CN114091953A - Credibility evaluation method and system based on heterogeneous block chain - Google Patents

Credibility evaluation method and system based on heterogeneous block chain Download PDF

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CN114091953A
CN114091953A CN202111432613.9A CN202111432613A CN114091953A CN 114091953 A CN114091953 A CN 114091953A CN 202111432613 A CN202111432613 A CN 202111432613A CN 114091953 A CN114091953 A CN 114091953A
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叶卿怡
刘耀东
冯霞
孙国
黄龙霞
余春堂
陈向益
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JIANGSU PRODUCTIVITY PROMOTION CENTER
Jiangsu University
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Abstract

The invention discloses a credible evaluation method and system based on a heterogeneous block chain. The invention ensures the credibility of the evaluation result and the fairness of the evaluation process through the storage mode of block chain decentralized and the characteristic that data can not be tampered. The system calculates the objectivity value of each evaluator by adopting a clustering-based method according to the historical evaluation behavior and data of each evaluator, sets dual thresholds from the aspects of objectivity and participation degree before the evaluators participate in evaluation, and carries out qualification authentication on the objectivity value and the participation degree, thereby realizing constraint on the evaluation of the evaluators and improving the objectivity of the evaluation content and the credibility of the evaluation result.

Description

Credibility evaluation method and system based on heterogeneous block chain
Technical Field
The invention relates to a block chain technology, in particular to a credibility evaluation method and system based on a heterogeneous block chain.
Background
The evaluation system is an indispensable part of the present society, and is the most direct and effective measurement method for individual credibility based on group intelligence in the society, so the evaluation system plays more and more important roles. However, due to the lack of support of the evaluation technology, many evaluation systems are deployed on a central server nowadays, and the evaluation processes are processed in a centralized manner, so that such systems are easy to attack and data are easy to tamper, and do not have sufficient reliability and security. In addition, most evaluation systems are established on the premise that "no difference exists among evaluation groups", and behaviors such as malicious poor evaluation and blind evaluation cause large deviation of evaluation results, so that the evaluation results do not have enough reliability.
In recent years, a new opportunity is brought for solving the problems by the appearance of a block chain technology, and a block chain is a comprehensive application of a block chain structure, an encryption algorithm, a consensus mechanism, an intelligent contract and the like, and has the characteristics of being difficult to tamper, counterfeit and trace. A credible evaluation system is established based on the heterogeneous block chain, so that the centralization problem existing in the traditional evaluation system can be solved by utilizing the characteristics of the credible evaluation system, and meanwhile, the public transparency of the evaluation process and the real credibility of the evaluation result are realized.
Although there are some applications and implementations of evaluation by using the block chain technology in the evaluation technology field, most of these evaluation systems do not fully consider the influence of the actual evaluation influencing factors on the result, and do not consider the objectivity and credibility of the evaluation made by the participants more, in terms of the transparency and openness of the evaluation process.
Disclosure of Invention
The purpose of the invention is as follows: in order to solve the problem of trust relationship between an evaluator and an evaluated person in the prior art, the invention provides a credibility evaluation method and a credibility evaluation system based on a heterogeneous block chain.
The technical scheme is as follows: the invention discloses a credible evaluation method based on a heterogeneous block chain, which comprises the following steps:
initializing a credible evaluation system, and defining all values related to evaluation events;
each evaluator E maintains a set of variables E, E ═ E (ID, OI, PI, Event, M), where ID is identity information, OI is an objective index of the evaluator, OI is an initial value t, PI is an participation index of the evaluator, PI is an initial value s, Event is an evaluation Event list in which the evaluator participates, and M is an evaluation information list given by the evaluator each participation;
an Event to be evaluated issued by an evaluation system maintains a set of variable events (E)ObjectP, α, β), in which EObjectThe evaluation object is P which is the evaluation participator involved in the evaluation, the participator participating in the evaluation is limited by P, alpha and beta are respectively an objective index threshold value and an participation index threshold value which are required to be reached by the participation evaluation, alpha<t and beta<s; meanwhile, an intelligent contract is deployed on the block chain, and all evaluators participate in evaluation by accessing the intelligent contract;
step (2), the evaluation participator uses the necessary identity attribute to apply for registering the evaluation system, the identity authentication module verifies and identifies the identity of the participator, if the verification and the identification are successful, the evaluation participator will register on the system, the system creates a digital ID for the corresponding evaluation participator and stores the user information in the system;
step (3), the system records the historical evaluation data of the evaluators and sends the historical evaluation data to an objectivity calculation module, the objectivity calculation module calculates the objective index of each evaluator, and the numerical value is updated and disclosed on a block chain after each evaluation is finished;
step (4), the system calls the deployed intelligent contract to release evaluation, sets an evaluation object and participants contained in the evaluation, then calculates the participation index of an evaluator, sets a dual threshold from the perspective of objectivity and participation of the evaluator to select an evaluator list with evaluation qualification, and the evaluator gives evaluation information according to the evaluation object and submits the evaluation information to the system;
and (5) verifying the validity of the evaluation information by the system, if the verification is successful, extracting the evaluation information and sending the evaluation information to the evaluation result calculation module, and calculating the final evaluation result by the evaluation result calculation module and disclosing the final evaluation result on the block chain.
On one hand, the invention realizes the tracking evaluation of an evaluator and restricts the evaluation randomness; and on the other hand, the appraised person is provided with the privacy information of the appraiser and evidence of historical appraisal conditions, so that the appraised person believes the appraisal qualification and the fairness of the appraisal of the appraiser.
