CN111246468B - Data quality perception incentive method aiming at privacy protection in group perception - Google Patents

Data quality perception incentive method aiming at privacy protection in group perception Download PDF

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CN111246468B
CN111246468B CN202010035651.XA CN202010035651A CN111246468B CN 111246468 B CN111246468 B CN 111246468B CN 202010035651 A CN202010035651 A CN 202010035651A CN 111246468 B CN111246468 B CN 111246468B
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data
participant
perception
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service provider
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CN111246468A (en
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蒋云
赵搏文
唐韶华
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South China University of Technology SCUT
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    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04W—WIRELESS COMMUNICATION NETWORKS
    • H04W12/00—Security arrangements; Authentication; Protecting privacy or anonymity
    • H04W12/02—Protecting privacy or anonymity, e.g. protecting personally identifiable information [PII]
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
    • H04L63/00—Network architectures or network communication protocols for network security
    • H04L63/12—Applying verification of the received information
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
    • H04L9/00—Cryptographic mechanisms or cryptographic arrangements for secret or secure communications; Network security protocols
    • H04L9/32—Cryptographic mechanisms or cryptographic arrangements for secret or secure communications; Network security protocols including means for verifying the identity or authority of a user of the system or for message authentication, e.g. authorization, entity authentication, data integrity or data verification, non-repudiation, key authentication or verification of credentials
    • H04L9/3218—Cryptographic mechanisms or cryptographic arrangements for secret or secure communications; Network security protocols including means for verifying the identity or authority of a user of the system or for message authentication, e.g. authorization, entity authentication, data integrity or data verification, non-repudiation, key authentication or verification of credentials using proof of knowledge, e.g. Fiat-Shamir, GQ, Schnorr, ornon-interactive zero-knowledge proofs
    • H04L9/3221—Cryptographic mechanisms or cryptographic arrangements for secret or secure communications; Network security protocols including means for verifying the identity or authority of a user of the system or for message authentication, e.g. authorization, entity authentication, data integrity or data verification, non-repudiation, key authentication or verification of credentials using proof of knowledge, e.g. Fiat-Shamir, GQ, Schnorr, ornon-interactive zero-knowledge proofs interactive zero-knowledge proofs
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
    • H04L9/00—Cryptographic mechanisms or cryptographic arrangements for secret or secure communications; Network security protocols
    • H04L9/32—Cryptographic mechanisms or cryptographic arrangements for secret or secure communications; Network security protocols including means for verifying the identity or authority of a user of the system or for message authentication, e.g. authorization, entity authentication, data integrity or data verification, non-repudiation, key authentication or verification of credentials
    • H04L9/3271—Cryptographic mechanisms or cryptographic arrangements for secret or secure communications; Network security protocols including means for verifying the identity or authority of a user of the system or for message authentication, e.g. authorization, entity authentication, data integrity or data verification, non-repudiation, key authentication or verification of credentials using challenge-response
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04W—WIRELESS COMMUNICATION NETWORKS
    • H04W12/00—Security arrangements; Authentication; Protecting privacy or anonymity
    • H04W12/03—Protecting confidentiality, e.g. by encryption
    • H04W12/033—Protecting confidentiality, e.g. by encryption of the user plane, e.g. user's traffic

Abstract

The invention discloses a data quality perception incentive method aiming at privacy protection in group perception. The task publisher publishes a collection numerical range, the task participants are recruited by the perception service provider, the participants hide data in the constructed commitment to participate in the evaluation of the perception service provider, meanwhile, the reliability of the data submitted by the task participants is verified by the task publisher, the perception service provider provides anonymous technology for the participants to protect the identity privacy of the participants, and the incentive of data quality under the privacy protection is realized under the constraint of the task budget through the two-stage data quality measurement and the incentive mechanism based on the data quality. The method protects the identity privacy of the user and evaluates the reliability of the data of the participants in a privacy protection manner.

Description

Data quality perception incentive method aiming at privacy protection in group perception
Technical Field
The invention relates to the technical field of information security, in particular to a data quality perception incentive method aiming at privacy protection in group perception.
Background
In recent years, with the popularization of mobile sensor devices and the development of mobile device communication technologies, mobile group awareness is becoming a new data collection paradigm. The population aware application includes three main entities: a task requester, a perceptual service provider, and a group of participants. The task requester outsources the perception task to a perception service provider, and the perception service provider recruits a group of qualified participants to execute the task for the perception task. The group sensing application has the characteristics of easiness in deployment, wide coverage range and low maintenance cost, and brings great convenience for large-scale data collection, but the quality of the collected data is greatly different due to the irregular participation of sensing equipment and the uncontrollable behavior of participants; furthermore, while the perceptual service provider provides convenience for the task to process the collected data, it also faces privacy issues that reveal user data. If the group perception application does not have any privacy protection measures, the willingness of the participants to execute the perception tasks is reduced, and the popularization of the group perception application is influenced.
The reliability of a community-aware application depends not only on the large amount of sensory data collected, but also requires the support of a single high quality data. Existing methods for evaluating perceptual data quality fall into three categories: and (3) a participant reputation score, the context of perception data and a truth value discovery iterative algorithm. Evaluating data quality according to participant reputation scores tends to ignore user data privacy; data quality assessment algorithms such as perceptual data context and truth discovery are vulnerable to malicious data attacks. Therefore, in order to improve the willingness of the participants to execute tasks, reasonably evaluate the quality of the perception data and protect the privacy of the perception data, the incentive method for evaluating the quality of the perception data with privacy protection is realized on the basis of the zero-knowledge proof theory, and meanwhile, anonymous identity information is provided for the participants to protect the identity information of the users.
