CN114978492A - Privacy protection method for centralized space crowdsourcing task allocation in spatial information network - Google Patents
Privacy protection method for centralized space crowdsourcing task allocation in spatial information network Download PDFInfo
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Abstract
A privacy protection method for centralized space crowdsourcing task allocation in a space information network mainly solves the problems that in the prior art, when an untrusted server exists, the threat of leakage of privacy data of positions of workers is caused, and task allocation cannot be accurately performed. The method comprises the steps of constructing a centralized space crowdsourcing system; a worker maps the real position to generate a false position by adopting a pseudorandom function technology; the consistency of the real position and the false position of the worker is ensured by a zero knowledge proving method; the over-function encryption calculates the exact distance of the worker from the spatial crowdsourcing task. According to the invention, the task allocation based on the accurate distance is realized, so that the requirement of a position strategy with fine granularity is met, meanwhile, the safety of position privacy data of workers is enhanced, the matching degree of space crowdsourcing tasks and workers is improved, and the selectivity and efficiency of task allocation are obviously improved.
Description
Technical Field
The invention belongs to the technical field of networks, and further relates to a privacy protection method for centralized space crowdsourcing task allocation in a space information network in the technical field of space information networks. The method can be applied to a centralized space crowdsourcing task allocation application scene in the technical field of space information networks, and can complete task allocation under the condition of protecting position privacy.
Background
The space information network is a comprehensive information network which is formed by various spacecrafts, radio cellular information networks, data and command control centers and other ground facilities in a broad sense and integrates the space, the space and the ground. The satellite network is the backbone of the spatial information network, has high integration and can realize the comprehensive utilization of various resources. The space crowdsourcing is taken as a typical application mode in a space information network, and plays a role in the fields of emergency rescue, ecological environment dynamic monitoring, intelligent transportation and the like. The space crowdsourcing comprises three participants of a requester, a worker and a space crowdsourcing platform, and is a service mode for distributing tasks to workers meeting certain space constraints by fully utilizing crowd wisdom. Spatial crowdsourcing based on centralized management utilizes a satellite network to provide spatial crowdsourcing services. Various types of aircraft, such as users, smart devices, and drones, moving on the ground are requestors or workers. The requester submits a task request and a position strategy to the space crowdsourcing platform, the worker submits position information and answers to the space crowdsourcing platform, and then the platform conducts crowdsourcing management according to the information.
The spatial crowdsourcing platform needs to collect location information of all workers to meet basic services, and the server is not always completely trusted, which brings about a problem of privacy disclosure of the worker location. For the existing privacy protection method for space crowdsourcing task allocation, a worker generates a key to encrypt position information by a key issuing server to protect position privacy, and the method has the problems of complex key management and leakage of the position privacy of the worker due to the fact that the key issuing server is not credible. The differential privacy technology can protect the position privacy of the workers, and the method adds noise to the position information of the workers to make the positions indistinguishable, but the method not only increases the calculation overhead of the users, but also causes that the distance cannot be accurately calculated by the position ciphertext of the workers, and the task allocation efficiency is not high. Thus, centralized spatial crowdsourcing faces the technical problem of how to ensure worker location privacy and accomplish task distribution by calculating precise distances without server confidence.
The patent document of Shandong university in Shandong university ' applied for ' a space crowdsourcing task allocation privacy protection method and system ' (application number: 202111121645.7 application date: 2021.09.24 application publication number: CN113905047A) discloses a space crowdsourcing task allocation privacy protection method. The method is applied to protecting the privacy of the position of a worker and comprises the following steps: a worker submits identity information to a key issuing server for registration to obtain an encryption key; encrypting the worker message to obtain a message ciphertext, and submitting the ciphertext to a space crowdsourcing server; receiving a requester identity information ciphertext sent by a crowdsourcing server, and uploading a task worker grid coding set and a radius ciphertext to the crowdsourcing server after verifying the validity of the requester identity information ciphertext; and receiving final task information sent by the crowdsourcing server, and sending tracing information to the crowdsourcing server or sending task result information to the requester terminal. The method has the defects that in the initialization stage, when a worker submits identity information to a key issuing server for registration to obtain a private key used for encrypting position information, the problem that position privacy data of the worker is leaked due to the fact that the key issuing server is not trusted exists.
