CN109474463A - IoT edge device method for evaluating trust, device, system and proxy server - Google Patents
IoT edge device method for evaluating trust, device, system and proxy server Download PDFInfo
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- CN109474463A CN109474463A CN201811308426.8A CN201811308426A CN109474463A CN 109474463 A CN109474463 A CN 109474463A CN 201811308426 A CN201811308426 A CN 201811308426A CN 109474463 A CN109474463 A CN 109474463A
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
- H04L41/00—Arrangements for maintenance, administration or management of data switching networks, e.g. of packet switching networks
- H04L41/14—Network analysis or design
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
- H04L41/00—Arrangements for maintenance, administration or management of data switching networks, e.g. of packet switching networks
- H04L41/04—Network management architectures or arrangements
- H04L41/044—Network management architectures or arrangements comprising hierarchical management structures
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
- H04L41/00—Arrangements for maintenance, administration or management of data switching networks, e.g. of packet switching networks
- H04L41/04—Network management architectures or arrangements
- H04L41/046—Network management architectures or arrangements comprising network management agents or mobile agents therefor
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
- H04L41/00—Arrangements for maintenance, administration or management of data switching networks, e.g. of packet switching networks
- H04L41/14—Network analysis or design
- H04L41/147—Network analysis or design for predicting network behaviour
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Abstract
The invention discloses a kind of IoT edge device method for evaluating trust, prediction trust value in current period is obtained according to trust value of the equipment within the time in the past period using time window method, there is temporal correlation due to trusting, prediction trust value delimit the possible range of current trust value to a certain extent, the practical trust value received is compared with the difference of prediction trust value with error threshold, judge whether the trust value of interaction is credible, if insincere, trust value is modified by carrying out penal system, the polymerization for carrying out feedback trust after amendment again calculates, an available more structurally sound global trust value, avoid spurious feedback, it is maliciously evaluated caused by the malicious acts such as malicious attack and leaguing together for some evil end, improve the safety of the reliability and system of global trust.The invention also discloses a kind of IoT edge device trust evaluation device, a kind of edge proxy server and a kind of IoT edge device trust evaluation systems, have above-mentioned beneficial effect.
Description
Technical field
The present invention relates to internet of things field, in particular to a kind of IoT edge device method for evaluating trust, a kind of edge IoT
Equipment trust evaluation device, a kind of edge proxy server and a kind of IoT edge device trust evaluation system.
Background technique
Internet of Things and the integrated of edge calculations are one of hot spots of current research, and edge calculations service, which can substantially reduce, to be needed
The data volume to be transmitted reduces network delay and quickly responds service request.Trust due to lacking between Internet of Things edge device,
It hampers people and calculates service for Internet of Things edge calculations as outsourcing.So needing the trust machine of service-strong, lightweight
System guarantees service quality cooperative behaviors and establishes the reliable trust between Internet of Things edge device.
Internet of Things edge calculations architecture currently based on the trust computing mechanism of feedback mainly includes as shown in Figure 1:
Network layer, Agent layer and mechanical floor.Network layer uses traditional cloud computing platform, and Agent layer is used to monitor the clothes of internet of things equipment
Business behavior simultaneously polymerize the feedback from internet of things equipment, reduces the trust computing cost in mechanical floor.Mechanical floor master
If the trust value mutually assessed is submitted to agency during service collaboration.And the global trust of an equipment includes setting
Direct trust between standby, the feedback from other edge devices are trusted and the feedback from service broker is trusted.And trust
It calculates and is completed completely by Agent layer and mechanical floor, do not need the participation of central network.For current network bandwidth and reliability,
Trust calculating in network edge and can obtain shorter response time, higher execution efficiency and lesser network load pressure
Power.
The existing trust problem solved between Internet of Things edge device is mainly to pass through direct trust and the generation of equipment room
Reason to the objective grading of equipment is polymerize to obtain the global trust of equipment, establishes effective faith mechanism with this.Possessing
In the environment of Internet of Things edge device, if carrying out service collaboration between two equipment, one of equipment is sent to its agency
The trust value of partner is requested.Due to security risks various in Internet of Things and attack, Internet of Things edge device just suffers from falseness
The various malicious acts such as feedback, malicious attack and leaguing together for some evil end are set so the direct trust of equipment room and agency receive to come from
There may be false trust values for all feedbacks of standby layer other equipment, so that obtaining after acting on behalf of layers of polymer and calculating anti-
The calculating of equipment global trust is trusted there are certain error and is affected in feedback, and global trust accuracy rate is low, influences security of system
And reliability.
Therefore, how in faith mechanism raising edge device evaluation confidence level, improve Internet of Things edge device
The safety and reliability of environment are those skilled in the art's technical issues that need to address.
Summary of the invention
The object of the present invention is to provide a kind of IoT edge device method for evaluating trust, this method can believe edge device
Appoint the detection judgement of value, and the trust value from non-trusted device is modified its trust value by penal system, with this
The malicious acts such as spurious feedback, malicious attack and leaguing together for some evil end are coped with, to improve the accuracy and system of global trust
Security reliability；It is a further object of the present invention to provide a kind of IoT edge device trust evaluation devices, a kind of edge proxies service
Device and a kind of IoT edge device trust evaluation system.
In order to solve the above technical problems, the present invention provides a kind of IoT edge device method for evaluating trust, comprising:
When edge proxy server receives the trust value request to the first equipment, current and first equipment is filtered out
Interactive edge device obtains the second equipment；
The instruction of the first equipment trust value computing is sent to second equipment；
Predict that second equipment to the trust value of first equipment, obtains prediction letter according to the history trust value of storage
Appoint value；
The difference of the practical trust value that calculating receives and corresponding prediction trust value；
To the difference compared with error threshold carries out size, and the direct trust value is divided into according to comparison result
Abnormal trust value and normal trust value；
The abnormal trust value is modified by penalty mechanism, obtains revised trust value；
The revised trust value is polymerize with the normal trust value, obtains feedback trust value；
The feedback trust value is fed back into request originator, so as to the request originator by the feedback trust value with
Itself carries out fusion calculation to the direct trust value that first equipment evaluation obtains, and obtains the global trust of first equipment
Value.