Disclosure of Invention
The invention aims to overcome the defects and shortcomings of the prior art, and provides a data quality perception excitation method aiming at privacy protection in group perception, which aims at solving the problems of data quality evaluation and data privacy in group perception excitation, proving whether perception data provided by participants are in a reasonable interval range of an evaluation standard, so as to realize the evaluation of data quality, and simultaneously realizing the identity privacy of users through an anonymity technology.
In order to achieve the purpose, the technical scheme provided by the invention is as follows: a data quality perception incentive method aiming at privacy protection in group perception comprises the following steps:
s1, the task publisher initializes the public and private key pair (pk)d,skd) Sending { T, pkdPi, n, B, R are respectively task content T and public key pkdThe incentive reward control parameter pi, the recruiter number n, the budget B and the quality evaluation standard interval R to a perception service provider, and the perception service provider generates a parameter pk of zero knowledge proof for the task Tz(p, G, h) where p is a large prime number, generating a cyclic group G at the base of p, G and h being generator elements of the cyclic group GPerception service provider broadcast task information { T, pkd,pkzN, B recruiting participants wiI is more than or equal to 1 and less than or equal to n, participant wiAccording to cost c of collecting perception dataiAnd minimum reward for the task
Figure GDA0002883152230000021
Determines whether to participate in the task and collects perception data, the perception service provider collecting perception data for each participant wiProviding a token for submitting data
Figure GDA0002883152230000022
mod p, wherein
Figure GDA0002883152230000023
xiIs to perceive the service provider as a participant wiThe random value is selected to be a value,
Figure GDA0002883152230000024
represents a set of positive integers in cyclic group G;
s2, participant wiCalculating an anonymous identity
Figure GDA0002883152230000025
mod p,
Figure GDA0002883152230000026
Sending privacy-preserving perceptual data quality assessment requests
Figure GDA0002883152230000027
Wherein y isiIs participant wiSelf-selected random value, zero-knowledge proof of challenge-response protocol iZKM (D) by perceptual service providers with privacy preserving data quality assessmenti,pkzR) determining perception data DiWhether the task is within a reasonable range of the task requirement, namely within a quality evaluation standard interval R;
s3, the perception service provider evaluates the participation data to obtain qualified participant information
Figure GDA0002883152230000031
Is sent to the task publisher, and the task publisher,
Figure GDA0002883152230000032
mod p is participant wiIdentity information of S0,iIs participant wiFor perception data DiStructural commitment, perception of service provider in receiving task publisher's prepaid remuneration
Figure GDA0002883152230000033
Immediately thereafter, the participant is informed to submit the encrypted perception data Enc (D)i,pkd) And a random number Enc (r)i,pkd) To the task publisher, riIs participant wiA random value of choice;
s4, the task publisher encrypts the received encrypted perception data Enc (D)i,pkd) Decrypting and verifying to confirm the perception data DiAfter passing the verification, informing the perception service provider according to
Figure GDA0002883152230000034
Distributing rewards to participants
Figure GDA0002883152230000035
Representing payment confirmation parameters,. pi.is an incentive reward control parameter,. qiIs to the perception data DiBy Euclidean distance function
Figure GDA0002883152230000036
The value of the metric being evaluated is,
Figure GDA0002883152230000037
is the average of the sum of all the perceptual data,
Figure GDA0002883152230000038
is the average value of the summation calculation of all the measurement values, otherwise, the perception service provider is informed not to send the task reportRemuneration to participant wi。
The step S1 includes the steps of:
s11, the task publisher initializes the public and private key pair (pk) of the parameter for the task content Td,skd) Wherein
Figure GDA0002883152230000039
And
Figure GDA00028831522300000310
control incentive reward control parameter pi, number of persons recruiting participants n and budget B, and quality assessment criteria interval R of collected data [ a, B ═]The task publisher sends a task request { T, pkdPi, n, B, R } to a perceptual service provider;
s12, sensing parameters T, pk in service provider broadcast task requestdN, B } and recruiting n participants;
s13 participant w with intention to participateiWhen a request is made to a aware service provider to participate in a task, then the aware service provider computes
Figure GDA00028831522300000311
mod p as a data submission token to participant wi，
Figure GDA00028831522300000312
S14, participant wiFirst, the cost of executing the task is judged
Figure GDA00028831522300000313
Whether or not this is true because
Figure GDA00028831522300000314
Is the minimum reward for performing the task, thereby ensuring the benefit of the participant if
Figure GDA00028831522300000315
If true, then participant wiFor perceiving tasksCollecting data Di。
Step S2 includes the following steps:
s21, participant generates anonymous identity
Figure GDA0002883152230000041
Zero-knowledge proof challenge-response protocol iZKM (D) for privacy preserving data quality assessment with mod p participating in zero-knowledge proof constructioni,pkzR), detailed procedures including construction commitments, challenge-response and verification evaluation;
s22, iZKM construction commitment: participant wiSelecting a random value ri,
Figure GDA0002883152230000042
Construct a commitment
Figure GDA0002883152230000043
Is sent to the provider of the awareness service,
Figure GDA0002883152230000044
is that
Figure GDA00028831522300000415
Is determined by the fact that the factors of confusion,
Figure GDA0002883152230000045