Shenzhen university discloses a task allocation method for privacy protection space crowdsourcing in the patent document 'a task allocation system model and implementation method for privacy protection space crowdsourcing' (application number: CN201710533457.2 application date: 2021.07.03 application publication number: CN 107257381A). The system model of the method comprises a space crowdsourcing server, a requester, a worker and a trusted third party, namely an encryption service providing unit. The requester creates and submits a task request to the server, the encryption service providing unit performs task allocation privacy protection management, and the server allocates the task to the worker. The method has the disadvantages that a trusted third party, namely an encryption service providing unit, is used for participating in space crowdsourcing to perform all privacy protection task allocation management, and the problem that the privacy data of the position of a worker is leaked due to the fact that the encryption service providing unit is not trusted exists; the scheme uses a paillier homomorphic encryption algorithm and an ElGamal cryptographic algorithm, and the calculation cost is high.
The patent document of the university of Fujian university in application "a spatial crowdsourcing method based on deep reinforcement learning and block chains" (application number: CN202110725729.5 application date: 2021.06.29 application publication number: CN113553613A) discloses a spatial crowdsourcing method based on deep reinforcement learning and block chains. According to the method, users are managed through a user trust management mechanism, spatial crowdsourcing tasks are managed through a method of classifying and managing the tasks in a grading mode, reliable workers are selected through a block chain, and task allocation is completed. The method ensures the position privacy of the user by combining the block chain and the deep reinforcement learning. The method has the disadvantages that the accurate distance between the worker and the spatial crowdsourcing task cannot be calculated, the matching degree between the crowdsourcing task and the worker can be reduced by distributing the task according to the fuzzy distance range, and the task distribution efficiency is low.
The paper "Geo-indicating Mechanisms for Spatial Crowdsourcing estimation Optimization" (Cryptographic and Security, Jan 2022) published by Shun Zhang et al proposes a method of Spatial Crowdsourcing location privacy protection based on geographical location indistinguishability. According to the method, noise is added to position information of a worker locally through a differential privacy technology, the worker submits a disturbed false position to a server to participate in space crowdsourcing, and the server performs privacy protection and task allocation efficiency balance through a self-adaptive regionalization fuzzy mechanism with an inference error boundary based on geographical indistinguishability. The method has the disadvantages that noise conforming to a differential privacy mechanism is added to the real position of a worker, the usability of the position data of the worker is reduced, the task allocation cannot be carried out by calculating an accurate distance, and the task allocation efficiency is reduced.
Disclosure of Invention
The invention aims to overcome the defects of the prior art, and provides a privacy protection method for centralized space crowdsourcing task allocation in a space information network, which is used for solving the technical problems that the position privacy of workers cannot be ensured and the task allocation according to an accurate distance cannot be completed under the condition that a server is not trusted in the centralized space crowdsourcing in the prior art.
The technical idea for realizing the purpose of the invention is as follows: the method comprises the steps that a worker maps a real position to generate a false position by adopting a pseudorandom function technology, the consistency of the real position and the false position of the worker is ensured through a zero-knowledge proof method, namely, the distances from the real position and the false position of the worker to a space crowdsourcing task are ensured to be the same, then, the false position information of the worker is encrypted by adopting an encryption algorithm of function encryption, and finally, the worker submits a ciphertext of the false position to a server to participate in space crowdsourcing. Because the false position information replaces the real position information, the server cannot deduce the real position information of the worker, and further the invention can realize the position privacy protection of the worker under the condition that the server is not trusted. The server calculates the ciphertext of the false position of the worker and the position ciphertext of the space crowdsourcing task by adopting a decryption algorithm of function encryption to obtain the accurate distance between the worker and the crowdsourcing task, and then the server distributes the task to the worker closest to the worker according to the accurate distance. Because the distances from the false position and the real position of the worker to the space crowdsourcing task are the same, the distance can be calculated by calculating the distance from the false position and the real position of the worker to replace the calculation of the distance by using the real position of the worker, so that the usability of the false position data of the worker is equivalent to that of the real position data of the worker, and the problems that only a distance range can be estimated after noise is added to worker position information by using a differential privacy technology, the task distribution cannot be performed by using an accurate distance, and the task distribution efficiency is reduced are solved.