Further, the credible evaluation system in the step (1) is based on a heterogeneous block chain, and includes a public chain and a federation chain, the public chain stores and discloses data, and the federation chain calculates relevant parameters and executes an evaluation process, wherein the specific process of data access is as follows:
after receiving the uploaded data, the credible evaluation system firstly obtains a unique data key through a key generation algorithm, encrypts the original data and calculates the hash value of the original data, and then calculates a data index;
after the steps are completed, storing the encrypted data embedded with the hash value in a cloud platform, and storing the data index, the hash value and the key in a public chain;
the cloud platform checks the validity of the transaction after receiving the transaction from the blockchain system, calculates the hash value of the received encrypted data, compares the hash value with the received hash value, and stores the encrypted data into the cloud platform if the hash value is matched with the received hash value;
when the alliance chain needs to request actual data in the evaluation process, the system firstly obtains encrypted data from the cloud platform through an index value stored on the public chain, verifies the hash value of the data to ensure that the data is not tampered, decrypts the data by using a key stored on the public chain, and returns the actual data to a data requester.
Here, the public chain, the alliance chain and the cloud platform are introduced to store and interact data, and in addition, the data security is further ensured through data-based encryption storage and a hash algorithm.
Further, the specific process of evaluating the identity authentication of the participants in the step (2) is as follows:
step (2.1), the evaluation participator provides own identity attribute Id when applying for registrationvThe identity authentication module identifies and verifies the identity attribute of the identity authentication module;
step (2.2), if the verification is successful, the system distributes a pair of public and private keys (pk, sk) to the system, the private keys are stored locally and uniquely identify participants, and the public keys are stored in the system;
step (2.3), based on the tuple information maintained by the evaluator in step (1), the system generates a unique digital Identity (ID) h (pk, Id) for the successfully registered evaluation participantsv) Finally, the evaluators who have successfully registered identify each other by ID.
Further, the objectivity calculating module in the step (3) calculates an objective index based on a clustering method, specifically:
in step (3.1), assuming that there are n evaluators in the primary evaluation, the evaluator is denoted as Ei(i ═ 1,2, …, n), giving evaluation information as a sample set Mi(i ═ 1,2, …, n), dividing k clusters C for the clustersj(j＝1,2,…,k)；
First, each cluster C is calculatedjMean vector of
Figure BDA0003380780610000031
Then use
Figure BDA0003380780610000032
Figure BDA0003380780610000033
Quantifying closeness of intra-cluster samples around cluster mean vectorThe larger the numerical value, the less objective the evaluator is to evaluate the time; u. ofjIs a cluster mean vector;
step (3.2) of defining a time decay function f (r) ═ ρm-rWhere ρ represents a time attenuation factor, m represents the number of evaluations participated in by an evaluator, and r represents the r-th evaluation participated in; 0<ρ<1,1≤r≤m；
Step (3.3), calculating the objective index of the evaluator in the system according to the time decay function f (r) and the objective degree of the evaluator in each evaluation event, and setting the evaluator EiIs marked as OIi；
Figure BDA0003380780610000034
Further, the specific steps of evaluating the qualification selection certification in the step (4) are as follows:
step (4.1), first, the participation indexes of all evaluators are calculated, and referring to step (3), the set formed by all evaluators in one evaluation is recorded as Ei(i-1, 2, …, n), each participant EiIs involved in
Figure BDA0003380780610000041
Where m represents the number of times the user participates in the evaluation,
Figure BDA0003380780610000043
representing a total number of times the rating was published in the system since the user registered;
step (4.2), the system calls objective indexes and participation indexes of all evaluators, and double thresholds are set: recording the objective index threshold value of an evaluator as alpha and the participation index threshold value of the evaluator as beta;
step (4.3), assuming that the set of evaluators who reach the objective index threshold α is Elα(1, 2, …, p), and the set of evaluators who reached the objective index threshold β is Elβ(l 1,2, …, t), the evaluator set qualified for the reference is Elα∪Elβ。
Further, the specific method for calculating the final evaluation result by the evaluation processing module in the step (5) is as follows:
step (5.1), the evaluation processing module obtains the evaluation data M given by each participant in the evaluationiThe evaluation data are divided into four categories according to the difference of participants, and n in the evaluators is recorded1The data set evaluated by the user is M1i，n2The data set evaluated by the bit owner is M2i，n3The dataset evaluated by the bit supervisor is M3i，n4The data set of evaluations made by the bit history user is M4i；
Step (5.2), according to different importance degrees of the evaluation information given by different participants, giving them different weights omegaq(0<q is less than or equal to 4), and the weight of the participator not participating in evaluation is 0;
assuming that the final evaluation result is R, the calculation formula is:
Figure BDA0003380780610000042
the invention also discloses a system for realizing the credibility evaluation method based on the heterogeneous block chain, which comprises a system initialization module, an identity authentication module, an objectivity calculation module, an evaluation qualification authentication module, an evaluation result calculation module and a data access module;
the system initialization module defines all parameters related to an evaluation process, gives initial values to partial variables (namely participation indexes and objective indexes of an evaluator), deploys intelligent contracts on a block chain, and the evaluator participates in evaluation by accessing the intelligent contracts;
the identity authentication module identifies and verifies the identity attribute provided by the evaluation participant when the evaluation participant applies for registration, if the verification is passed, the registration is successful, and the system creates an identity ID for the user and stores the identity information of the user;
the objectivity calculation module is used for digitizing the objective degree of evaluation made by each evaluator based on historical evaluation behaviors and evaluation data of the evaluators stored in the system, and outputting the objective degree as an objective index of the evaluators after carrying out standardization processing on the objective degree;
the assessment qualification authentication module introduces the participation index of the evaluator on the basis of considering the objective index of the evaluator, sets double thresholds to carry out qualification authentication on the evaluators, and finally outputs an evaluator list capable of participating in an assessment event;
the evaluation result calculation module processes and calculates the evaluation score of an evaluation object based on the evaluation data uploaded by an evaluator, outputs an evaluation result and discloses the evaluation result to a block chain;
the data access module defines the storage position of the data and the data acquisition authority, and is simultaneously responsible for fusing and butting the data among the identity verification module, the objectivity calculation module, the evaluation qualification certification module and the evaluation result calculation module.