is to the perception data DiP, G and h are public parameters, p is a large prime number, G is a cyclic group of p prime orders, and G and h are generating elements of the cyclic group G; the reasonable interval is expressed as [ a, b]，
Figure GDA0002883152230000046
If the perception data uploaded by the participants
Figure GDA0002883152230000047
The participator and the perception service provider prove that the uploaded perception data are in a reasonable interval through interaction [ a, b ]]Within the range;
s23, iZKM challenge: whenever a aware service provider receives participant wiSent commitment S0,iThe perceptual service provider then returns the value of the lower bound a and the value of the upper bound b of the evaluation range as a challenge to the participant;
s24, iZKM response: after the participants receive the challenge containing the values a and b sent by the perception service provider, the participants judge the perception data D of the participantsiWhether or not in [ a, b ]]Interval, if the perception data D of the participantiIn [ a, b ]]If the interval is not within the interval, the participant exits the task and returns to the perception service provider, the data quality evaluation of the participant is terminated, and if the perception data D of the participanti∈[a,b]Then the participant calculates
Figure GDA0002883152230000048
And
Figure GDA0002883152230000049
as a response to the challenge, wherein
Figure GDA00028831522300000416
And
Figure GDA00028831522300000410
are respectively
Figure GDA00028831522300000411
And
Figure GDA00028831522300000412
in the context of the confusion that is,
Figure GDA00028831522300000413
and
Figure GDA00028831522300000414
is to DiA and | b-DiHiding of |, S1,iAnd S2,iResponses to the challenge lower limit a and upper limit b, respectively, and then transmitted (S)1,i,S2,i) To the aware service provider;
s25, iZKM validation evaluation: sensing the response returned by the service provider to the challenge based on the participant (S)1,i,S2,i) Verifying commitments submitted by participants S0,iBy calculating S1,i＝S0,i·(ga)-1mod p and S2,i＝gb·(S0,i)-1mod p，S0,i、S1,iAnd S2,iAre respectively the participant wiCommitment of constructs and response to challenges, (g)a)-1And gbIs a structural factor, (S)0,i)-1Is S0,iIn the reverse of the loop group G, a computational validation that is true indicates that the participant uses the same perceptual data values in constructing commitments and response challenges, that the perceptual service provider is not spoofed, and that the perceptual service provider trusts the perceptual data D uploaded by the participanti∈[a,b]The perception data uploaded by the participant proves the challenge-response protocol iZKM through zero knowledge of privacy protection data quality evaluation, otherwise the data quality evaluation of the participant is failed.
Step S3 includes the following steps:
s31, participant wiData D ofiThe data quality assessment by the perceptual service provider satisfies the scope of requirements R of the task, and subsequently the perceptual service provider will satisfy the participants w of the data quality assessmentiInformation of
Figure GDA0002883152230000051
Is sent to the task publisher, wherein
Figure GDA0002883152230000052
The representation of an anonymous identity is represented,
Figure GDA0002883152230000053
represents the commitment of the construct while informing the participant wiData D ofiSatisfy reliability assessment of data quality, otherwise notify participant wiThe data evaluation fails, and the task is ended;
s32, task publisherReceiving participant w satisfying the data quality assessmentiAfter the information, a prepayment request is sent
Figure GDA0002883152230000054
To a perceptual service provider, wherein
Figure GDA0002883152230000055
Is a prepayment to the participant;
s33, perception service provider receives and provides to participant wiImmediately after the prepayment, the participant w is notifiediSubmitting the perception data to a task publisher;
s34, participant wiEncrypted perception data Enc (D) after receipt of a prepayment noticei,pkd) And a random number Enc (r)i,pkd) And sending the task to the task publisher.
Step S4 includes the following steps:
s41, the task publisher uses the private key skdDecrypting participant submitted data D'i＝Dec(Enc(Di,pkd),skd) And ri'＝Dec(Enc(ri,pkd),skd)；
S42, calculating by task publisher
Figure GDA0002883152230000056
Validating participant wiThe reliability of the submitted data is such that,
Figure GDA0002883152230000057
is that
Figure GDA0002883152230000058
In the context of the confusion that is,
Figure GDA0002883152230000059
is to D 'obtained after decryption'iIs hidden, D'iAnd ri'is decrypted D'i＝Dec(Enc(Di,pkd),skd) And Dec (Enc (r)i,pkd),skd) Result of the acquisition, S0,iIs a commitment made by the participant to perform a privacy data quality assessment,
Figure GDA0002883152230000069
is that the task publisher bases on the participant wiSubmitted data D'i＝Dec(Enc(Di,pkd),skd) And ri'＝Dec(Enc(ri,pkd),skd) Fabricated commitment as long as task publisher decrypts resulting data D'iAnd ri' satisfy
Figure GDA0002883152230000061
The submitted data meets the reliability, the surplus reward of the participants is paid, and the reward is refused to be paid if the verification is not passed;
s43, sending by the task publisher as long as the data passes the verification
Figure GDA0002883152230000062
To a perception service provider, wherein
Figure GDA0002883152230000063
Representing payment confirmation parameters,. pi.is an incentive reward control parameter,. qiIs to the perception data DiOf the Euclidean distance function
Figure GDA0002883152230000064
The quality of the measurement of (a) is evaluated,
Figure GDA0002883152230000065
is the average of the sum of all the perceptual data,
Figure GDA0002883152230000066
is the average of the sum of all the metrics, and uses this parameter to inform the sensing service provider whether it is an anonymous user
Figure GDA0002883152230000067
mod p payments;
s44 perception service provider as participant wiIssuing a true monetary amount
Figure GDA0002883152230000068
m is less than or equal to n, i is less than or equal to 1 and less than or equal to m, m represents the number of users passing the verification of the task publisher, and B is the task budget.