In order to achieve the purpose, the technical scheme adopted by the invention comprises the following steps:
step 1, constructing a centralized spatial crowdsourcing system:
constructing a centralized space crowdsourcing system consisting of a server, a requester and n workers, wherein n is more than or equal to 2;
step 2, the requester generates a task request ciphertext;
step 3, the requester submits a task request ciphertext to the server:
step 3.1, the requester sends the task request ciphertext to the server;
step 3.2, the server broadcasts task request ciphertexts to all workers;
and 4, the server distributes the generated key of the function encryption algorithm to the requester and the worker:
step 4.1, the server generates public parameters by using an initialization algorithm of function encryption:
Setup(λ)→{p,G 1 ,G 2 ,G T ,g 1 ,g 2 ,e}
wherein Setup () represents the initialization algorithm of the function encryption, λ represents the security parameter of the server, → represents the algorithm output symbol, p represents the large prime number, G 1 、G 2 And G T Representing a cyclic group of order p, g 1 Represents G 1 G is a generator of 2 Represents G 2 E represents a bilinear mapping operation: g 1 ×G 2 →G T ；
Step 4.2, the server generates a first key and a second key by adopting a dual orthogonal basis generation algorithm:
wherein Dual (-) represents a Dual orthogonal basis generation algorithm,
and
a set of dual orthogonal bases is represented,
the representation base vector is 8-dimensional and each element in the base vector belongs to
Representing an integer field {0,1,2,. eta., p-1},
and
a set of dual orthogonal bases is represented,
the representation base vector is 2-dimensional and each element in the base vector belongs to an integer domain
Step 5, the requester submits the generated space crowdsourcing task position ciphertext to the server:
step 5.1, the requester generates a spatial crowdsourcing task position ciphertext { C 1 ,C 2 }：
Wherein, alpha,
Indicating that the requestor is from an integer domain
Wherein two independent uniform elements are randomly selected,
r 2 ＝-2x r ，r 3 ＝-2y r ，r 4 ＝1；
step 5.2, the requester submits the space crowdsourcing task position ciphertext to the server;
and 6, generating false position information corresponding to the real position information of each worker by using a pseudo-random function:
6.1, each worker decrypts the received task request ciphertext to obtain a task request plaintext;
step 6.2, generating a false position from the real position of each worker by using a pseudo-random function, wherein the distance from the false position to the space crowdsourcing task is the same as the distance from the real position to the space crowdsourcing task;
and 7, generating an evidence for the real position and the false position by each worker by adopting a zero-knowledge proof method:
π i ＝Prove(W i ',W i )
wherein, Prove (·) represents the evidence generation algorithm of the non-interactive zero-knowledge proof method, W i ' real position plane coordinates, W, of the ith worker i Is represented by the formula and i ' the corresponding dummy location coordinates of the location,
the abscissa representing the ith worker false location,
a vertical coordinate representing the ith worker false location;
and 8, submitting the generated ciphertext of the false position to a server by each worker:
step 8.1, each worker generates a location ciphertext { V } i1 ,V i2 }：
Wherein the content of the first and second substances,
w i1 ＝1，
step 8.2, each worker sends the position ciphertext, the verification material and the evidence to a server;
step 9, the server assigns the task to the nearest worker according to the precise distance:
step 9.1, the server calculates the distance between each worker and the space crowdsourcing task position by using a decryption algorithm of function encryption:
D i1 ＝e(C 1 ,V i1 )，
D i2 ＝e(C 2 ,V i2 )，
wherein v is i Representing the distance of the ith worker from the spatial crowdsourcing task location;
9.2, the server selects the minimum distance from all the distances and distributes the task to the worker closest to the distance;
9.3, the server sends the task allocation result and the verification parameters to the requester;
step 10, the requester verifies the task allocation result:
step 10.1, the requester verifies whether the proof of the nearest worker meets Verify (π) m ,W m ) If yes, executing step 10.2; otherwise, the requester refuses to accept the task allocation result and terminates the protocol; wherein, Verify () represents evidence verification algorithm of non-interactive zero knowledge proof, pi m Evidence representing recent workers, W m False location coordinates representing the nearest worker;
step 10.2, the requestor verifies whether Ver is satisfied s ＝Ver r If yes, the requester receives the task distribution result, and the protocol is ended; otherwise, terminating the protocol; wherein, Ver s Representing server-generated authentication parameters, Ver r Representing a requestor-generated authentication parameter;
and step 11, the requester receives the task distribution result and the protocol is ended.