Further, the credible evaluation system relates to an Evaluator and an evaluation object EObject；
The evaluation object EObjectThe body to be evaluated in the evaluation activity;
the Evaluator is an evaluation participant which participates in the evaluation event and gives evaluation information, and the evaluation participant comprises four participants which are respectively a User, an Owner Owner, a Supervisor Supervisor and a historical User Huser(ii) a Wherein the user is a user or an immediate participant of the evaluation object; the owner is the owner or manager of the evaluation object; the supervisor is a person or an organization supervising the evaluation object; the history user is a user who has used or participated in the evaluation object.
Has the advantages that: compared with the prior art, the invention has the following advantages:
(1) the problems of easy attack and single point failure of a centralized evaluation system are avoided
The credible evaluation system runs in a block chain, related data of the credible evaluation system is encrypted and stored in a cloud platform, and data hash and indexes are stored in a public chain, so that the data cannot be tampered; the distributed storage mode of the block chain can also avoid the problem of system failure caused by the failure of individual nodes.
(2) Certain constraints are applied to the behavior of evaluators in the system
The credible evaluation system can record the evaluation data of the evaluator each time, calculate the objective index and the participation index of the evaluator, and perform qualification examination on the evaluator before the evaluation starts according to the two indexes, so that the objectivity of the evaluation result can be improved.
(3) Improving the reliability of the final evaluation result
On one hand, the invention uses the structure of the heterogeneous block chain to store the data and execute the evaluation process, thereby ensuring that the data is not tampered and the evaluation process is transparently disclosed; on the other hand, the method not only carries out identity authentication on the evaluators added into the system, but also carries out qualification authentication on the evaluators participating in evaluation before each evaluation, thereby further ensuring the objective credibility of the evaluation content of the evaluators.
Drawings
FIG. 1 is a diagram of the system architecture of the present invention;
FIG. 2 is a flow chart of the system implementation of the present invention;
FIG. 3 is a flow chart of objective index calculation based on clustering in the present invention.
Detailed Description
The technical solution of the present invention is described in detail below, but the scope of the present invention is not limited to the embodiments.
The invention realizes a credible evaluation system based on the heterogeneous block chain, and guarantees the credibility of the evaluation result and the fairness of the evaluation process through the storage mode of the decentralized block chain and the characteristic that the data can not be tampered. The credibility evaluation system calculates the objectivity value of each evaluator by adopting a clustering-based method according to the historical evaluation behavior and data of each evaluator, sets dual thresholds from the aspects of objectivity and participation degree before the evaluators participate in evaluation, and carries out qualification authentication on the evaluators, thereby realizing the constraint of action of the evaluators and improving the objectivity of evaluation contents and the credibility of evaluation results.
Example 1
As shown in fig. 1, the trusted evaluation system of the present embodiment is divided into an application layer, a blockchain layer and a user layer.
The Evaluator (Evaluator) and the evaluation object (E) are involved in the user layerObject). Evaluation object (E)Object) The body to be evaluated in the evaluation activity; the Evaluator (Evaluator) is an evaluation participant which participates in the evaluation event and gives evaluation information, and the evaluation participant comprises four participants, namely a User (User), an Owner (Owner), a Supervisor (Supervisor) and a history User (H)user). Wherein the user is a user or an immediate participant of the evaluation object; the owner is the owner or manager of the evaluation object; the supervisor is a person or an organization supervising the evaluation object; the history user is a user who has used or participated in the evaluation object.
The application layer comprises a system initialization module, an identity authentication module, an objectivity calculation module, an evaluation qualification authentication module, an evaluation result calculation module and a data access module.
The system initialization module defines all parameters related to the evaluation process, gives initial values to partial variables, deploys intelligent contracts on the blockchain at the same time, and an evaluator participates in evaluation by accessing the intelligent contracts. The identity authentication module identifies and authenticates the identity attribute provided by the evaluation participant when the evaluation participant applies for registration, if the authentication is passed, the registration is successful, and the system creates an identity ID for the user and stores the identity information of the user. And the objectivity calculation module is used for digitizing the objective degree of the evaluation made by each evaluator based on the historical evaluation behavior and the evaluation data of the evaluator stored in the system, standardizing the objective degree and outputting the objective degree as an objective index of the evaluator. The assessment qualification authentication module introduces the participation degree index of the evaluator on the basis of considering the objective index of the evaluator, sets double thresholds to carry out qualification authentication on the evaluators, and finally outputs an evaluator list capable of participating in an assessment event. And the evaluation result calculation module processes and calculates the evaluation score of the evaluation object based on the evaluation data uploaded by the evaluator, outputs the evaluation result and discloses the evaluation result to the block chain. The data access module defines the storage position of the data and the data acquisition authority, and is simultaneously responsible for fusing and butting the data among the identity verification module, the objectivity calculation module, the evaluation qualification certification module and the evaluation result calculation module.
