feedback, is had to the trust value fed back to received
The checking of effect property, excludes incredible value of feedback, the reputation value of calculate node and the node calculated after selectively converging
Reputation value is sent to trade management module.The function of trade management module is selected according to the height of node reputation value or trust value
Transaction node, performs transaction, and the information of the node of this transaction, which is sent to trust value computing, memory module, to be stored.
System of the present invention is mobile P 2 P trust management model system, will be whole in the local trust value of calculate node
The individual time is divided into several transaction intervals, in the trust value of the interval interior calculate node in real time of each transaction, then by each transaction
Trust value in interval is weighted, and finally gives the global trust value of node.The trust value so calculated can more reflect section
The current behavior of point.On this basis, the trust value of neighbor node feedback is collected, spurious feedback is excluded, finally calculates section
The reputation value of point.
The node of the system more believes the trust value calculated by the direct dealing experience of oneself, rather than by repeatedly
The reputation value calculated for mode.Because substantial amounts of flooding query messages can be produced in an iterative process, and node may
Receive spoofing.Trust and fame is measured with as node is credible, when requesting node knows the trust value of service node
When just not by way of the whole network iteration calculate node reputation value, but trust value being measured as node is credible.
" the performing the trust value for merchandising and updating transaction node " of the present invention and " search for the indirect fame of simultaneously calculate node
The specific implementation process of value " is as follows：
(1) trust value for merchandising and updating transaction node is performed；
In the trust value of calculate node, influence of the interval transaction of different transaction to node trust value is distinguished.Away from current
The weight that time nearer transaction is endowed is higher, and the transaction of current time of adjusting the distance farther out carries out appropriate decay.So both
The current behavioral aspect of node can be embodied can encourage node to be continuously kept good behavior in a network again.Therefore, will be whole
Period is divided into several transaction intervals, and t is used respectively1,t2,t3......tnRepresent.N is bigger to be represented closer to current transaction
Time.The interval length of transaction can be divided according to the trading situation between node.If the transaction between two nodes is non-
Often frequently, then the interval length of transaction can divide shorter.Otherwise merchandise interval length can just divide greatly one
A bit.Assuming that in transaction interval tkIt is interior, node i and node j Successful Transactions suc times, failed transactions fail times, then in tkThis
Individual transaction interval interior nodes i is to node j trust value：
In order to accommodate the dynamic of trust, this method is the trust value calculated in different transaction intervals by formula (1)
The different weight of distribution.It is bigger closer to the allocated weight of the trust value of current time, it is otherwise relatively small.It is specific and
Speech, system of the present invention is that the distribution of weight is performed using attenuation function.By weighting the trust value in each transaction interval
To obtain global trust value of the node i to node j.I.e. node i is to node j global trust value：
The implication of each parameter is as follows in formula (2)：
tk：K-th of transaction is interval.
(j)：In trust values of k-th of transaction interval interior nodes i to node j.
Wk：In tkIn individual transaction is interval, weight of the node i to node j trust value.
ρn+1-k：For the weights of the interval trust value distribution of each transaction.ρ(0<ρ<1) value can neatly be determined by system.K is
K-th of transaction is interval；N is the interval number of total transaction.Weights WkThe condition must being fulfilled for is：0<Wk<1 and Wn>Wn-1>…>W1。
(2) the indirect reputation value of search and calculate node；
Node j reputation value is a kind of indirect trust value of overall importance, is pair for the neighbor node feedback that node i is received
The set of node j trust value.It represents all nodes for having transaction with j in network and the subjectivity of node j behavior is seen
Method.Node i before node j transaction with needing decision node j credibility.This both can also rely on fame by trust value
Value.Just measured when resource request node possesses the trust value to contributed nodes in this, as node is credible, without
Computing resource provides the reputation value of node again.Otherwise will calculate node reputation value.
But reputation value is calculated by collecting the feedback of nodes, so being excluded when calculating reputation value
Spurious feedback.Therefore, the measure that this method is taken is the similitude detection for carrying out node feeding back information, difference is excluded very big
Feedback information, i.e., the consistent trust value of similarity-rough set fed back only with trusted node.
The detecting step of system of the present invention comprises the following steps：
After node receives the trust value of neighbor node feedback, the flat of the trust value that receives is calculated according to formula (3) first
Average, then calculates the standard deviation of the trust value received according to formula (4).Finally, trust value and letter are calculated according to formula (5)
Appoint the departure degree of the average value of value.If the trust value of some node, formula (5) formula are excessively calumniated or exaggerated to malicious node
It will set up.The purpose of formula (5) is that verification individual node is whole to all neighbor nodes in the trust value and network of some node
Departure degree between the trust value that body is provided.The standard of the trust value provided if the deviation from degree beyond all neighbor nodes
Deviation, then it is assumed that the trust value is excessively exaggerated or slandered, is spurious feedback and is abandoned in the reputation value of calculate node
The value of feedback.After all incredible feedback trust values received have been rejected, using formula (6) come the fame of calculate node
Value.Institute can suppress malicious node and some node is excessively exaggerated or slandered in this way.