Compared with the prior art, the invention has the following advantages:
in the invention, a worker uses a pseudorandom function to map a real position to generate a false position, an evidence is generated for the real position and the false position of the worker by a zero-knowledge proof method, then the false position information of the worker is encrypted by using an encryption algorithm of function encryption, and the worker submits a ciphertext of the false position to a server to participate in space crowdsourcing. Because the false position information replaces the real position information, the server can not predict the real position information of the worker, so that the invention can also realize the position privacy protection of the worker under the condition that the server is not trusted, overcomes the threat of leakage of position privacy data of the worker caused by the existence of an untrusted server in the prior art, enhances the safety of the position privacy data of the worker, further remarkably improves the participation degree of the worker in the space crowdsourcing, and ensures that the task allocation selectivity is more and the result is more optimal.
And 2, because the server adopts a decryption algorithm of function encryption to calculate the ciphertext of the false position of the worker and the position ciphertext of the spatial crowdsourcing task to obtain the accurate distance between the worker and the crowdsourcing task, and then the server distributes the task to the worker closest to the worker according to the accurate distance.
Drawings
FIG. 1 is a flow chart of an implementation of the present invention;
fig. 2 is a schematic structural diagram of a spatial crowdsourcing system used in the present invention.
Detailed Description
The invention is described in further detail below with reference to the figures and specific examples.
The implementation steps of the present invention are further described with reference to fig. 1 and the embodiment.
Step 1, constructing a centralized space crowdsourcing system.
Embodiments of the present invention build a centralized spatial crowdsourcing system comprising one requester, five workers and one server. As shown in FIG. 2, the system of FIG. 2 includes one requester, five workers, and one server. The main task of the requester is to submit a task request ciphertext and a task position ciphertext to the server; the main task of the worker is to submit a false location ciphertext to the server; the main task of the server is to broadcast task request ciphertext to the workers and send task assignment results to the requesters.
And 2, the requester generates a task request ciphertext.
The requester generates a task request ciphertext C ═ Enc (GK, R | | | h | | | epoch #), wherein Enc (·) represents a pair-based basisThe broadcast encryption algorithm is called a key, GK represents a group key of the broadcast encryption algorithm, R represents the position plane coordinate of a space crowdsourcing task determined by a requester according to a global positioning system, and R is (x) r ,y r )，x r Indicating the position abscissa, y, of the crowd-sourced task r The position ordinate of the crowdsourcing task is represented, | | represents a cascading symbol, h represents the upper limit of the distance from each worker to the position of the spatial crowdsourcing task, h is 100 in the embodiment of the invention, and the epoch # represents the time stamp of the moment when the requester generates the task request ciphertext.
And 3, submitting the task request ciphertext to the server by the requester.
And 3.1, the requester sends the task request ciphertext to the server.
And 3.2, broadcasting the task request cryptograph to all workers by the server.
And 4, the server distributes the generated key of the function encryption algorithm to the requester and the worker.