Example 2
As shown in fig. 2 and fig. 3, the credible evaluation method based on the heterogeneous block chain specifically includes the following processes:
(1) the rating system is initialized and all values associated with the rating events are defined. Each evaluator E in the system should maintain a set of variables, E ═ E (ID, OI, PI, Event, M), where ID is identity information, OI is an objective index of the evaluator, OI is an initial value, t, PI is an participation index of the evaluator, PI is an initial value, s, Event is an evaluation Event list in which the evaluator participates, and M is an evaluation information list given by the evaluator each time the evaluator participates. The system-issued evaluation events should maintain a set of variables: event ═ E (E)ObjectP, α, β), in which EObjectThe evaluation object, P is the participant included in the evaluation, and alpha and beta are the objective index threshold and the participation index threshold, respectively, which are required to be reached by the participation evaluation. And meanwhile, an intelligent contract is deployed on the blockchain, and all evaluators participate in evaluation by accessing the contract.
(1.1) the credible evaluation system based on the heterogeneous block chain is composed of a public chain and a alliance chain, wherein the public chain is used for storing and disclosing data; the federation chain is used for calculating related parameters and executing evaluation processes, wherein the specific process of data access is as follows:
after the system receives the uploaded data, a unique data key is obtained through a key generation algorithm, original data are encrypted, a hash value of the original data is calculated, and then a data index is calculated. After the steps are completed, the system stores the encrypted data embedded with the hash value in the cloud platform, and stores the index, the hash value and the key of the data in the public chain. And the cloud platform checks the validity of the transaction after receiving the transaction from the blockchain system, calculates the hash value of the received encrypted data, compares the hash value with the received hash value, and stores the encrypted data into the cloud platform if the hash value is matched with the received hash value. When the alliance chain needs to request actual data in the evaluation process, the system firstly obtains encrypted data from the cloud platform through an index value stored on the public chain, verifies the hash value of the data to ensure that the data is not tampered, decrypts the data by using a key stored on the public chain, and returns the actual data to a data requester.
(2) Evaluating the participant to apply for a registration system using the necessary identity attributes, the identity authentication module verifying and identifying the participant's identity, if the verification is successful, the participant registering on the system, the system creating a digital ID for the participant and storing the user information in the system.
(2.1) evaluation of participants in application for registration to provide their identity attribute IdvAnd the identity authentication module identifies and verifies the identity attribute of the identity authentication module.
(2.2) if the verification is successful, the system assigns a pair of public and private keys (pk, sk), the private key being stored locally and uniquely identifying the participant, and the public key being stored in the system.
(2.3) based on the tuple information maintained by the evaluator in step (1), the system generates a unique digital identity ID h (pk, ID) for the successfully registered participantv) The evaluators in the system identify each other by ID.
(3) The system records the historical evaluation data of the evaluators and sends the historical evaluation data to the objectivity calculation module, the objectivity calculation module calculates the objective index of each evaluator, and the numerical value is updated and disclosed on a chain after each evaluation is finished.
(3.1) assuming that n evaluators were present in total in one evaluation, the evaluators were designated as Ei(i ═ 1,2, …, n), giving evaluation information as a sample set Mi(i ═ 1,2, …, n), dividing k clusters C for the clustersj(j ═ 1,2, …, k); first, each cluster C is calculatedjMean vector of
Figure BDA0003380780610000081
Then use
Figure BDA0003380780610000082
Figure BDA0003380780610000083
The degree of closeness of the samples in the cluster around the cluster mean vector is quantified, with larger values representing less objective this evaluation by the evaluator.
(3.2) defining a time decay functionf(r)＝ρm-rWhere ρ represents a time attenuation factor, m represents the number of evaluations participated in by an evaluator, and r represents the r-th evaluation participated in; 0<ρ<1,1≤r≤m。
(3.3) calculating the objective index of the evaluator in the system according to the time decay function f (r) and the objective degree of the evaluator in each evaluation event, and adding the evaluator EiIs marked as OIi；
Figure BDA0003380780610000084
(4) The system calls the deployed intelligent contract to release evaluation, sets an evaluation object and evaluation included participants, then calculates the participation index of an evaluator, sets a dual threshold from the perspective of the objectivity and participation of the evaluator to select an evaluator list with evaluation qualification, and the evaluator gives evaluation information according to the evaluation object and submits the evaluation information to the system.
(4.1) first, the participation indexes of all the evaluators are calculated, and referring to the step (3), the set of all the evaluators in one evaluation is recorded as Ei(i-1, 2, …, n), each participant EiIs involved in
Figure BDA0003380780610000085
Where m represents the number of times the user participates in the evaluation,
Figure BDA0003380780610000086
representing the total number of times the rating was published in the system since the user registered.
(4.2) the system calls objective indexes and participation indexes of all evaluators, and sets dual thresholds: let the evaluator objective index threshold be α and the evaluator participation index threshold be β.
(4.3) the set of evaluators who assumed to reach the objective index threshold α is Elα(1, 2, …, p), and the set of evaluators who reached the objective index threshold β is Elβ(l 1,2, …, t), the evaluator set qualified for the reference is Elα∪Elβ。
(5) The system verifies the validity of the evaluation information, if the verification is successful, the evaluation information is extracted and sent to the evaluation processing module, and the evaluation processing module calculates the final evaluation result and discloses the final evaluation result to the block chain.