Compared with the prior art, the invention has the following advantages and beneficial effects:
1. the method can effectively balance the reliability evaluation and privacy protection of the data, and the zero-knowledge proof challenge-response protocol iZKM for evaluating the privacy protection data quality can effectively determine whether the data meets the range constraint of a task requester on the data and does not leak the data content.
2. The invention coordinates the relationship between the reward and the data quality, realizes a reward distribution mechanism integrating data quality evaluation and data quality metric evaluation, and realizes reward distribution with data quality consciousness under the constraint of task budget.
3. The invention can effectively prevent some malicious behaviors of participants and task requesters. And the task publisher is prevented from uploading forged data to deceive the task publisher after the task publisher passes data evaluation. Meanwhile, the benefit of the participants is guaranteed through a mechanism of prepaying, and the malicious repudiation behavior of the task publisher is prevented.
Drawings
FIG. 1 is a flow chart of the method of the present invention.
Fig. 2 is a diagram of the architecture of the application of the method of the present invention.
Detailed Description
The present invention will be further described with reference to the following specific examples.
The data quality perception incentive method for privacy protection in group perception provided by the embodiment completes evaluation and incentive of privacy data quality in a semi-trusted perception service provider based on a zero-knowledge proof principle and identity anonymity. In the non-secure channel, submitted data is encrypted through a public key cryptographic algorithm, and the confidentiality of the data is protected. Under the budget constraint, the relation between the data quality and the incentive is effectively coordinated. Malicious behavior of the task publisher and the participant can be effectively prevented by two-level data quantity measurement and reward part incentive.
Firstly, a task publisher initializes a private-public key pair of the task publisher, publishes the content, the public key and the parameters of the task to a service provider, and recruits participants by broadcasting the content of a task request. And the interaction between the perception service provider and the participants is judged through the zero-knowledge proof challenge-response protocol iZKM interaction of privacy protection data quality evaluation, and whether the data participating in evaluation is in a task requirement range is judged.
And secondly, a data submitting part after the data quality evaluation is passed, wherein the perception service provider informs the task publisher of the participant passing the data quality evaluation, and simultaneously constructs an anonymous identity for the participant, the anonymous identity is used for committing the data participating in the evaluation to be sent to the task publisher, the task publisher prepaying part stimulates the reward to the perception service provider, the perception service provider informs the participant to send the encrypted data to the task publisher, and the task publisher decrypts the data and verifies the rationality of the decrypted data through the constructed commitment submitted by the participant.
Finally, the task publisher notifies the aware service provider of the list of participants who pass the data validation, while issuing the remaining portion of incentive rewards through the service provider.
As shown in fig. 1 and fig. 2, the data quality perception incentive method for privacy protection in group perception includes the following steps:
s1, the task publisher initializes the public and private key pair (pk)d,skd) Sending { T, pkdPi, n, B, R are respectively task content T and public key pkdThe incentive reward control parameter pi, the recruiter number n, the budget B and the quality evaluation standard interval R to a perception service provider, and the perception service provider generates a parameter pk of zero knowledge proof for the task Tz(p, G, h) where p is a large prime number, generating a cyclic group G at the base of p, G and h being generators of the cyclic group G, sensory apparelService provider broadcasts task information { T, pkd,pkzN, B recruiting participants wiI is more than or equal to 1 and less than or equal to n, participant wiAccording to cost c of collecting perception dataiAnd minimum reward for the task
Figure GDA0002883152230000081
Determines whether to participate in the task and collects perception data, the perception service provider collecting perception data for each participant wiProviding a token for submitting data
Figure GDA0002883152230000082
mod p, wherein
Figure GDA0002883152230000083
xiIs to perceive the service provider as a participant wiThe random value is selected to be a value,
Figure GDA0002883152230000084
represents a set of positive integers in cyclic group G; the specific process is as follows:
s11, the task publisher initializes the public and private key pair (pk) of the parameter for the task content Td,skd) Wherein
Figure GDA0002883152230000085
And
Figure GDA0002883152230000086
control incentive reward control parameter pi, number of persons recruiting participants n and budget B, and quality assessment criteria interval R of collected data [ a, B ═]The task publisher sends a task request { T, pkdPi, n, B, R } to a perceptual service provider;
s12, sensing parameters T, pk in service provider broadcast task requestdN, B } and recruiting n participants;
s13 participant w with intention to participateiWhen a request is made to a aware service provider to participate in a task, then the aware service provider computes
Figure GDA0002883152230000087
mod p as a data submission token to participant wi，
Figure GDA0002883152230000088
S14, participant wiFirst, the cost of executing the task is judged
Figure GDA0002883152230000089
Whether or not this is true because
Figure GDA00028831522300000810
Is the lowest reward for performing the task, thereby ensuring the benefit of the participant. If it is not
Figure GDA00028831522300000811