Preferably, predict second equipment to the trust value of first equipment, packet according to the history trust value of storage
It includes:
It filters out second equipment in preset period of time span and history letter is obtained to the trust value of first equipment
Appoint value；
The average value for calculating the history trust value, using the average value being calculated as prediction trust value.
Preferably, the calculation method of the direct trust value includes:
Obtain in preset time other side in two equipment interactive processes complete the scoring of request task ability front sum and
The sum negatively to score；Wherein, the front scoring and the negative scoring comment the service quality of other side for interaction both sides
Get；
The sum for counting the front scoring accounts for the ratio of the front scoring and the sum negatively to score, obtains
Direct trust value.
Preferably, the calculation method of the error threshold includes:
WhenIndicate equipment diWith djBetween direct trust value in the Δ t time, when n is time cycle span,
The calculating that error threshold is carried out according to threshold calculations formula, obtains error threshold；
Wherein, the threshold calculations formula specifically:
Preferably, request originator is by the feedback trust value and the direct letter that itself obtains to first equipment evaluation
Value is appointed to carry out fusion calculation, comprising:
It obtains preset direct trust and feedback trusts corresponding weight factor, obtain direct weight and feedback
Weight；
Product value and the feedback trust value and the feedback to the direct trust value and the direct weight are weighed
The product value summation of weight, obtains global trust value.
Preferably, the determination method of the weight factor includes:
WhenFor the equipment d within the Δ t timeiTo djWhen completing the sum that request task ability negatively scores,
It is calculated according to factor calculation formula, using obtained data as direct weight；
The difference for calculating 1 with the direct weight, using obtained result as feedback weight；
Wherein, the factor calculation formula specifically:
Preferably, the abnormal trust value is modified by penalty mechanism, comprising:
WhenFor the equipment d within the Δ t timeiTo djThe sum that request task ability negatively scores is completed,Indicate equipment diWith djBetween direct trust value in the Δ t time when, according to correction formula to abnormal trust value into
Row amendment, obtains revised trust value；
Wherein, the correction formula specifically:Wherein β is amendment
The factor,
The present invention discloses a kind of IoT edge device trust evaluation device, comprising:
Edge device screening unit, when for receiving to the request of the trust value of the first equipment, filter out it is current with it is described
The edge device of first equipment interaction, obtains the second equipment；
Computations transmission unit, for sending the instruction of the first equipment trust value computing to second equipment；
Trust predicting unit, predicts second equipment to first equipment for the history trust value according to storage
Trust value obtains prediction trust value；
Difference computational unit, for calculating the difference of the practical trust value received with corresponding prediction trust value；
Difference comparsion unit, for the difference with error threshold progress size compared with, and according to comparison result by institute
It states direct trust value and is divided into abnormal trust value and normal trust value；
Abnormal amending unit obtains revised letter for being modified by penalty mechanism to the abnormal trust value
Appoint value；
Feedback is trusted polymerized unit and is obtained for the revised trust value to polymerize with the normal trust value
To feedback trust value；
Feedback trusts transmission unit, for the feedback trust value to be fed back to request originator, so as to request hair
Side is played by the feedback trust value and itself fusion calculation is carried out to the direct trust value that first equipment evaluation obtains, is obtained
The global trust value of first equipment.
The present invention discloses a kind of edge proxy server, comprising:
Memory, for storing program；
Processor, the step of IoT edge device method for evaluating trust is realized when for executing described program.
The present invention discloses a kind of IoT edge device trust evaluation system, comprising:
Request originator requests the trust value of the first equipment for sending to edge proxy server；According to itself
The interaction scenario of first equipment calculates the trust value to the first equipment, obtains the direct trust value to the first equipment；It receives anti-
When presenting trust value, the feedback trust value and the direct trust value are subjected to fusion calculation, obtain the whole of first equipment
Body trust value；
Edge proxy server when for receiving to the request of the trust value of the first equipment, filters out current with described the
The edge device of one equipment interaction, obtains the second equipment；The instruction of the first equipment trust value computing is sent to second equipment；Root
Predict that second equipment to the trust value of first equipment, obtains prediction trust value according to the history trust value of storage；It calculates
The difference of the practical trust value received and corresponding prediction trust value；To the difference compared with error threshold carries out size,
And the direct trust value is divided by abnormal trust value and normal trust value according to comparison result；By penalty mechanism to institute
It states abnormal trust value to be modified, obtains revised trust value；By the revised trust value and the normal trust value
It is polymerize, obtains feedback trust value；The feedback trust value is fed back into request originator；
Second equipment, when for receiving the first equipment trust value computing instruction, according to the interaction with the first equipment
Situation calculates the trust value to the first equipment, obtains practical trust value；The practical letter is returned to the edge proxy server
Appoint value.
IoT edge device method for evaluating trust provided by the present invention, in the Internet of Things of the trust computing mechanism based on feedback
Under network edge counting system structure, obtained currently using time window method according to trust value of the equipment within the time in the past period
Prediction trust value in period has temporal correlation due to trusting, and prediction trust value delimit current letter to a certain extent
The possible range for appointing value compares the practical trust value being currently received and the difference of prediction trust value and the error threshold of setting
Compared with judging in information exchange whether the trust value of interaction is credible, if the trust value of non-trusted device, pass through and carry out penal system
Trust value is modified, the polymerization for carrying out feedback trust again to realize the calibration to equipment is distrusted, after amendment calculates, can be with
A more structurally sound global trust value is obtained, the malicious acts such as spurious feedback, malicious attack and leaguing together for some evil end is avoided and causes
Malice evaluation, the safety of the reliability and system of global trust can be improved.In addition, the edge IoT provided in this embodiment
The trust that equipment method for evaluating trust can also be applied in recommender system calculates, and realizes the accurate recommendation of equipment, promotes work
Efficiency.