Step 4.1, the server generates its common parameter, Setup (λ) → { p, G, using the initialization algorithm for function encryption 1 ,G 2 ,G T ,g 1 ,g 2 E, where Setup () denotes the initialization algorithm for functional encryption, λ denotes the security parameter of the server, → denotes the algorithm output sign, p denotes the large prime number, G 1 、G 2 And G T Representing a cyclic group of order p, g 1 Represents G 1 G is a generator of 2 Represents G 2 E represents a bilinear mapping operation: g 1 ×G 2 →G T 。
Step 4.2, the server adopts a dual orthogonal basis generation algorithm to generate a first secret key of the server
And a second key
Wherein Dual (-) represents a Dual orthogonal basis generation algorithm,
and
a set of dual orthogonal bases is represented,
the representation base vector is 8-dimensional and each element in the base vector belongs to
Representing an integer field {0,1,2,. eta., p-1},
and
a set of dual orthogonal bases is represented,
the representation base vector is 2-dimensional and each element in the base vector belongs to an integer domain
Step 4.3, the server sends the public parameters and the key to the requester and all workers simultaneously.
And 5, submitting the generated space crowdsourcing task position ciphertext to a server by the requester.
Step 5.1, the requester generates a spatial crowdsourcing task position ciphertext { C 1 ,C 2 }，
Wherein, alpha,
Indicating that the requester is from an integer domain
Wherein two independent uniform elements are randomly selected,
r 2 ＝-2x r ，r 3 ＝-2y r ，r 4 ＝1。
step 5.2, the requester submits the space crowdsourcing task position ciphertext { C to the server 1 ,C 2 }。
And 6, generating false position information corresponding to the real position information of each worker by using a pseudo-random function.
And 6.1, each worker decrypts the received task request ciphertext by using the session key by using a decryption algorithm corresponding to the broadcast encryption algorithm to obtain a task request plaintext { R | | h | epoch # }.
And 6.2, generating a false position from the real position of each worker by using a pseudorandom function, wherein the distance from the false position to the space crowdsourcing task is the same as the distance from the real position to the space crowdsourcing task.
And 7, generating an evidence for the real position and the false position by each worker by adopting a zero-knowledge proof method.
Each worker generates evidence pi for real and ghost locations i Wherein, is i ＝Prove(W i ',W i ) Prove (-) represents the evidence generation algorithm of the non-interactive zero knowledge proof method, W i ' denotes the real position plane coordinates, W, determined by the ith worker from the Global positioning System i Is represented by the formula i ' the corresponding dummy location coordinates of the location,
the abscissa representing the ith worker false location,
the ordinate representing the ith worker false location.
And 8, submitting the generated ciphertext of the false position to a server by each worker.
Step 8.1, each worker follows
Generating worker location ciphertext { V i1 ,V i2 In which is beta i 、
w i1 ＝1，
Step 8.2, each worker follows
Calculating the material required for the verification step, wherein ID i The identity identifier of the ith worker is represented, the MAC represents a message verification code algorithm, and the MAC algorithm selected in the embodiment of the invention is an Hmac-MD5 algorithm, k i A session key representing broadcast encryption of the ith worker, F (-) represents a one-way function, in the embodiment of the invention, RSA is selected as the one-way function, h-v i Representing the ith worker pair
Is carried out h-v i The operation of the sub-one-way function,
indicating that the worker performed a MAC operation on the timestamp,
step 8.3, each worker will contain the proof and proof of the location ciphertext
And sending the data to a server.
Step 9, the server assigns the task to the nearest worker according to the precise distance.
Step 9.1, the server uses the decryption algorithm D of the function encryption i1 ＝e(C 1 ,V i1 )，D i2 ＝e(C 2 ,V i2 )，
Calculating the distance v of each worker from the spatial crowd-sourced task location i ，v i Representing the distance between the ith worker and the spatial crowd sourcing task.
And 9.2, selecting the minimum distance from all the distances by the server, and distributing the task to the worker closest to the distance.
Step 9.3, the server generates a verification parameter
Where pi represents the successive multiplication symbol, mod represents the modulo operation, and p and q represent two large prime numbers in the one-way function RSA, respectively.