If true, then participant wiCollecting data D for perceptual tasksi。
S2, participant wiCalculating an anonymous identity
Figure GDA00028831522300000812
mod p,
Figure GDA00028831522300000813
Sending privacy-preserving perceptual data quality assessment requests
Figure GDA0002883152230000091
Wherein y isiIs participant wiSelf-selected random value, zero-knowledge proof of challenge-response protocol iZKM (D) by perceptual service providers with privacy preserving data quality assessmenti,pkzR) determining perception data DiWhether the task is within a reasonable range of the task requirement, namely within a quality evaluation standard interval R; the specific process is as follows:
s21, participant generates anonymous identity
Figure GDA0002883152230000092
Zero-knowledge proof challenge-response protocol iZKM (D) for privacy preserving data quality assessment with mod p participating in zero-knowledge proof constructioni,pkzR), detailed procedures including construction commitments, challenge-response and verification evaluation;
s22, iZKM construction commitment: participant wiSelecting a random value ri,
Figure GDA0002883152230000093
Construct a commitment
Figure GDA0002883152230000094
Is sent to the provider of the awareness service,
Figure GDA0002883152230000095
is that
Figure GDA0002883152230000096
Is determined by the fact that the factors of confusion,
Figure GDA00028831522300000917
is to the perception data DiP, G and h are public parameters, p is a large prime number, G is a cyclic group of p prime orders, and G and h are generating elements of the cyclic group G; assume a reasonable interval denoted as [ a, b ]]，
Figure GDA0002883152230000097
If the perception data uploaded by the participants
Figure GDA0002883152230000098
The participator and the perception service provider prove that the uploaded perception data are in a reasonable interval through interaction [ a, b ]]Within the range;
s23, iZKM challenge: whenever a aware service provider receives participant wiSent commitment S0,iThe perceptual service provider then returns the value of the lower bound a and the value of the upper bound b of the evaluation range as a challenge to the participant;
s24, iZKM response: participate inAfter a participant receives a challenge containing a value and a value b sent by a perception service provider, the participant judges the perception data D of the participantiWhether or not in [ a, b ]]Interval, if the perception data D of the participantiIn [ a, b ]]If the interval is not within the interval, the participant exits the task and returns to the perception service provider, the data quality evaluation of the participant is terminated, and if the perception data D of the participanti∈[a,b]Then the participant calculates
Figure GDA0002883152230000099
And
Figure GDA00028831522300000910
as a response to the challenge, wherein
Figure GDA00028831522300000911
And
Figure GDA00028831522300000912
are respectively
Figure GDA00028831522300000913
And
Figure GDA00028831522300000914
in the context of the confusion that is,
Figure GDA00028831522300000915
and
Figure GDA00028831522300000916
is to DiA and | b-DiHiding of |, S1,iAnd S2,iResponses to the challenge lower limit a and upper limit b, respectively, and then transmitted (S)1,i,S2,i) To the aware service provider;
s25, iZKM validation evaluation: sensing the response returned by the service provider to the challenge based on the participant (S)1,i,S2,i) Verifying commitments submitted by participants S0,iBy calculating S1,i＝S0,i·(ga)-1mod p and S2,i＝gb·(S0,i)-1mod p，S0,i、S1,iAnd S2,iAre respectively the participant wiCommitment of constructs and response to challenges, (g)a)-1And gbIs a structural factor, (S)0,i)-1Is S0,iIn the reverse of the loop group G, a computational validation that is true indicates that the participant uses the same perceptual data values in constructing commitments and response challenges, that the perceptual service provider is not spoofed, and that the perceptual service provider trusts the perceptual data D uploaded by the participanti∈[a,b]The perception data uploaded by the participant proves the challenge-response protocol iZKM through zero knowledge of privacy protection data quality evaluation, otherwise the data quality evaluation of the participant is failed.
S3, the perception service provider evaluates the participation data to obtain qualified participant information
Figure GDA0002883152230000101
Is sent to the task publisher, and the task publisher,
Figure GDA0002883152230000102
mod p is participant wiIdentity information of S0,iIs participant wiFor perception data DiStructural commitment, perception of service provider in receiving task publisher's prepaid remuneration
Figure GDA0002883152230000103
Immediately thereafter, the participant is informed to submit the encrypted perception data Enc (D)i,pkd) And a random number Enc (r)i,pkd) To the task publisher, riIs participant wiA random value of choice; the specific process is as follows:
s31, participant wiData D ofiThe data quality assessment by the perceptual service provider satisfies the scope of requirements R of the task, and subsequently the perceptual service provider will satisfy the participants w of the data quality assessmentiInformation of
Figure GDA0002883152230000104
Is sent to the task publisher, wherein
Figure GDA0002883152230000105
mod p represents the anonymous identity and,
Figure GDA0002883152230000106
represents the commitment of the construct while informing the participant wiData D ofiSatisfy reliability assessment of data quality, otherwise notify participant wiThe data evaluation fails, and the task is ended;
s32, the task publisher receives the participant w meeting the data quality evaluationiAfter the information, a prepayment request is sent
Figure GDA0002883152230000107
To a perceptual service provider, wherein
Figure GDA0002883152230000108
Is a prepayment to the participant;
s33, perception service provider receives and provides to participant wiImmediately after the prepayment, the participant w is notifiediSubmitting the perception data to a task publisher;
s34, participant wiEncrypted perception data Enc (D) after receipt of a prepayment noticei,pkd) And a random number Enc (r)i,pkd) And sending the task to the task publisher.