The implication of symbol is as follows in above-mentioned formula (3), formula (4), formula (5)：
Tk(j)：Trust values of the neighbor node k to offer node j
Ti(k)：Trust value of the resource request node i to neighbor node k
The average value of node j trust value is provided
Sj：The standard deviation of node j trust values is provided
n：The number of neighbor node of the trust value of node i more than 0.5.
As n=0 or 1, similitude detection is no longer carried out, directly R is calculated with formula (6)ij。
Reputation value R of the node i to node jijComputational methods be：
Wherein RkjRepresent reputation values of the node k to node j.
As shown in Fig. 2 the present invention provides a kind of execution method of dynamic mobile P 2 P trust management model system, the party
Method comprises the following steps：
Step 1：File request node sends the trust value inquiry request to service node.
Step 2：Trust value is inquired about to trust value computing, memory module if service node is neighbor node, then will
The trust value is sent to trade management module.
Step 3：Otherwise, inquiry fame value metric module is to clothes by reputation value metric module collection neighbor node feedback
The trust value of business section, weeds out spurious feedback, then calculates reputation value of the requesting node to service node.Finally by the fame
Value is sent to trade management module.
Step 4：Trust value and reputation value that trade management module is relatively received, selection have maximum trust value or fame
The node of value is traded.Transaction success or failure situation is sent to trust value computing, memory module after the completion of transaction.
Step 5：Trust value computing, memory module store transaction trust simultaneously trust of the computation requests node to service node
Value.
Claims (6)
1. a kind of dynamic mobile P 2 P trust management model system, it is characterised in that：Each node of the system is by part
Trust value computing and memory module, indirect reputation value metric module, trade management module composition；Local trust value is calculated and stored
Module is that the historical transactional information of integration node calculates the global trust value of egress, and storage had the node of transaction with this node
Transaction Information and trust value, give trade management module the trust value of node；Indirect reputation value metric module is to collect
The trust value of neighbor node feedback, carries out validation verification to the trust value fed back to received, excludes incredible value of feedback,
Selectively converge after calculate node reputation value and the reputation value of the node calculated is sent to trade management module；Transaction pipe
It is to select transaction node according to the height of node reputation value or trust value to manage module, performs transaction, the node of this transaction
Information be sent to trust value computing, memory module storage, the system includes：
(1) trust value for merchandising and updating transaction node is performed；
In the trust value of calculate node, influence of the interval transaction of different transaction to node trust value is distinguished；Away from current time
The weight that nearer transaction is endowed is higher, and the transaction of current time of adjusting the distance farther out carries out appropriate decay；By the whole time
Section is divided into several transaction intervals, and t is used respectively1,t2,t3......tnRepresent；The bigger expressions of n are closer to current exchange hour；
The interval length of transaction is divided according to the trading situation between node, if the transaction between two nodes is very frequent, that
The interval length of transaction can divide shorter, and the length in interval of otherwise merchandising just can divide larger；Assuming that
Merchandise interval tkIt is interior, node i and node j Successful Transactions suc times, failed transactions fail times, then in tkThis transaction is interval
Interior nodes i is to node j trust value：
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Different weights are distributed for the interval interior trust value calculated by formula (1) of different transaction, closer to the current time
Trust value it is allocated weight it is bigger, it is otherwise relatively small；The system performs the distribution of weight using attenuation function,
Global trust value of the node i to node j is obtained by weighting the trust value in each transaction interval, i.e., node i is to the whole of node j
Body trust value is：
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The implication of each parameter is as follows in formula (2)：
tk：K-th of transaction is interval；
In trust values of k-th of transaction interval interior nodes i to node j；
Wk：In tkIn individual transaction is interval, weight of the node i to node j trust value；
ρn+1-k：For the weights of the interval trust value distribution of each transaction, ρ (0<ρ<1) value can neatly be determined that k is k-th by system
Transaction is interval, and n is the interval number of total transaction, weights WkThe condition must being fulfilled for is：0<Wk<1 and Wn>Wn-1>…>W1；
(2) the indirect reputation value of search and calculate node；
Node j reputation value is a kind of indirect trust value of overall importance, be node i receive neighbor node feedback to node
The set of j trust value, it represents in network all nodes for having transaction with j to the subjective opinion of node j behavior, section
Decision node j credibility is needed before point i and node j transaction；Both reputation value was also depended on by trust value；When resource request section
Point is just measured when possessing the trust value to contributed nodes in this, as node is credible, and no longer computing resource provides section
The reputation value of point；
Reputation value is calculated by collecting the feedback of nodes, so being excluded when calculating reputation value false anti-
Feedback；Therefore, what the system took is the similitude detection for carrying out node feeding back information, difference very big feedback letter is excluded
Breath, only with the consistent trust value of the similarity-rough set of trusted node feedback.