The present invention also provides a kind of IoT edge device trust evaluation device, a kind of edge proxy server and a kind of IoT
Edge device trust evaluation system has above-mentioned beneficial effect, and details are not described herein.
Detailed description of the invention
In order to more clearly explain the embodiment of the invention or the technical proposal in the existing technology, to embodiment or will show below
There is attached drawing needed in technical description to be briefly described, it should be apparent that, the accompanying drawings in the following description is only this
The embodiment of invention for those of ordinary skill in the art without creative efforts, can also basis
The attached drawing of offer obtains other attached drawings.
Fig. 1 is the existing believable Internet of Things edge calculations configuration diagram that computing mechanism is trusted based on cloud platform；
Fig. 2 is a kind of signaling diagram of IoT edge device method for evaluating trust provided in an embodiment of the present invention；
Fig. 3 is a kind of trust value prediction principle figure provided in an embodiment of the present invention；
Fig. 4 is a kind of edge device d provided in an embodiment of the present invention1、d2、d3、d4Edge device interacts schematic diagram；
Fig. 5 is a kind of structural block diagram of IoT edge device trust evaluation device provided in an embodiment of the present invention；
Fig. 6 is a kind of structural schematic diagram of edge proxy server provided in an embodiment of the present invention；
Fig. 7 is a kind of structural block diagram of IoT edge device trust evaluation system provided in an embodiment of the present invention.
Specific embodiment
Core of the invention is to provide a kind of IoT edge device method for evaluating trust, and this method can believe edge device
Appoint the detection of value to judge and be modified by penal system to its trust value to the trust value from non-trusted device, is come with this
The malicious acts such as spurious feedback, malicious attack and leaguing together for some evil end are coped with, to improve the accuracy of global trust and the peace of system
Full reliability；Another core of the invention is to provide a kind of IoT edge device trust evaluation device, a kind of edge proxy server
And a kind of IoT edge device trust evaluation system.
In order to make the object, technical scheme and advantages of the embodiment of the invention clearer, below in conjunction with the embodiment of the present invention
In attached drawing, technical scheme in the embodiment of the invention is clearly and completely described, it is clear that described embodiment is
A part of the embodiment of the present invention, instead of all the embodiments.Based on the embodiments of the present invention, those of ordinary skill in the art
Every other embodiment obtained without making creative work, shall fall within the protection scope of the present invention.
Fig. 1 is the existing believable Internet of Things edge calculations configuration diagram that computing mechanism is trusted based on cloud platform, this
Structure mainly includes three layers: network layer, Agent layer and mechanical floor.Such as equipment DiTo its proxy requests DjTrust value, the trust value
Mainly from equipment DiWith equipment DjBetween directly trust and act on behalf of by other multiple equipments about DjTrust value gathered
Feedback trust value after conjunction.DiDirect trust is trusted into fusion calculation with feedback and obtains DjGlobal trust.This trust computer
System can understand the trust situation of interactive device before interacting, and reduce to validity network risks, it is with higher can
By property.
But due to security risks various in Internet of Things and attack, Internet of Things edge device is just suffering from spurious feedback, is disliking
The various malicious acts such as meaning attack and leaguing together for some evil end, the direct trust of equipment room and agency receive from mechanical floor other equipment
All feedbacks there may be false trust value, affect the calculating of equipment global trust.The edge IoT provided by the present application is set
Standby method for evaluating trust can judge the detection of edge device trust value and to the trust value from non-trusted device by punishing
It penalizes system to be modified its trust value, the malicious acts such as spurious feedback, malicious attack and leaguing together for some evil end is coped with this, thus
Improve the accuracy of global trust and the security reliability of system.
The existing framework of Internet of Things framework is essentially identical in the application, is introduced in the present embodiment with framework shown in Fig. 1, figure
2 be a kind of signaling diagram of IoT edge device method for evaluating trust provided in this embodiment；This method specifically includes that
Step s111, request originator sends to edge proxy server and requests the trust value of the first equipment.
Wherein, request originator and the first equipment are edge device.It needs to carry out with the first equipment in request originator
When interaction or when request originator needs to screen interactive device, it is desirable to obtain the trust of edge device
Degree sends to affiliated edge proxy server and requests the trust value of the equipment.
Trust value to the first equipment mainly includes that other equipment initiate the feedback trust value of the first equipment and request
The global trust value to the first equipment can be obtained to the direct trust value of the first equipment in side after fusion.
Step s121, edge proxy server filters out the edge device currently interacted with the first equipment, obtains second and sets
It is standby.
It is of course also possible to consider influence of the equipment once interacted in the past with the first equipment to the first equipment trust value,
The calculating that certain weight carries out the first equipment global trust value is distributed to the trust value generated in previous interaction, in the present embodiment
Without limitation to this kind of situation.
Step s121, edge proxy server sends the instruction of the first equipment trust value computing to the second equipment.
Step s131, the second equipment is obtained according to the trust value calculated with the interaction scenario of the first equipment to the first equipment
Practical trust value.
Each second equipment upon receipt of the instructions according to distance ought for the previous period in the interaction scenario of the second equipment
The case where completing task to the first equipment carries out the calculating of direct trust value to the second equipment.
To the calculating process of direct trust value, (including each second equipment is straight to the first equipment without limitation in the present embodiment
Connect the calculating of the calculating and request originator of trust value to the first equipment direct trust value), it is referred to existing direct letter
Appoint the calculation method of value.