S4, the task publisher encrypts the received encrypted perception data Enc (D)i,pkd) Decrypting and verifying to confirm the perception data DiAfter passing the verification, informing the perception service provider according to
Figure GDA0002883152230000111
Distributing rewards to participants
Figure GDA0002883152230000112
Denotes a payment confirmation parameter,. pi.Excitation reward control parameter, qiIs to the perception data DiBy Euclidean distance function
Figure GDA0002883152230000113
The value of the metric being evaluated is,
Figure GDA0002883152230000114
is the average of the sum of all the perceptual data,
Figure GDA0002883152230000115
is the average of the sum of all metrics, otherwise the perception service provider is notified not to send task remuneration to participant wi(ii) a The specific process is as follows:
s41, the task publisher uses the private key skdDecrypting participant submitted data Di'＝Dec(Enc(Di,pkd),skd) And ri'＝Dec(Enc(ri,pkd),skd)；
S42, calculating by task publisher
Figure GDA0002883152230000116
Validating participant wiThe reliability of the submitted data is such that,
Figure GDA0002883152230000117
is that
Figure GDA0002883152230000118
In the context of the confusion that is,
Figure GDA0002883152230000119
is to D 'obtained after decryption'iIs hidden, D'iAnd ri'is decrypted D'i＝Dec(Enc(Di,pkd),skd) And Dec (Enc (r)i,pkd),skd) Result of the acquisition, S0,iIs a commitment made by the participant to perform a privacy data quality assessment,
Figure GDA00028831522300001110
is that the task publisher bases on the participant wiSubmitted data D'i＝Dec(Enc(Di,pkd),skd) And ri'＝Dec(Enc(ri,pkd),skd) Fabricated commitment as long as task publisher decrypts resulting data D'iAnd ri' satisfy
Figure GDA00028831522300001111
The submitted data meets the reliability, the surplus reward of the participants is paid, and the reward is refused to be paid if the verification is not passed;
s43, sending by the task publisher as long as the data passes the verification
Figure GDA00028831522300001112
To a perception service provider, wherein
Figure GDA00028831522300001113
Representing payment confirmation parameters,. pi.is an incentive reward control parameter,. qiIs to the perception data DiOf the Euclidean distance function
Figure GDA00028831522300001114
The quality of the measurement of (a) is evaluated,
Figure GDA00028831522300001115
is the average of the sum of all the perceptual data,
Figure GDA00028831522300001116
is the average of the sum of all the metrics, and uses this parameter to inform the sensing service provider whether it is an anonymous user
Figure GDA00028831522300001117
mod p payments;
s44 perception service provider as participant wiIssuing a true monetary amount
Figure GDA00028831522300001118
m is less than or equal to n, i is less than or equal to 1 and less than or equal to m, m represents the number of users passing the verification of the task publisher, and B is the task budget.
The task publisher: the system is used for initializing the public and private keys of the system, determining a reasonable interval of data, determining the number of people for recruiting participants and determining the reward for releasing tasks; issuing a prepaid fee to the participant for data quality assessment by the service provider; decrypting the encrypted data submitted by the participant and verifying the encrypted data according to a zero-knowledge proof principle; compensation is issued by the service provider to the participants who provide data that meets the task requirements.
The perception service provider: the method is used for data quality evaluation, and according to the commitment constructed by the sensing data used by the participants, the upper limit and the lower limit of a reasonable interval required by a sending task are used as a challenge to be sent to the participants; judging whether the data meets the requirements of the task or not according to the response of the participants to the challenge; the commitment and the anonymous identity of the participant passing the data quality evaluation are sent to a task publisher, and the participant is informed of passing the data quality evaluation, otherwise, the participant is informed of not passing the data quality evaluation and is ended; and after the task publisher verifies the data, issuing incentive compensation to the participants.
The participants: the system comprises a data acquisition module, a data processing module and a data processing module, wherein the data acquisition module is used for acquiring data for a perception task, constructing a commitment containing perception data according to task parameters broadcast by a service provider and submitting the commitment to the service provider for evaluation; simultaneously responding to challenges posed by the service provider with respect to the data commitments; and after the data quality evaluation is carried out, encrypting the sensing data by using the public key of the task publisher and sending the encrypted sensing data to the task publisher.
In summary, the present invention mainly includes privacy protection data quality assessment, participant identity privacy protection, two-level data quality metrics, and a data quality-based incentive function. In the initialization process, a task publisher initializes a public key and a private key, and gives a reasonable range of collected data, the number of recruited people and task incentive rewards; the service provider broadcasts task information and recruits participants, simultaneously performs quality evaluation on data of the participants, sets anonymous identities for users who pass the data quality evaluation, and forwards data commitments and the anonymous identities of the participants to a task publisher; the task publisher issues prepaid consideration to the participant who passes the data quality evaluation to the service provider, and the service provider informs the participant to submit the encrypted data to the task publisher; the task publisher decrypts the encrypted data and performs calculation verification with the data commitment of the user; the task publisher issues the remaining incentive rewards to the service provider for the verified participants; finally the service provider sends all the rewards this time to the participants.