(5.1) the evaluation processing module obtains the evaluation data M given by each participant in the evaluationiThe evaluation data are divided into four categories according to the difference of participants, and n in the evaluators is recorded1The data set evaluated by the user is M1i，n2The data set evaluated by the bit owner is M2i，n3The dataset evaluated by the bit supervisor is M3i，n4The data set of evaluations made by the bit history user is M4i。
(5.2) according to different importance degrees of the evaluation information given by different participants, giving different weights omega to the participantsq(0<q is less than or equal to 4), and the weight of the participator not participating in evaluation is 0. Assuming that the final evaluation result is R, the calculation formula is:
Figure BDA0003380780610000091
example (b):
the present embodiment evaluates the course of colleges and universities. The technical solution of the present invention will be described in detail by the following examples, but the scope of the present invention is not limited to the examples.
As shown in fig. 1, the course evaluation system of the college and universities of the present embodiment is divided into an application layer, a block chain layer and a user layer.
The Evaluator (Evaluator) and the evaluation object (E) are involved in the user layerObject). Evaluation object (E)Object) Is the subject to be evaluated in the evaluation activities, namely the course of colleges and universities; the Evaluator (Evaluator) is an evaluation participant participating in an evaluation event and giving evaluation information, and comprises four participants, namely a User (User), an Owner (Owner), a Supervisor (Supervisor) and a historical User (H)user). Wherein the user refers to a student participating in the course in the current session; the historical user appoints students who have participated in the course; the owner isRefers to a teacher who teaches the course; supervisors refer to leaders and teaching supervisors from school parties or educational authorities associated with the course.
The application layer comprises a system initialization module, an identity authentication module, an objectivity calculation module, an evaluation qualification authentication module, an evaluation result calculation module and a data access module.
The system initialization module defines all parameters related to the evaluation process, gives initial values to the objective index and the participation index, deploys the intelligent contract on the block chain, and the evaluator participates in evaluation by accessing the intelligent contract. The identity authentication module identifies and authenticates the identity attribute provided by the evaluation participant when the evaluation participant applies for registration, if the authentication is passed, the registration is successful, and the system creates an identity ID for the user and stores the identity information of the user. And the objectivity calculation module is used for digitizing the objective degree of the evaluation made by each evaluator based on the historical evaluation behavior and the evaluation data of the evaluator stored in the system, standardizing the objective degree and outputting the objective degree as an objective index of the evaluator. The assessment qualification authentication module introduces the participation degree index of the evaluator on the basis of considering the objective index of the evaluator, sets double thresholds to carry out qualification authentication on the evaluators, and finally outputs an evaluator list capable of participating in an assessment event. And the evaluation result calculation module processes and calculates the evaluation score of the evaluation object based on the evaluation data uploaded by the evaluator, outputs the evaluation result and discloses the evaluation result to the block chain. The data access module defines the storage position of the data and the data acquisition authority, and is simultaneously responsible for fusing and butting the data among the identity verification module, the objectivity calculation module, the evaluation qualification certification module and the evaluation result calculation module.
The specific process of the university course evaluation method based on the heterogeneous block chain in the embodiment is as follows:
(1) the rating system is initialized and all values associated with the rating events are defined. Each evaluator E in the system should maintain a set of variables E ═ E (ID, OI, PI, Event, M), where ID is identity information, OI is an objective index of the evaluator, OI is an initial value, t, PI is an participation index of the evaluator, PI is an initial value, s, and Event is an evaluation Event list in which the evaluator participates,m is an evaluation information list given by each evaluation participated by the evaluator. The system-issued evaluation events should maintain a set of variables: event ═ E (E)ObjectP, α, β), in which EObjectThe evaluation object, P is the participant included in the evaluation, and alpha and beta are the objective index threshold and the participation index threshold, respectively, which are required to be reached by the participation evaluation.
Two intelligent contracts are deployed on the blockchain simultaneously: a user information contract and an evaluation execution contract. The user information contract stores related information, calculates objective indexes and participation indexes for each user according to the behavior and data of each user in the system in historical evaluation, and maintains the instant state information of the users; the evaluation execution contract describes the execution process of an evaluation event, and comprises two links of evaluation qualification certification and evaluation result calculation of a user, and an evaluator subjected to the evaluation qualification certification participates in evaluation by accessing the contract.
(1.1) the heterogeneous blockchain-based course evaluation system for colleges and universities is composed of a public chain and a alliance chain, wherein the public chain is used for storing and disclosing data; the federation chain is used for calculating related parameters and executing evaluation processes, wherein the specific process of data access is as follows:
after the system receives the uploaded data, a unique data key is obtained through a key generation algorithm, original data are encrypted, a hash value of the original data is calculated, and then a data index is calculated. After the steps are completed, the system stores the encrypted data embedded with the hash value in the cloud platform, and stores the index, the hash value and the key of the data in the public chain. And the cloud platform checks the validity of the transaction after receiving the transaction from the blockchain system, calculates the hash value of the received encrypted data, compares the hash value with the received hash value, and stores the encrypted data into the cloud platform if the hash value is matched with the received hash value. When the alliance chain needs to request actual data in the evaluation process, the system firstly obtains encrypted data from the cloud platform through an index value stored on the public chain, verifies the hash value of the data to ensure that the data is not tampered, decrypts the data by using a key stored on the public chain, and returns the actual data to a data requester.
(2) The evaluation participant does not need to provide real identity, but only needs to provide necessary identity attributeIdvApplying for a registration system, verifying and identifying the identity of the participant by an identity authentication module, registering the participant on the system if the verification is successful, and creating a digital ID for the participant and storing user information in the system by the system.