Step 9.4, the server distributes the task results and verifies the required materials
Is sent to the requester, wherein v m The minimum distance is represented as a function of,
the verification material representing the worker closest in distance,
ID m representing the identity of the worker closest to it.
Step 10, the requester verifies the task allocation result.
Step 10.1, the requester verifies the worker closest in distanceWhether the evidence satisfies Verify (pi) m ,W m ) If yes, executing step 10.2; otherwise, the requester refuses to accept the task allocation result and terminates the protocol; wherein Verify () is the proof verification algorithm of the non-interactive zero knowledge proof.
Step 10.2, the requestor verifies whether Ver is satisfied s ＝Ver r If yes, executing step 11; otherwise, terminating the protocol; wherein, Ver r Indicating the authentication parameters generated by the requestor,
indicating that the requester performs a MAC operation on the timestamp,
and step 11, the requester receives the task allocation result and the protocol is ended.
The foregoing description is only an example of the present invention and should not be construed as limiting the invention in any way, and it will be apparent to those skilled in the art that various modifications and variations can be made in form and detail without departing from the spirit and structure of the invention, after understanding the principles and principles of the invention, but such modifications and variations are considered to be within the scope of the appended claims.
Claims (6)
1. A privacy protection method for distributing centralized space crowdsourcing tasks in a space information network is characterized in that workers submit false position information to participate in space crowdsourcing, a server calculates the accurate distance between the workers and the space crowdsourcing tasks according to the false position information to distribute the tasks, and the method specifically comprises the following steps:
step 1, constructing a centralized space crowdsourcing system consisting of a server, a requester and n workers, wherein n is more than or equal to 2;
step 2, the requester generates a task request ciphertext;
step 3, the requester submits a task request ciphertext to the server:
step 3.1, the requester sends the task request ciphertext to the server;
step 3.2, the server broadcasts task request ciphertexts to all workers;
and 4, the server distributes the generated key of the function encryption algorithm to the requester and the worker:
step 4.1, generating public parameters of the server by using the initialization algorithm encrypted by the following functions:
Setup(λ)→{p,G 1 ,G 2 ,G T ,g 1 ,g 2 ,e}
wherein Setup () represents the initialization algorithm of the function encryption, λ represents the security parameter of the server, → represents the algorithm output symbol, p represents the large prime number, G 1 、G 2 And G T Representing a cyclic group of order p, g 1 Represents G 1 G is a generator of 2 Represents G 2 E represents a bilinear mapping operation: g 1 ×G 2 →G T ；
Step 4.2, generating a first key and a second key of the server by adopting the following dual orthogonal basis generation algorithm:
wherein Dual (-) represents a Dual orthogonal basis generation algorithm,
and with
A set of dual orthogonal bases is represented,
the representation base vector is 8-dimensional, and each element in the base vector belongs to
Representing an integer field {0,1,2,. eta., p-1},
and
a set of dual orthogonal bases is represented,
the representation base vector is 2-dimensional and each element in the base vector belongs to an integer domain
And 5, submitting the generated space crowdsourcing task position ciphertext to a server by the requester:
step 5.1, the requester generates a spatial crowdsourcing task position ciphertext { C 1 ,C 2 }：
Wherein the content of the first and second substances,
indicating that the requestor is from an integer domain
Wherein two independent uniform elements are randomly selected,
r 2 ＝-2x r ，r 3 ＝-2y r ，r 4 ＝1；
step 5.2, the requester submits the space crowdsourcing task position ciphertext to each worker from the server;
and 6, generating false position information corresponding to the real position information of each worker by using a pseudo-random function:
6.1, each worker decrypts the received task request ciphertext to obtain a task request plaintext;
step 6.2, generating a false position from the real position of each worker by using a pseudorandom function, wherein the distance from the false position to the space crowdsourcing task is equal to the distance from the real position to the space crowdsourcing task;
and 7, generating an evidence for the real position and the false position of each worker by adopting the following zero-knowledge proof method:
π i ＝Prove(W i ',W i )