The above embodiments are preferred embodiments of the present invention, but the present invention is not limited to the above embodiments, and any other changes, modifications, substitutions, combinations, and simplifications which do not depart from the spirit and principle of the present invention should be construed as equivalents thereof, and all such changes, modifications, substitutions, combinations, and simplifications are intended to be included in the scope of the present invention.

Claims (5)

1. A data quality perception incentive method aiming at privacy protection in group perception is characterized by comprising the following steps:
s1, the task publisher initializes the public and private key pair (pk)d,skd) Sending { T, pkdPi, n, B, R are respectively task content T and public key pkdThe incentive reward control parameter pi, the recruiter number n, the budget B and the quality evaluation standard interval R to a perception service provider, and the perception service provider generates a parameter pk of zero knowledge proof for the task Tz(p, G, h), where p is a large prime number, generating a cyclic group G at base p, G and h are generators of the cyclic group G, the perceptual service provider broadcasting task information { T, pkd,pkzN, B recruiting participants wiI is more than or equal to 1 and less than or equal to n, participant wiAccording to cost c of collecting perception dataiAnd minimum reward for the task
Figure FDA0002906501450000011
Determines whether to participate in the task and collects perception data, the perception service provider collecting perception data for each participant wiProviding a token for submitting data
Figure FDA0002906501450000012
Wherein
Figure FDA0002906501450000013
xiIs to perceive the service provider as a participant wiThe random value is selected to be a value,
Figure FDA0002906501450000014
represents a set of positive integers in cyclic group G;
s2, participant wiCalculating an anonymous identity
Figure FDA0002906501450000015
Sending privacy-preserving perceptual data quality assessment requests
Figure FDA0002906501450000016
Wherein y isiIs participant wiSelf-selected random value, zero-knowledge proof of challenge-response protocol iZKM (D) by perceptual service providers with privacy preserving data quality assessmenti,pkzR) determining perception data DiWhether the task is within a reasonable range of the task requirement, namely within a quality evaluation standard interval R;
s3, the perception service provider evaluates the participation data to obtain qualified participant information
Figure FDA0002906501450000017
Is sent to the task publisher, and the task publisher,
Figure FDA0002906501450000018
is participant wiIdentity information of S0,iIs participant wiFor perception data DiStructural commitment, perception of service provider in receiving task publisher's prepaid remuneration
Figure FDA0002906501450000019
Immediately thereafter, the participant is informed to submit the encrypted perception data Enc (D)i,pkd) And a random number Enc (r)i,pkd) To the task publisher, riIs participant wiA random value of choice;
s4, the task publisher encrypts the received encrypted perception data Enc (D)i,pkd) Decrypting and verifying to confirm the perception data DiAfter passing the verification, informing the perception service provider according to
Figure FDA00029065014500000110
Issuing a reward to a participant wi，
Figure FDA0002906501450000021
Representing payment confirmation parameters, qiIs to the perception data DiBy Euclidean distance function
Figure FDA0002906501450000022
The value of the metric being evaluated is,
Figure FDA0002906501450000023
is the average of the sum of all the perceptual data,
Figure FDA0002906501450000024
is the average of the sum of all metrics, otherwise the perception service provider is notified not to send task remuneration to participant wi。
2. The data quality perception incentive method for privacy protection in community perception according to claim 1, wherein the step S1 comprises the following steps:
s11, the task publisher initializes the public and private key pair (pk) of the parameter for the task content Td,skd) Wherein
Figure FDA0002906501450000025
And
Figure FDA0002906501450000026
control incentive reward control parameter pi, number of persons recruiting participants n and budget B, and quality assessment criteria interval R of collected data [ a, B ═]A represents setting a lower limit of reasonable data, b represents setting an upper limit of reasonable data, and a task publisher sends a task request { T, pkdPi, n, B, R } to a perceptual service provider;
s12, sensing parameters T, pk in service provider broadcast task requestdN, B } and recruiting n participants;
s13 participant w with intention to participateiWhen a request is made to a aware service provider to participate in a task, then the aware service provider computes
Figure FDA0002906501450000027
As a data submission token to participant wi，
Figure FDA0002906501450000028
S14, participant wiFirst, the cost of executing the task is judged
Figure FDA0002906501450000029
Whether or not this is true because
Figure FDA00029065014500000210
Is the minimum reward for performing the task, thereby ensuring the benefit of the participant if
Figure FDA00029065014500000211
If true, then participant wiCollecting data D for perceptual tasksi。
3. The data quality perception incentive method for privacy protection in community perception according to claim 1, wherein the step S2 comprises the following steps:
s21, participant generates anonymous identity
Figure FDA00029065014500000212
Zero-knowledge proof challenge-response protocol iZKM (D) for privacy preserving data quality assessment participating in zero-knowledge proof constructioni,pkzR), detailed procedures including construction commitments, challenge-response and verification evaluation;
s22, iZKM construction commitment: participant wiSelecting a random value ri,
Figure FDA00029065014500000213
Construct a commitment
Figure FDA0002906501450000031
Is sent to the provider of the awareness service,
Figure FDA0002906501450000032
is that
Figure FDA0002906501450000033
Is determined by the fact that the factors of confusion,