(2.1) evaluation of participants in application for registration to provide their identity attribute IdvAnd the identity authentication module identifies and verifies the identity attribute of the identity authentication module.
(2.2) if the verification is successful, the system assigns a pair of public and private keys (pk, sk), the private key being stored locally and uniquely identifying the participant, and the public key being stored in the system.
(2.3) based on the tuple information maintained by the evaluator in step (1), the system generates a unique digital identity ID h (pk, ID) for the successfully registered participantv) The evaluators in the system identify each other by ID.
(3) For each user in the system, the system maintains two parameters bound to it: objective index and participation index. The system records the historical evaluation data of the user and sends the historical evaluation data to the user information contract, and after the evaluation is finished each time, the latest objective index and participation index of the user in the appointment automatic computing system are combined, the user information is updated, and the information is linked and stored.
(3.1) assuming that n evaluators were present in total in one evaluation, the evaluators were designated as Ei(i ═ 1,2, …, n), giving evaluation information as a sample set Mi(i ═ 1,2, …, n), dividing k clusters C for the clustersj(j ═ 1,2, …, k); first, each cluster C is calculatedjMean vector of
Figure BDA0003380780610000111
Then use
Figure BDA0003380780610000112
Figure BDA0003380780610000113
The degree of closeness of the samples in the cluster around the cluster mean vector is quantified, with larger values representing less objective this evaluation by the evaluator.
(3.2) defining a time decay function f (r) ═ pm-rWhere ρ represents a time attenuation factor, m represents the number of evaluations participated in by an evaluator, and r represents the r-th evaluation participated in; 0<ρ<1,1≤r≤m。
(3.3) calculating the objective index of the evaluator in the system according to the time decay function f (r) and the objective degree of the evaluator in each evaluation event, and adding the evaluator EiIs marked as OIi；
Figure BDA0003380780610000114
(3.4) calculation of participation index of all evaluators
Figure BDA0003380780610000115
Where m represents the number of times the user participates in the evaluation,
Figure BDA0003380780610000116
representing the total number of times the rating was published in the system since the user registered.
(4) The school calls the deployed rating execution contract to issue a rating Event ═ (E)ObjectP, α, β), a specific evaluation course and a participant included in the evaluation are set, and then a list of evaluators qualified for evaluation is selected based on a user objective index and a participation index stored in the system and submitted to the system.
(4.1) the system calls objective indexes and participation indexes of all evaluators, and sets dual thresholds: let the evaluator objective index threshold be α and the evaluator participation index threshold be β.
(4.2) the set of evaluators who assumed to reach the objective index threshold α is Elα(1, 2, …, p), and the set of evaluators who reached the objective index threshold β is Elβ(l 1,2, …, t), the evaluator set qualified for the reference is Elα∪Elβ。
(5) The user passing the qualification authentication is used as an evaluator to participate in the course evaluation, the evaluator calls an evaluation execution contract and submits evaluation information of the evaluator, and the contract obtains a final evaluation result through the evaluation result calculation module and outputs the final evaluation result.
(5.1) the evaluation result calculation module acquires the evaluation data M given by each evaluator in the evaluationiThe evaluation data are divided into four categories according to the difference of participants, and n in the evaluators is recorded1The data set evaluated by the user is M1i，n2The data set evaluated by the bit owner is M2i，n3The dataset evaluated by the bit supervisor is M3i，n4The data set of evaluations made by the bit history user is M4i。
(5.2) according to different importance degrees of the evaluation information given by different participants, giving different weights omega to the participantsq(0<q is less than or equal to 4), and the weight of the participator not participating in evaluation is 0. Assuming that the final evaluation result is R, the calculation formula is:
Figure BDA0003380780610000121
(6) and (4) the nodes in the block chain carry out consensus on the final result, then the evaluation result is recorded on the block chain, the state of the block chain is updated, and the course evaluation is finished.
According to the embodiment, the distributed and non-falsifiable characteristics of the block chain are used for solving the problem of centralized rights collection of the existing evaluation system, and meanwhile, the credibility and traceability of data and the transparent disclosure of the evaluation process are ensured; the system calculates the objectivity value of each evaluator by adopting a clustering-based method according to the historical evaluation behavior and data of each evaluator, sets dual thresholds from the aspects of objectivity and participation degree before the evaluators participate in evaluation, and carries out qualification authentication on the objectivity value and the participation degree, thereby realizing constraint on the evaluation of the evaluators and improving the objectivity of the evaluation content and the credibility of the evaluation result.

Claims (8)

1. A credible evaluation method based on heterogeneous block chains is characterized by comprising the following steps: the method comprises the following steps:
initializing a credible evaluation system, and defining all values related to evaluation events;
each evaluator E maintains a set of variables E, E ═ E (ID, OI, PI, Event, M), where ID is its identity information, OI is the objective index of the evaluator, OI is an initial value, OI is t, PI is the participation index of the evaluator, PI is an initial value, PI is s, Event is the list of evaluation events that the evaluator participated in, and M is the list of evaluation information given by the evaluator each time it participates in;
an Event to be evaluated issued by an evaluation system maintains a set of variable events (E)ObjectP, α, β), in which EObjectThe evaluation object, P is the evaluation participator involved in the evaluation, alpha and beta are the objective index threshold and the participation index threshold respectively, alpha is the objective index threshold and the participation index threshold which are needed to be reached by the participation evaluation<t and beta<s; meanwhile, an intelligent contract is deployed on the block chain, and all evaluators participate in evaluation by accessing the intelligent contract;
step (2), the evaluation participator uses the necessary identity attribute to apply for registering the evaluation system, the identity authentication module verifies and identifies the identity of the participator, if the verification and the identification are successful, the evaluation participator will register on the system, the system creates a digital ID for the corresponding evaluation participator and stores the user information in the system;
step (3), the system records the historical evaluation data of the evaluators and sends the historical evaluation data to an objectivity calculation module, the objectivity calculation module calculates the objective index of each evaluator, and the numerical value is updated and disclosed on a block chain after each evaluation is finished;
step (4), the system calls the deployed intelligent contract to release evaluation, sets an evaluation object and participants contained in the evaluation, then calculates the participation index of an evaluator, sets a dual threshold from the perspective of objectivity and participation of the evaluator to select an evaluator list with evaluation qualification, and the evaluator gives evaluation information according to the evaluation object and submits the evaluation information to the system;
and (5) verifying the validity of the evaluation information by the system, extracting the evaluation information and sending the evaluation information to the evaluation result calculation module if the verification is successful, and calculating the final evaluation result by the evaluation result calculation module and disclosing the final evaluation result on the block chain.