wherein, Probe (-) represents the evidence generation algorithm of the non-interactive zero knowledge proof of knowledge method, W i ' denotes the true location of the ith worker, W i Is represented by the formula i ' a corresponding dummy location of the dummy,
an abscissa value representing the ith worker false location,
a vertical coordinate value representing the ith worker false location;
and 8, submitting the generated ciphertext of the false position to a server by each worker:
step 8.1, each worker generates a location ciphertext { V } i1 ,V i2 The method comprises the following steps:
wherein the content of the first and second substances,
w i1 ＝1，
step 8.2, each worker sends the position ciphertext, the verification material and the evidence to a server;
and 9, the server distributes tasks for the workers:
step 9.1, the server calculates the distance between each worker and the spatial crowdsourcing task position by using a decryption algorithm of function encryption:
D i1 ＝e(C 1 ,V i1 )，
D i2 ＝e(C 2 ,V i2 )，
wherein v is i Representing the distance of the ith worker from the spatial crowd-sourced task location;
9.2, the server selects the minimum distance from all the distances and distributes the task to the worker closest to the distance;
9.3, the server sends the task allocation result and the verification parameters to the requester;
step 10, the requester verifies the task allocation result:
step 10.1, the requester verifies whether the proof of the nearest worker satisfies Verify (π) m ,W m ) If yes, executing step 10.2; otherwise, the requester refuses to accept the task allocation result and terminates the protocol; wherein, Verify () represents evidence verification algorithm of non-interactive zero knowledge proof, pi m Showing evidence of the worker who obtained the task assignment, W m Representing obtaining false location coordinates of a task distributor;
step 10.2, the requestor verifies whether Ver is satisfied s ＝Ver r If yes, executing step 11; otherwise, terminating the protocol; wherein, Ver s Representing authentication parameters, Ver, of the server r An authentication parameter representing a requestor;
and step 11, the requester receives the task distribution result and the protocol is ended.
2. The privacy protection method for centralized spatial crowd-sourced task distribution in a spatial information network as claimed in claim 1, wherein: the task request ciphertext in step 2 is obtained by the following formula:
C＝Enc(GK,R||h||epoch#)
where C denotes a task request ciphertext generated by the requester, Enc (·) denotes a broadcast encryption algorithm based on a symmetric key, GK denotes a group key of the broadcast encryption algorithm, R denotes a spatial crowd-sourced task position of the requester, and R ═ x (x) r ,y r )，x r Indicating the position abscissa, y, of the crowd-sourced task r Represents the position ordinate of the crowdsourcing task, | | represents the cascade symbol, h represents the upper limit of the distance from each worker to the position of the spatial crowdsourcing task, and etcoh # represents the requestThe requester generates a time stamp of the task request ciphertext time.
3. The privacy protection method for centralized spatial crowdsourcing task distribution in a spatial information network according to claim 2, characterized in that: the task request plaintext in step 6.1 is as follows:
{R||h||epoch#}。
4. the privacy protection method for centralized spatial crowd-sourced task distribution in a spatial information network as claimed in claim 2, wherein: the verification material described in step 8.2 is determined by the following formula:
wherein, ID i Identity identifier, k, representing the ith worker i Session key representing broadcast encryption of the ith worker, F (-) represents the one-way function RSA, h-v i Representing the ith worker pair
Is carried out h-v i The operation of the sub-one-way function,
indicating that the worker performed a MAC operation on the timestamp, MAC indicates a message authentication code algorithm,
5. the privacy protection method for centralized spatial crowd-sourced task distribution in a spatial information network as claimed in claim 4, wherein: the verification parameters described in step 9.3 are derived from the following formula:
where pi represents the successive multiplication symbol, mod represents the modulo operation, and p and q represent two large prime numbers in the one-way function RSA, respectively.
6. The privacy protection method for centralized spatial crowd-sourced task distribution in a spatial information network as claimed in claim 4, wherein: the authentication parameters of the supplicant described in step 10.2 are determined by:
wherein the content of the first and second substances,
indicating that the requester performs a MAC operation on the timestamp,
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