Wherein it is preferred to which other side completes request task ability just in two equipment interactive processes in available preset time
The sum of face scoring and the sum negatively to score；Wherein, front scoring and negative scoring are interaction both sides to the clothes of other side
Business quality score obtains；The sum of statistics front scoring accounts for the ratio of front scoring and the sum negatively to score, obtains directly
Trust value.
Specifically, it is assumed thatFor the equipment d within the Δ t time1To d2Request task ability front is completed to comment
The sum divided,For the equipment d within the Δ t time1To d2The sum that request task ability negatively scores is completed, directly
It connects trust value and is referred to following formula to calculate, direct trust value:
It is only introduced by taking the calculation of above-mentioned direct trust value as an example herein, other calculations are not done superfluous herein
It states.
Step s132, the second equipment returns to practical trust value to edge proxy server.
Step s123, edge proxy server predicts the second equipment to the letter of the first equipment according to the history trust value of storage
Appoint value, obtains prediction trust value.
As the network attack frequency in Internet of Things edge device environment is continuously increased, edge device may maliciously be set
Standby attack, trust value can change, and be likely to appear in during carrying out service collaboration non-trusted device for false letter
Value is appointed to be supplied to the agency of marginal layer, it, can be final if do not judged these trust values from mechanical floor in Agent layer
Cause to obtain an insecure global trust.
There is temporal correlation due to trusting, the Internet of Things edge calculations architecture of the trust computing mechanism based on feedback
In the case where, to avoid maliciously evaluating caused by the malicious acts such as spurious feedback, malicious attack and leaguing together for some evil end, in the present embodiment
The trust predicted value in current period is obtained according to trust value of the equipment within the time in the past period using time window method, it will
Obtained practical trust value is compared with the difference for trusting predicted value with the error threshold of setting, judges the process interacted
Whether middle trust value is credible, realizes that the detection to edge device trust value judges, if error is larger, proves that the equipment can not
Letter is modified the trust value of non-trusted device by carrying out penal system to its trust value, false anti-to cope with this
The malicious acts such as feedback, malicious attack and leaguing together for some evil end, improve the safety and reliability of system.
Due to the temporal correlation of trust, the history in time cycle that several can be taken nearest apart from current period is believed
Appoint value to carry out the prediction of trust value, detailed process for carrying out trust value prediction according to the history trust value of acquisition is not limited at this
It is fixed, wherein preferably, the second equipment in preset period of time span can be filtered out, the trust value of the first equipment is gone through
History trust value；The average value for calculating history trust value, using the average value being calculated as prediction trust value.Average value both can be with
Reflect the current conventional trust value situation of the equipment, if certain trust value and average value difference are larger, occur it is abnormal can
Energy property is larger, can be using average value as judgment criteria, and the calculating process of average value is simple and quick.It is of course also possible to select
The calculating process of predicted value is carried out with other calculations, for example will be gone through according to the weight become larger with what interval moved closer to
History trust value is multiplied, and weight summation is 1 etc., without limitation to the calculating process of specific prediction trust value at this, can be voluntarily
Setting.
It is introduced by taking average value as an example herein, trust value prediction principle figure is as shown in Figure 3.
Indicate t moment equipment diTo djTrust predicted value.
Indicate t moment equipment diTo djPractical trust value.
If time cycle span be n (value of n generally takes distance current nearest several moment, for example, n can take 3), when
Predict the trust value of t momentWhen, t-1, t-2 are extracted ... the trust value at ..t-n momentIt calculates
Step s124, the difference of the practical trust value that edge proxy server calculating receives and corresponding prediction trust value
Value.
Step s125, edge proxy server incites somebody to action difference compared with error threshold carries out size, and according to comparison result
Direct trust value is divided into abnormal trust value and normal trust value.
Practical trust value is compared with the difference of prediction trust value with the error threshold of setting, is reliably trusted
The degree of reliability of global trust value can be improved in value, if difference is greater than error threshold, determines the corresponding direct trust value of the difference
For abnormal trust value；If certain difference is not more than error threshold, determine that the corresponding direct trust value of the difference is normal trust value.
Abnormal trust value indicates that the trust value recorded in the trust value and history is quite different, may deposit in transmission process
The malicious acts such as spurious feedback, malicious attack and leaguing together for some evil end are being avoided, are needing to recycle it after being modified the trust value
Carry out the calculating of feedback trust value.Normal trust value indicate the trust value and history strongly in trust value it is very nearly the same, judgement
It is credible, the calculating of feedback trust value can be directly carried out using the trust value.
Without limitation, error threshold is set after being counted according to the interaction scenario of more equipment for the setting of specific error threshold
Surely fixed value can also carry out corresponding setting of floating according to the situation of change of abutted equipment trust value, can be with distinct device
Unified error threshold is set, corresponding error threshold (such as the letter in statistics a period of time is set also for different equipment
The situation of change of value is appointed to carry out the setting of error threshold) etc., it can set automatically according to demand.
Wherein it is preferred to whenIndicate equipment diWith djBetween direct trust value in the Δ t time, when n is
Between period span when, can according to threshold calculations formula carry out error threshold calculating, obtain error threshold；
Wherein, threshold calculations formula specifically:
Determining error threshold is more bonded the situation of change of practical trust value through the above way, avoids the feelings of erroneous detection as far as possible
Condition improves the extreme accuracy of global trust value.
Step s126, edge proxy server is modified abnormal trust value by penalty mechanism, obtains revised
Trust value.
The practical trust value that will be currently receivedWith corresponding trust predicted valueDifference and setting
Error threshold ε be compared, judge whether trust value credible, if the trust value of non-trusted device, pass through and carry out punishment system
Degree carries out feedback trust again polymerization after being modified to trust value calculates.