2. The method according to claim 1, wherein the method comprises: the credible evaluation system in the step (1) is based on a heterogeneous block chain and comprises a public chain and a federation chain, wherein the public chain is used for storing and disclosing data, and the federation chain is used for calculating relevant parameters and executing an evaluation process, and the specific process of data access is as follows:
after receiving the uploaded data, the credible evaluation system firstly obtains a unique data key through a key generation algorithm, encrypts the original data and calculates the hash value of the original data, and then calculates a data index;
after the steps are completed, storing the encrypted data embedded with the hash value in a cloud platform, and storing the data index, the hash value and the key in a public chain;
the cloud platform checks the validity of the transaction after receiving the transaction from the blockchain system, calculates the hash value of the received encrypted data, compares the hash value with the received hash value, and stores the encrypted data into the cloud platform if the hash value is matched with the received hash value;
when the alliance chain needs to request actual data in the evaluation process, the system firstly obtains encrypted data from the cloud platform through an index value stored on the public chain, verifies the hash value of the data to ensure that the data is not tampered, decrypts the data by using a key stored on the public chain, and returns the actual data to a data requester.
3. The method according to claim 1, wherein the method comprises: the specific process of evaluating the identity authentication of the participants in the step (2) is as follows:
step (2.1), each evaluation participant needs to provide own identity attribute Id when applying for registrationvThe identity authentication module identifies and verifies the identity attribute of the identity authentication module;
step (2.2), if the verification is successful, the system distributes a pair of public and private keys (pk, sk) to the system, the private keys are stored locally and uniquely identify participants, and the public keys are stored in the system;
step (2.3), based on the tuple information maintained by the evaluator in step (1),the system generates a unique digital identity ID h (pk, ID) for successfully registered evaluation participantsv) Finally, the evaluators who have successfully registered identify each other by ID.
4. The method according to claim 1, wherein the method comprises: the objectivity calculating module in the step (3) calculates the objective index based on a clustering method, and specifically comprises the following steps:
in step (3.1), assuming that there are n evaluators in the primary evaluation, the evaluator is denoted as EiThe evaluation information given by them is a sample set MiI 1,2, …, n, dividing k clusters C for clusteringj(j＝1,2,…,k)；
First, each cluster C is calculatedjMean vector of
Figure FDA0003380780600000021
Then use
Figure FDA0003380780600000022
Figure FDA0003380780600000023
Quantifying the degree of closeness of the samples in the cluster around the cluster mean vector, wherein the larger the value is, the more objective the evaluator is to evaluate the time; u. ofjIs a cluster mean vector;
step (3.2) of defining a time decay function f (r) ═ ρm-rWhere ρ represents a time attenuation factor, m represents the number of evaluations participated in by an evaluator, and r represents the r-th evaluation participated in; 0<ρ<1,1≤r≤m；
Step (3.3), calculating the objective index of the evaluator in the system according to the time decay function f (r) and the objective degree of the evaluator in each evaluation event, and setting the evaluator EiIs marked as OIi；
Figure FDA0003380780600000024
5. The method according to claim 1, wherein the method comprises: the specific steps of the qualification selection authentication in the step (4) are as follows:
step (4.1), firstly calculating the participation indexes of all evaluators, and recording the set formed by all evaluators in one evaluation as Ei1,2, …, n, each participant EiIs involved in
Figure FDA0003380780600000031
Where m represents the number of times the user participates in the evaluation,
Figure FDA0003380780600000032
representing a total number of times the rating was published in the system since the user registered;
step (4.2), the system calls objective indexes and participation indexes of all evaluators, and double thresholds are set: recording the objective index threshold value of an evaluator as alpha and the participation index threshold value of the evaluator as beta;
step (4.3), assuming that the set of evaluators who reach the objective index threshold α is Elα1,2, …, p, and the set of evaluators who reached the objective index threshold β is ElβThe evaluator set with the qualification for evaluation is Elα∪Elβ。
6. The method according to claim 1, wherein the method comprises: the specific method for calculating the final evaluation result by the evaluation processing module in the step (5) is as follows:
step (5.1), the evaluation processing module obtains the evaluation data M given by each participant in the evaluationiThe evaluation data are divided into four categories according to the difference of participants, and n in the evaluators is recorded1The data set evaluated by the user is M1i，n2The data set evaluated by the bit owner is M2i，n3The dataset evaluated by the bit supervisor is M3i，n4The data set of evaluations made by the bit history user is M4i；
Step (5.2), according to different importance degrees of the evaluation information given by different participants, giving them different weights omegaq，0<q is less than or equal to 4, and the weight of the participator not participating in evaluation is 0;
assuming that the final evaluation result is R, the calculation formula is:
Figure FDA0003380780600000033