2. a kind of dynamic mobile P 2 P trust management model system according to claim 1, it is characterised in that：The system
The whole time is divided into several transaction intervals by system in the local trust value of calculate node, real in each transaction is interval
When calculate node trust value, then by it is each transaction interval in trust value be weighted, finally give the global trust of node
Value；The trust value of neighbor node feedback is collected, spurious feedback is excluded, the final reputation value for calculating egress.
3. a kind of dynamic mobile P 2 P trust management model system according to claim 1, it is characterised in that：The system
The trust value that the node of system is calculated by the direct dealing experience of oneself；Trust and fame is with as the credible amount of node
Degree, when requesting node knows the trust value of service node just not by way of the whole network iteration calculate node reputation value, and
It is to measure trust value as node is credible.
4. a kind of dynamic mobile P 2 P trust management model system according to claim 1, it is characterised in that：The system
Unite as mobile P 2 P trust management model system.
5. a kind of dynamic mobile P 2 P trust management model system according to claim 1, it is characterised in that the system
The execution method of system comprises the following steps：
Step 1：File request node sends the trust value inquiry request to service node, if service node is neighbor node
Calculated to local trust value and memory module inquires about trust value, the trust value is then sent to trade management module；
Step 2：Otherwise, indirect reputation value metric module is inquired about, neighbor node feedback is collected by indirect reputation value metric module
To the trust value of service section, spurious feedback is weeded out, reputation value of the requesting node to service node is then calculated, finally should
Reputation value is sent to trade management module；
Step 3：Trust value and reputation value that trade management module is relatively received, selection have maximum local trust value or indirect
The node of reputation value is traded；Transaction success or failure situation is sent into local trust value after the completion of transaction to calculate and store
Module, by trust value of the module computation requests node to service node.
6. a kind of detection method of dynamic mobile P 2 P trust management model system, it is characterised in that methods described includes as follows
Step：
After node receives the trust value of neighbor node feedback, the average value of the trust value received is calculated according to formula (3) first,
Then the standard deviation of the trust value received is calculated according to formula (4)；Finally, trust value and trust value are calculated according to formula (5)
Average value departure degree；If the trust value of some node is excessively calumniated or exaggerated to malicious node, formula (5) into
It is vertical；The effect of formula (5) is that verification individual node is integrally provided to all neighbor nodes in the trust value and network of some node
Trust value between departure degree；The standard deviation of the trust value provided if the deviation from degree beyond all neighbor nodes,
Then think that the trust value is excessively exaggerated or slandered, be spurious feedback and abandon the feedback in the reputation value of calculate node
Value；After all incredible feedback trust values received have been rejected, using formula (6) come the reputation value of calculate node；
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The implication of symbol is as follows in above-mentioned formula (3), formula (4), formula (5)：
Tk(j)：Trust values of the neighbor node k to offer node j；
Ti(k)：Trust value of the resource request node i to neighbor node k；
The average value of node j trust value is provided；
Sj：The standard deviation of node j trust values is provided；
n：The number of neighbor node of the trust value of node i more than 0.5；
As n=0 or 1, similitude detection is no longer carried out, directly R is calculated with formula (6)ij；
Reputation value R of the node i to node jijComputational methods be：
Wherein RkjRepresent reputation values of the node k to node j.
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Citations (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN101217396A (en) * | 2007-12-29 | 2008-07-09 | 华中科技大学 | An Ad hoc network invasion detecting method and system based on trust model |
| CN101404592A (en) * | 2008-11-14 | 2009-04-08 | 西安交通大学 | Total trust degree decision method based on history evidence window |
| CN101714976A (en) * | 2009-10-15 | 2010-05-26 | 浙江大学 | Method for resisting malicious behaviors of nodes in P2P network |
-
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Patent Citations (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN101217396A (en) * | 2007-12-29 | 2008-07-09 | 华中科技大学 | An Ad hoc network invasion detecting method and system based on trust model |
| CN101404592A (en) * | 2008-11-14 | 2009-04-08 | 西安交通大学 | Total trust degree decision method based on history evidence window |
| CN101714976A (en) * | 2009-10-15 | 2010-05-26 | 浙江大学 | Method for resisting malicious behaviors of nodes in P2P network |
Non-Patent Citations (2)
| Title |
|---|
| 基于信任和名誉的P2P安全模型;索瑾;《中国优秀硕博学位论文全文数据库（硕士）信息科技辑》;20070615;第29-36页 * |
| 面向P2P电子商务的信任管理模型研究;崔萌;《中国优秀硕博学位论文全文数据库（硕士）信息科技辑》;20120915;第31-42页 * |
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