Without limitation to the modification method of abnormal trust value, it can be set and reduce preset value (ratio on obtained trust value
As subtracted 10 to trust value once detect as abnormal trust value), or can also be according to the trust degree of the equipment in the past
And this practical trust value is corresponding with the progress of the difference of predicted value corrects that (for example setting is to the equipment trust value-reality letter
Appoint difference/2 of value with predicted value)
Wherein it is preferred to whenFor the equipment d within the Δ t timeiTo djIt is negative to complete request task ability
The sum of scoring,Indicate equipment diWith djBetween direct trust value in the Δ t time when, can be public according to amendment
Formula is modified abnormal trust value, obtains revised trust value；
Wherein, correction formula specifically:Wherein β is modifying factor,
Through testing, the intensity of anomaly of trust value is considered not only by above-mentioned correcting mode, and according to previous equipment
Trust degree is modified, if phenomenon of playing tricks occurs in equipment in previous interaction, trust value reduction degree is more, to avoid not
The selection of trusted devices.
Step s127, revised trust value polymerize by edge proxy server with normal trust value, is fed back
Trust value.
The polymerization methods of feedback trust value are referred to existing polymerization methods, wherein preferably, can pass through comentropy
Theory polymerization is calculated feedback and trusts, and each trust value can be fully taken into account in such a way that information entropy theory is polymerize
Significance level realizes the efficient statistics of equipment trusted situations.
For example, edge proxy server b1, b1By equipment d3, d4With equipment d2The direct trust value that interaction generates
WithFeedback directly is calculated by information entropy theory polymerization to trust.Feedback is trustedCalculating can
Referring to following formula:
Wherein WiFor weight factor, EiFor the comentropy of trust value.
Step s128, edge proxy server feeds back to request originator for trust value is fed back.
Step s112, request originator will feed back trust value and the direct trust value itself the first equipment evaluation obtained into
Row fusion calculation obtains the global trust value of the first equipment.
Practical trust value fusion direct trust value and feedback trust value, can the corresponding situation of task to equipment carry out it is complete
Face evaluation, specifically the fusion process of trust value is without limitation, it is preferable that can be direct trust value and feedback trust value difference
Certain weight is distributed, by trust value and corresponding multiplied by weight, obtains global trust.Wherein the specific distribution of weight does not limit
It is fixed, it can be set according to the trust degree before each equipment, for example equipment is completed request task ability height and then set greatly
Weight, it is low, set small weight etc.；In addition it is interacted before direct trust value reflection trust value requesting party and trust value Requested Party
The trusted situations of process can set the weight of direct trust value slightly larger than feedback trust value.Preferably, it is weighed using the former
The setting of weight can more reasonably reflect distinct device trust degree, can when determining weight according to the trusting degree of distinct device
To obtain more accurately merging trust value
The determination method of weight factor specifically: whenFor the equipment d within the Δ t timeiTo djComplete request
It when the sum that task ability negatively scores, is calculated according to factor calculation formula, using obtained data as direct weight；Meter
The difference for calculating 1 with direct weight, using obtained result as feedback weight；Wherein, factor calculation formula specifically:
Herein with equipment d1To directly it trustTrust with feedbackFusion calculation is carried out, is obtained
d2Global trustFor.The calculating of global trust value can be with are as follows:Wherein ω is weight factor,For the equipment d within the Δ t timeiTo djIt is negative to complete request task ability
The sum of face scoring.It is only introduced by taking above-mentioned data fusion method as an example herein, other data fusion methods can refer to
It gives an account of and continues.
Through testing, under the conditions of using identical architectural framework, trust value is carried out using method provided in this embodiment
Corresponding error threshold is predicted and be arranged, can be improved the accuracy of global trust, makes the service between Internet of Things edge device
It cooperates relatively reliable.
Based on above-mentioned introduction, IoT edge device method for evaluating trust provided in this embodiment, based on the trust by feedback
Under the Internet of Things edge calculations architecture of calculation mechanism, the letter using time window method according to equipment within the time in the past period
Appoint value to obtain the prediction trust value in current period, there is temporal correlation due to trusting, prediction trust value is to a certain extent
The possible range for having delimited current trust value, by the mistake of the difference and setting of the practical trust value being currently received and prediction trust value
Poor threshold value is compared, and judges whether the trust value of interaction in information exchange is credible, if the trust value of non-trusted device, passes through
It carries out penal system to be modified trust value, carries out feedback trust again to realize the calibration to equipment is distrusted, after amendment
Polymerization calculates, and an available more structurally sound global trust value avoids spurious feedback, malicious attack and leaguing together for some evil end etc.
It is maliciously evaluated caused by malicious act, the safety of the reliability and system of global trust can be improved.In addition, the present embodiment mentions
The trust that the IoT edge device method for evaluating trust of confession can also be applied in recommender system calculates, and realizes accurately pushing away for equipment
It recommends, promotes working efficiency.
To deepen the understanding to IoT edge device method for evaluating trust provided by the invention, it is assumed that edge device includes d1、
d2、d3、d4、d5, wherein equipment d1Go for equipment d2Global trust value, d3With d4Currently and d2In interaction mode, d5
Currently and d2No interactions, the present embodiment are introduced overall flow by taking above situation as an example, edge device d1、d2、d3、d4Edge
Equipment interaction schematic diagram as shown in figure 4, trust evaluation process master and want the following steps are included:
Equipment d1Go for equipment d2Global trust value, to its edge proxy server send request.
Edge proxy server is screened after receiving request by facility information, finds d3、d4It is being in and equipment d2's
Interaction mode.