7. a system for implementing the trusted evaluation method based on heterogeneous blockchains according to any one of claims 1 to 6, wherein:
the system comprises a system initialization module, an identity authentication module, an objectivity calculation module, an evaluation qualification authentication module, an evaluation result calculation module and a data access module;
the system initialization module defines all parameters related to the evaluation process, gives initial values to part of variables, deploys intelligent contracts on a block chain at the same time, and an evaluator participates in evaluation by accessing the intelligent contracts;
the identity authentication module is used for identifying and verifying the identity attribute provided by all evaluation participants when the evaluation participants apply for registration, if the authentication is passed, the registration is successful, and the system creates an identity ID for the user and stores the identity information of the user;
the objectivity calculation module is used for digitizing the objective degree of evaluation made by each evaluator based on historical evaluation behaviors and evaluation data of the evaluators stored in the system, and outputting the objective degree as an objective index of the evaluators after carrying out standardization processing on the objective degree;
the assessment qualification authentication module introduces the participation index of the evaluator on the basis of considering the objective index of the evaluator, sets double thresholds to carry out qualification authentication on the evaluators, and finally outputs an evaluator list capable of participating in an assessment event;
the evaluation result calculation module processes and calculates the evaluation score of an evaluation object based on the evaluation data uploaded by an evaluator, outputs an evaluation result and discloses the evaluation result to a block chain;
the data access module defines the storage position of the data and the data acquisition authority, and is simultaneously responsible for fusing and butting the data among the identity verification module, the objectivity calculation module, the evaluation qualification certification module and the evaluation result calculation module.
8. The system of the trusted evaluation method based on the heterogeneous blockchain according to claim 7, wherein: involving Evaluator and evaluation object EObject；
The evaluation object EObjectThe body to be evaluated in the evaluation activity;
the Evaluator is an evaluation participant which participates in the evaluation event and gives evaluation information, and the evaluation participant comprises four participants which are respectively a User, an Owner Owner, a Supervisor Supervisor and a historical User Huser(ii) a Wherein the user is a user or an immediate participant of the evaluation object; the owner is the owner or manager of the evaluation object; the supervisor is a person or an organization supervising the evaluation object; the history user is a user who has used or participated in the evaluation object.
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Cited By (3)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN115271741A (en) * 2022-08-03 2022-11-01 国网江苏省电力有限公司南通供电分公司 Intelligent payment system and method for electric power capital construction cost based on block chain technology
CN117196653A (en) * 2023-08-29 2023-12-08 中山大学 Provider evaluation traceable collaborative management method and device based on alliance chain
CN117273832A (en) * 2022-04-19 2023-12-22 河北雄安三千科技有限责任公司 Evaluation method, device and system

Citations (6)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN110276547A (en) * 2019-06-20 2019-09-24 福州数据技术研究院有限公司 A kind of more people's evaluation methods based on block chain and history evaluation information
KR102106373B1 (en) * 2019-11-11 2020-05-04 이민우 Manufacturing execution system for smart factory based on blockchain interworking
CN111984843A (en) * 2020-08-18 2020-11-24 成都数融科技有限公司 Citizen credit evaluation method and system based on block chain
KR20210004091A (en) * 2019-07-03 2021-01-13 신기영 Method For Credit Rating Based On Block Chain
CN113240427A (en) * 2021-05-18 2021-08-10 山东省计算中心（国家超级计算济南中心） Credible transaction and service credit evaluation method based on block chain
CN113364831A (en) * 2021-04-27 2021-09-07 国网浙江省电力有限公司电力科学研究院 Multi-domain heterogeneous computing network resource credible cooperation method based on block chain

Patent Citations (6)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN110276547A (en) * 2019-06-20 2019-09-24 福州数据技术研究院有限公司 A kind of more people's evaluation methods based on block chain and history evaluation information
KR20210004091A (en) * 2019-07-03 2021-01-13 신기영 Method For Credit Rating Based On Block Chain
KR102106373B1 (en) * 2019-11-11 2020-05-04 이민우 Manufacturing execution system for smart factory based on blockchain interworking
CN111984843A (en) * 2020-08-18 2020-11-24 成都数融科技有限公司 Citizen credit evaluation method and system based on block chain
CN113364831A (en) * 2021-04-27 2021-09-07 国网浙江省电力有限公司电力科学研究院 Multi-domain heterogeneous computing network resource credible cooperation method based on block chain
CN113240427A (en) * 2021-05-18 2021-08-10 山东省计算中心（国家超级计算济南中心） Credible transaction and service credit evaluation method based on block chain

Non-Patent Citations (1)

* Cited by examiner, † Cited by third party
Title
董贵山 等: "基于区块链的异构身份联盟与监管体系架构和关键机制", 通信技术, vol. 53, no. 02, 10 February 2020 (2020-02-10), pages 401 - 413 *

Cited By (3)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN117273832A (en) * 2022-04-19 2023-12-22 河北雄安三千科技有限责任公司 Evaluation method, device and system
CN115271741A (en) * 2022-08-03 2022-11-01 国网江苏省电力有限公司南通供电分公司 Intelligent payment system and method for electric power capital construction cost based on block chain technology
CN117196653A (en) * 2023-08-29 2023-12-08 中山大学 Provider evaluation traceable collaborative management method and device based on alliance chain

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