Figure FDA0002906501450000034
is to the perception data DiP, G and h are public parameters, p is a large prime number, G is a cyclic group of p prime orders, and G and h are generating elements of the cyclic group G; the reasonable interval is expressed as [ a, b]，
Figure FDA0002906501450000035
If the perception data uploaded by the participants
Figure FDA0002906501450000036
The participator and the perception service provider prove that the uploaded perception data are in a reasonable interval through interaction[a,b]Within the range;
s23, iZKM challenge: whenever a aware service provider receives participant wiSent commitment S0,iThe perceptual service provider then returns the value of the lower bound a and the value of the upper bound b of the evaluation range as a challenge to the participant;
s24, iZKM response: after the participants receive the challenge containing the values a and b sent by the perception service provider, the participants judge the perception data D of the participantsiWhether or not in [ a, b ]]Interval, if the perception data D of the participantiIn [ a, b ]]If the interval is not within the interval, the participant exits the task and returns to the perception service provider, the data quality evaluation of the participant is terminated, and if the perception data D of the participanti∈[a,b]Then the participant calculates
Figure FDA0002906501450000037
And
Figure FDA0002906501450000038
as a response to the challenge, wherein
Figure FDA0002906501450000039
And
Figure FDA00029065014500000310
are respectively
Figure FDA00029065014500000311
And
Figure FDA00029065014500000312
in the context of the confusion that is,
Figure FDA00029065014500000313
and
Figure FDA00029065014500000314
is to DiA and | b-DiHiding of |Tibetan, S1,iAnd S2,iResponses to the challenge lower limit a and upper limit b, respectively, and then transmitted (S)1,i,S2,i) To the aware service provider;
s25, iZKM validation evaluation: sensing the response returned by the service provider to the challenge based on the participant (S)1,i,S2,i) Verifying commitments submitted by participants S0,iBy calculating S1,i＝S0,i·(ga)-1mod p and S2,i＝gb·(S0,i)-1mod p，S0,i、S1,iAnd S2,iAre respectively the participant wiCommitment of constructs and response to challenges, (g)a)-1And gbIs a structural factor, (S)0,i)-1Is S0,iIn the reverse of the loop group G, a computational validation that is true indicates that the participant uses the same perceptual data values in constructing commitments and response challenges, that the perceptual service provider is not spoofed, and that the perceptual service provider trusts the perceptual data D uploaded by the participanti∈[a,b]The perception data uploaded by the participant proves the challenge-response protocol iZKM through zero knowledge of privacy protection data quality evaluation, otherwise the data quality evaluation of the participant is failed.
4. The data quality perception incentive method for privacy protection in community perception according to claim 1, wherein the step S3 comprises the following steps:
s31, participant wiData D ofiThe data quality assessment by the perceptual service provider satisfies the scope of requirements R of the task, and subsequently the perceptual service provider will satisfy the participants w of the data quality assessmentiInformation of
Figure FDA0002906501450000041
Is sent to the task publisher, wherein
Figure FDA0002906501450000042
The representation of an anonymous identity is represented,
Figure FDA0002906501450000043
represents the commitment of the construct while informing the participant wiData D ofiSatisfy reliability assessment of data quality, otherwise notify participant wiThe data evaluation fails, and the task is ended;
s32, the task publisher receives the participant w meeting the data quality evaluationiAfter the information, a prepayment request is sent
Figure FDA0002906501450000044
To a perceptual service provider, wherein
Figure FDA0002906501450000045
Is a prepayment to the participant;
s33, perception service provider receives and provides to participant wiImmediately after the prepayment, the participant w is notifiediSubmitting the perception data to a task publisher;
s34, participant wiEncrypted perception data Enc (D) after receipt of a prepayment noticei,pkd) And a random number Enc (r)i,pkd) And sending the task to the task publisher.
5. The data quality perception incentive method for privacy protection in community perception according to claim 1, wherein the step S4 comprises the following steps:
s41, the task publisher uses the private key skdDecrypting participant submitted data D'i＝Dec(Enc(Di,pkd),skd) And r'i＝Dec(Enc(ri,pkd),skd)；
S42, calculating by task publisher
Figure FDA0002906501450000046
Validating participant wiThe reliability of the submitted data is such that,
Figure FDA0002906501450000047
is that
Figure FDA0002906501450000048
In the context of the confusion that is,
Figure FDA0002906501450000049
is to D 'obtained after decryption'iIs hidden, D'iAnd r'iIs decrypted D'i＝Dec(Enc(Di,pkd),skd) And Dec (Enc (r)i,pkd),skd) The result of the acquisition is that,
Figure FDA00029065014500000410
is that the task publisher bases on the participant wiSubmitted data D'i＝Dec(Enc(Di,pkd),skd) And r'i＝Dec(Enc(ri,pkd),skd) Fabricated commitment as long as task publisher decrypts resulting data D'iAnd r'iSatisfy the requirement of
Figure FDA00029065014500000411
The submitted data meets the reliability, the surplus reward of the participants is paid, and the reward is refused to be paid if the verification is not passed;
s43, sending by the task publisher as long as the data passes the verification
Figure FDA0002906501450000051
To the aware service provider, informing the aware service provider whether the user is anonymous or not using the parameter
Figure FDA0002906501450000052
Paying;
s44 perception service provider as participant wiIssuing a true monetary amount
Figure FDA0002906501450000053
m is less than or equal to n, i is less than or equal to 1 and less than or equal to m, and m represents the number of users passing the verification of the task publisher.
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