Equipment d1And d3、d4According to d2The interaction scenario of progress calculates separately the direct trust value respectively generatedEquipment d1、d3、d4The trust value is fed back into edge proxy server, this
When the practical trust value that receives of edge proxy server be exactly equipment d1、d3、d4To d2Direct trust value
Edge proxy server is according to equipment d3、d4To d2The history that feedback is come is trustedWherein n is time cycle span, point
It does not calculate respectively about equipment d2Prediction trust value
The practical trust value that will be receivedIt calculates separately and respective prediction trust valueDifference, the error threshold with settingIt carries out
Compare, judges whether the practical trust value received is believable trust value with this, if not within the scope of error threshold, to this
The trust value of equipment is modified.The modification rule of trust value are as follows:
Revised trust value:Wherein β is modifying factor,
For the sum negatively to score within the Δ t time.Wherein [3,4] i=, i ∈ Z, j=2.
Edge proxy server is by revised trust valueWherein [3,4] i=, i ∈ Z.Carry out polymerization meter
Calculation obtains feedback and trustsAnd it is sent to equipment d1, and it is mainly equipment d that the feedback, which is trusted,3、d4To d2Trust value.
Equipment d1The feedback from edge proxy server will be received to trustWith oneself about equipment d2It is straight
Connect trust valueFusion calculation is carried out, equipment d is obtained2Global trust value
As the network attack frequency in Internet of Things edge device environment is continuously increased, edge device may maliciously be set
Standby attack, trust value can change.False trust value is supplied to by non-trusted device during carrying out service collaboration
The agency of marginal layer.If do not judged these trust values from mechanical floor in Agent layer, can eventually lead to obtain one
A insecure global trust.But by the way that the error threshold of the difference and setting of practical trust value and prediction trust value is carried out
Compare, obtains reliable trust value.Global trust that is last and combining directly trust calculating equipment.
The present embodiment carries out trust value according to the history intersection record in the time in the past period, using time window method
The trust value actually obtained is compared by prediction, the edge proxy server of Agent layer with the trust value of prediction, passes through calculating
Whether whether the absolute difference of two trust values is greater than the error threshold of setting credible to judge the trust value, if being judged as not
Credible equipment is then modified its trust value by penal system.A more structurally sound global trust is calculated with this
Value.
Referring to FIG. 5, Fig. 5 is a kind of structural block diagram of IoT edge device trust evaluation device provided in this embodiment；It can
To include: edge device screening unit 510, computations transmission unit 520, trust predicting unit 530, difference computational unit
540, difference comparsion unit 550, abnormal amending unit 560, feedback trust polymerized unit 570 and feedback trusts transmission unit
580.IoT edge device trust evaluation device provided in this embodiment can be mutual with above-mentioned IoT edge device method for evaluating trust
Control.
Wherein, it when edge device screening unit 510 is mainly used for receiving the trust value request to the first equipment, filters out
The edge device currently interacted with the first equipment obtains the second equipment；
Computations transmission unit 520 is mainly used for sending the instruction of the first equipment trust value computing to the second equipment；
Trust predicting unit 530 to be mainly used for predicting the second equipment to the letter of the first equipment according to the history trust value of storage
Appoint value, obtains prediction trust value；
Difference computational unit 540 is mainly used for calculating the practical trust value that receives and the corresponding difference for predicting trust value
Value；
Difference comparsion unit 550 is mainly used for difference compared with error threshold carries out size, and will according to comparison result
Direct trust value is divided into abnormal trust value and normal trust value；
Abnormal amending unit 560 is mainly used for being modified abnormal trust value by penalty mechanism, obtains revised
Trust value；
Feedback trusts polymerized unit 570 and is mainly used for for revised trust value polymerizeing with normal trust value, obtains
Feed back trust value；
Feedback, which trusts transmission unit 580 and is mainly used for that trust value will be fed back, feeds back to request originator, to request to initiate
Side will feed back trust value and itself carries out fusion calculation to the direct trust value that the first equipment evaluation obtains, and obtain the first equipment
Global trust value.
IoT edge device trust evaluation device provided in this embodiment can judge the detection of edge device trust value,
And the trust value from non-trusted device is modified its trust value by penal system, with this come cope with spurious feedback,
The malicious acts such as malicious attack and leaguing together for some evil end, to improve the accuracy of global trust and the security reliability of system.
Wherein it is preferred to which trusting predicting unit in the present embodiment can specifically include:
Trust value screens subelement, for filtering out in preset period of time span the second equipment to the trust of the first equipment
Value, obtains history trust value；
Mean value calculation subelement, for calculating the average value of history trust value, using the average value being calculated as pre-
Survey trust value.
Preferably, the error threshold computing unit in IoT edge device trust evaluation device specifically can be used for: whenIndicate equipment diWith djBetween direct trust value in the Δ t time, when n is time cycle span, according to threshold value meter
The calculating that formula carries out error threshold is calculated, error threshold is obtained；Wherein, threshold calculations formula specifically:
Preferably, abnormal amending unit specifically can be used for: whenFor the equipment d within the Δ t timeiTo dj
The sum that request task ability negatively scores is completed,Indicate equipment diWith djBetween direct trust in the Δ t time
When value, abnormal trust value is modified according to correction formula, obtains revised trust value；Wherein, correction formula specifically:Wherein β is modifying factor,
The present embodiment provides a kind of edge proxy servers, comprising: memory and processor.
Wherein, memory is for storing program；
It realizes when processor is for executing program such as the step of above-mentioned IoT edge device method for evaluating trust, can specifically join
According to the introduction in above-described embodiment about IoT edge device method for evaluating trust.
Referring to FIG. 6, being a kind of structural schematic diagram of edge proxy server provided in this embodiment, edge proxies clothes
Business device can generate bigger difference because configuration or performance are different, may include one or more processors (central
Processing units, CPU) 322 (for example, one or more processors) and memory 332, one or more
Store the storage medium 330 (such as one or more mass memory units) of application program 342 or data 344.Wherein, it deposits
Reservoir 332 and storage medium 330 can be of short duration storage or persistent storage.The program for being stored in storage medium 330 may include
One or more modules (diagram does not mark), each module may include to the series of instructions behaviour in data processing equipment
Make.Further, central processing unit 322 can be set to communicate with storage medium 330, in edge proxy server 301
Execute the series of instructions operation in storage medium 330.
Edge proxy server 301 can also include one or more power supplys 326, one or more it is wired or
Radio network interface 350, one or more input/output interfaces 358, and/or, one or more operating systems
341, such as Windows ServerTM, Mac OS XTM, UnixTM, LinuxTM, FreeBSDTM etc..
Step in IoT edge device method for evaluating trust described in above figure 1 can be by edge proxy server
Structure is realized.
Referring to FIG. 7, Fig. 7 is a kind of structural block diagram of IoT edge device trust evaluation system provided in this embodiment；It should
System specifically includes that request originator 710, edge proxy server 720 and the second equipment 730.
Request originator 710 and the second equipment 730 are the edge device under edge proxy server 720 controls, if
Standby type can be such as mobile phone, computer etc. without limitation.
Wherein, request originator 710 is mainly used for sending to edge proxy server and request the trust value of the first equipment；
According to the trust value calculated with the interaction scenario of itself the first equipment to the first equipment, the direct trust to the first equipment is obtained
Value；When receiving feedback trust value, feedback trust value and direct trust value are subjected to fusion calculation, obtain the entirety of the first equipment
Trust value.
Any one edge device that above-mentioned function may be implemented can be used as request originator, can be to will assist
The edge device of work carries out trust judgement, judges whether credible.
In request originator 710 carry out fusion calculation module be specifically used for: obtain it is preset it is direct trust and
Feedback trusts corresponding weight factor, obtains direct weight and feedback weight；To the product of direct trust value and direct weight
The product value of value and feedback trust value and feedback weight is summed, and global trust value is obtained.
Wherein, weight factor can be determined by weighting factor determination module, and specifically, weighting factor determination module is used
In: whenFor the equipment d within the Δ t timeiTo djWhen completing the sum that request task ability negatively scores, according to
Factor calculation formula is calculated, using obtained data as direct weight；The difference for calculating 1 with direct weight, by what is obtained
As a result it is used as feedback weight；Wherein, factor calculation formula specifically:
When edge proxy server 720 is mainly used for receiving the trust value request to the first equipment, filter out currently with
The edge device of first equipment interaction, obtains the second equipment；The instruction of the first equipment trust value computing is sent to the second equipment；According to
The history trust value of storage predicts that the second equipment to the trust value of the first equipment, obtains prediction trust value；Calculate the reality received
The difference of border trust value and corresponding prediction trust value；To difference compared with error threshold carries out size, and according to comparison result
Direct trust value is divided into abnormal trust value and normal trust value；Abnormal trust value is modified by penalty mechanism,
Obtain revised trust value；Revised trust value is polymerize with normal trust value, obtains feedback trust value；It will feedback
Trust value feeds back to request originator；
When second equipment 730 is mainly used for receiving the instruction of the first equipment trust value computing, according to the friendship with the first equipment
Mutual situation calculates the trust value to the first equipment, obtains practical trust value；Practical trust value is returned to edge proxy server.
Wherein, the computing module of the second equipment 730 and the direct trust value in request originator 710 can specifically be used
In: it obtains in preset time other side in two equipment interactive processes and completes the sum of request task ability front scoring and negatively comment
The sum divided；Wherein, front scoring and negative scoring score to obtain for interaction both sides to the service quality of other side；Statistics front
The sum of scoring accounts for the ratio of front scoring and the sum negatively to score, obtains direct trust value.
Specifically, the process that three carries out information exchange in system is referred to the corresponding specific embodiment of Fig. 2, herein
It repeats no more.
IoT edge device trust evaluation system provided in this embodiment can judge the detection of edge device trust value,
And the trust value from non-trusted device is modified its trust value by penal system, with this come cope with spurious feedback,
The malicious acts such as malicious attack and leaguing together for some evil end, to improve the accuracy of global trust and the security reliability of system.
Each embodiment is described in a progressive manner in specification, the highlights of each of the examples are with other realities
The difference of example is applied, the same or similar parts in each embodiment may refer to each other.For device disclosed in embodiment
Speech, since it is corresponded to the methods disclosed in the examples, so being described relatively simple, related place is referring to method part illustration
?.
Professional further appreciates that, unit described in conjunction with the examples disclosed in the embodiments of the present disclosure
And algorithm steps, can be realized with electronic hardware, computer software, or a combination of the two, in order to clearly demonstrate hardware and
The interchangeability of software generally describes each exemplary composition and step according to function in the above description.These
Function is implemented in hardware or software actually, the specific application and design constraint depending on technical solution.Profession
Technical staff can use different methods to achieve the described function each specific application, but this realization is not answered
Think beyond the scope of this invention.
The step of method described in conjunction with the examples disclosed in this document or algorithm, can directly be held with hardware, processor
The combination of capable software module or the two is implemented.Software module can be placed in random access memory (RAM), memory, read-only deposit
Reservoir (ROM), electrically programmable ROM, electrically erasable ROM, register, hard disk, moveable magnetic disc, CD-ROM or technology
In any other form of storage medium well known in field.
Above to IoT edge device method for evaluating trust, device, system and edge proxy server provided by the present invention
It is described in detail.Used herein a specific example illustrates the principle and implementation of the invention, the above reality
The explanation for applying example is merely used to help understand method and its core concept of the invention.It should be pointed out that for the art
For those of ordinary skill, without departing from the principle of the present invention, can with several improvements and modifications are made to the present invention,
These improvements and modifications also fall within the scope of protection of the claims of the present invention.
Claims (10)
1. a kind of IoT edge device method for evaluating trust characterized by comprising
When edge proxy server is received to the request of the trust value of the first equipment, filters out and current interacted with first equipment
Edge device, obtain the second equipment；
The instruction of the first equipment trust value computing is sent to second equipment；
Predict that second equipment to the trust value of first equipment, obtains prediction and trusts according to the history trust value of storage
Value；
The difference of the practical trust value that calculating receives and corresponding prediction trust value；
To the difference compared with error threshold carries out size, and the direct trust value is divided by exception according to comparison result
Trust value and normal trust value；
The abnormal trust value is modified by penalty mechanism, obtains revised trust value；
The revised trust value is polymerize with the normal trust value, obtains feedback trust value；
The feedback trust value is fed back into request originator, so that the request originator is by the feedback trust value and itself
Fusion calculation is carried out to the direct trust value that first equipment evaluation obtains, obtains the global trust value of first equipment.
2. IoT edge device method for evaluating trust as described in claim 1, which is characterized in that trusted according to the history of storage
Value predicts second equipment to the trust value of first equipment, comprising:
It filters out second equipment in preset period of time span and history trust is obtained to the trust value of first equipment
Value；
The average value for calculating the history trust value, using the average value being calculated as prediction trust value.
3. IoT edge device method for evaluating trust as described in claim 1, which is characterized in that the meter of the direct trust value
Calculation method includes:
It obtains in preset time other side in two equipment interactive processes and completes the sum of request task ability front scoring and negative
The sum of scoring；Wherein, the front scoring and the negative scoring score to the service quality of other side for interaction both sides
It arrives；
The sum for counting the front scoring accounts for the ratio of the front scoring and the sum negatively to score, obtains directly
Trust value.
4. IoT edge device method for evaluating trust as described in claim 1, which is characterized in that the calculating of the error threshold
Method includes:
WhenIndicate equipment diWith djBetween direct trust value in the Δ t time, when n is time cycle span, according to
Threshold calculations formula carries out the calculating of error threshold, obtains error threshold；
Wherein, the threshold calculations formula specifically:
5. IoT edge device method for evaluating trust as described in claim 1, which is characterized in that request originator will be described anti-
Feedback trust value and the direct trust value progress fusion calculation itself first equipment evaluation obtained, comprising:
It obtains preset direct trust and feedback trusts corresponding weight factor, obtain direct weight and feedback power
Weight；
Product value and the feedback trust value and the feedback weight to the direct trust value and the direct weight
Product value summation, obtains global trust value.
6. IoT edge device method for evaluating trust as claimed in claim 5, which is characterized in that the determination of the weight factor
Method includes:
WhenFor the equipment d within the Δ t timeiTo djWhen completing the sum that request task ability negatively scores, according to
Factor calculation formula is calculated, using obtained data as direct weight；
The difference for calculating 1 with the direct weight, using obtained result as feedback weight；
Wherein, the factor calculation formula specifically:
7. IoT edge device method for evaluating trust as described in claim 1, which is characterized in that by penalty mechanism to described
Abnormal trust value is modified, comprising:
WhenFor the equipment d within the Δ t timeiTo djThe sum that request task ability negatively scores is completed,Indicate equipment diWith djBetween direct trust value in the Δ t time when, according to correction formula to abnormal trust value into
Row amendment, obtains revised trust value；
Wherein, the correction formula specifically:Wherein β is modifying factor,
8. a kind of IoT edge device trust evaluation device characterized by comprising
Edge device screening unit when for receiving to the request of the trust value of the first equipment, filters out current with described first
The edge device of equipment interaction, obtains the second equipment；
Computations transmission unit, for sending the instruction of the first equipment trust value computing to second equipment；
Trust predicting unit, predicts second equipment to the trust of first equipment for the history trust value according to storage
Value obtains prediction trust value；
Difference computational unit, for calculating the difference of the practical trust value received with corresponding prediction trust value；
Difference comparsion unit is used for the difference compared with error threshold carries out size, and will be described straight according to comparison result
It connects trust value and is divided into abnormal trust value and normal trust value；
Abnormal amending unit obtains revised trust value for being modified by penalty mechanism to the abnormal trust value；
Feedback trusts polymerized unit, for the revised trust value to polymerize with the normal trust value, obtains anti-
Present trust value；
Feedback trusts transmission unit, for the feedback trust value to be fed back to request originator, so as to the request originator
By the feedback trust value and itself fusion calculation is carried out to the direct trust value that first equipment evaluation obtains, obtained described
The global trust value of first equipment.
9. a kind of edge proxy server characterized by comprising
Memory, for storing program；
Processor realizes the IoT edge device trust evaluation as described in any one of claim 1 to 7 when for executing described program
The step of method.
10. a kind of IoT edge device trust evaluation system characterized by comprising
Request originator requests the trust value of the first equipment for sending to edge proxy server；According to itself first
The interaction scenario of equipment calculates the trust value to the first equipment, obtains the direct trust value to the first equipment；Receive feedback letter
When appointing value, the feedback trust value and the direct trust value are subjected to fusion calculation, obtain the whole letter of first equipment
Appoint value；
Edge proxy server when for receiving to the request of the trust value of the first equipment, being filtered out and current being set with described first
The edge device of standby interaction, obtains the second equipment；The instruction of the first equipment trust value computing is sent to second equipment；According to depositing
The history trust value of storage predicts that second equipment to the trust value of first equipment, obtains prediction trust value；It calculates and receives
The difference of the practical trust value arrived and corresponding prediction trust value；To the difference compared with error threshold carries out size, and root
The direct trust value is divided into abnormal trust value and normal trust value according to comparison result；By penalty mechanism to described different
Normal trust value is modified, and obtains revised trust value；The revised trust value and the normal trust value are carried out
Polymerization obtains feedback trust value；The feedback trust value is fed back into request originator；
Second equipment, when for receiving the first equipment trust value computing instruction, according to the interaction scenario with the first equipment
The trust value to the first equipment is calculated, practical trust value is obtained；The practical trust value is returned to the edge proxy server.
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