A commitment-based data range proof method in the Internet of Things

Abstract

The present invention discloses a data range certification method based on commitment in the Internet of Things. Based on commitment, a data range certification model with privacy protection is proposed, wherein the data requester first gives the range of data to be certified, and calculates the upper and lower bounds of the data range. The commitment value is sent to the cloud server for later data range certification. Then, the cloud server, as a verifier, obtains the data commitment value from the mobile user, and interacts with the data requester to verify whether the data submitted by the mobile user meets the data range required by the data requester. If the data is within the range, it means that the data meets the requirements and the verification is passed. Otherwise, the data does not meet the requirements and the verification fails. Compared with the prior art, the present invention can prevent malicious mobile users from uploading task data that does not meet the range requirements to damage the task results; improve the accuracy of the task results; realize the data range certification with privacy protection, and improve the certification speed.

Description

Technical Field

[0001] The present invention relates to the technical field of data security in the Internet of Things, and in particular to a data range certification method based on commitment in the Internet of Things. Background Art

[0002] With the development of sensors and embedded devices, mobile Internet of Things technology has attracted the attention of many applications due to its advantages in data tasks, data collection and data analysis [RKGanti, F.Ye, and H.Lei, "Mobile crowdsensing: Current state and future challenges," IEEE Communications Magazine, vol.49, no.11, pp.32–39, 2011.]. For example, crowdsourcing, location-based services and environmental detection. However, with the widespread application of Internet of Things technology, more and more mobile users are participating in it. The problems that come with it are also endless. The open, sparse and highly dynamic nature of the network environment makes it impossible to guarantee the reliability of mobile users participating in the task. Specifically, mobile users may submit incorrect task data that does not meet scope requirements, thus undermining the accuracy of task results [J.Ni, K.Zhang, Q.Xia, X.Lin, and XSShen, “Enabling strong privacypreservation and accurate task allocation for mobile crowdsensing,” IEEE Transactions on Mobile Computing, vol.19, no.6, pp.1317–1331, 2019.].

[0003] In response to the above problems, Zhao et al. [B.Zhao,S.Tang,X.Liu,and X.Zhang,“Pace:Privacy-preserving and quality-aware incentive mechanism for mobile crowdsensing,”IEEE Transactions on Mobile Computing,vol.20,no.5,pp.1924–1939,2020.] proposed a corresponding solution for the range proof of privacy-preserving task data. Although the range proof of privacy-preserving task data was achieved, its computational and communication overheads were large. Summary of the invention

[0004] In order to realize the scope proof of task data and reduce the computing overhead and communication overhead of mobile users at the same time, the present invention proposes a commitment-based data scope proof method in the Internet of Things.

[0005] The technical solution of the present invention is implemented as follows: a data range certification method based on commitment in the Internet of Things, comprising the steps of:

[0006] S1: The trusted center generates two large prime numbers p and q, and satisfies q|p-1. At the same time, it generates two generators g and h of the cyclic group G of order q, and distributes public and private keys to data requesters, cloud servers, and mobile users through secure channels.

[0007] S2, the data requester acts as a task distributor and uses the public key of the cloud server to encrypt the task request and send the encrypted ciphertext to the cloud server. The cloud server re-encrypts the ciphertext to obtain the re-encrypted ciphertext and then distributes the re-encrypted ciphertext to the mobile users.

[0008] S3, after receiving the ciphertext, the mobile user decrypts it to obtain the task request. The mobile user who wants to participate in the task uses its own sensors to sense the task data and submits the task data to the cloud server and the data requester in ciphertext, including the following steps:

[0009] S31, the mobile user obtains the task data d through the corresponding sensor. If d is a decimal, it is converted into a corresponding integer in the subsequent calculation, that is,

[0010] S32, select a random number r and

[0011] S33, calculate the commitment value Com of task data d d =g d ·h r mod p, and Com d Send to cloud server;

[0012] S34, the mobile user encrypts the random number r with the public key of the data requester, and the ciphertext is recorded as C r , encrypt the task data d, and record the ciphertext as C d , and C r and C d Sent to the data requester;

[0013] S4, after the mobile user who wants to participate in this task submits the task data, the cloud server needs to verify whether the submitted data meets the scope requirements of the task data, including the following steps:

[0014] S41, the cloud server calculates the result commitment through data commitment and data range commitment in

[0015] S42, the data requester receives the ciphertext C of the task data d After that, first decrypt the task data d, if d≤d l or d≥d u The task data does not meet the data range requirements, and the data requester terminates the calculation. l ≤d≤d u , the data requester calculates and And {Cm 1 ,Cm 2}Send to cloud server;

[0016] S43, the server verifies whether the task data of the mobile user meets the data range requirement through equation (1)

[0017]

[0018] If equation (1) holds true, it means that the task data submitted by the mobile user meets the data range requirement;

[0019] Step S5: The cloud server selects mobile users that meet the data range requirements as participants;

[0020] Step S6: The cloud server aggregates the task data submitted by the participants, calculates the task results using the corresponding method, and sends the task results to the data requester.

[0021] Furthermore, in step S2, the data requester distributes data tasks through the cloud server, and the data task data includes but is not limited to temperature, humidity, and longitude and latitude.

[0022] The beneficial effects of the present invention are that, compared with the prior art, the present invention can prevent malicious mobile users from uploading task data that does not meet the range requirements and damaging the task results by verifying whether the data submitted by the mobile user to the cloud server meets the data range requirements; by verifying whether the task data meets the data range requirements, the accuracy of the task results is improved; and the data range proof with privacy protection is realized, the proof speed is improved, and it is more in line with the social needs of existing Internet of Things applications. BRIEF DESCRIPTION OF THE DRAWINGS

[0023] Figure 1 The present invention is a flowchart of a data range certification method based on commitment in the Internet of Things. DETAILED DESCRIPTION

[0024] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0025] See also Figure 1 The present invention provides a commitment-based data range proof method in the Internet of Things with three main participants, namely, the data requester, the cloud server and the mobile user. The communication between them can adopt either wireless communication or wired communication, wherein the data requester is mainly responsible for distributing tasks; the cloud server is mainly responsible for verifying whether the task data submitted by the mobile user meets the data range requirements, calculating the task results and sending them to the data requester; the mobile user is mainly responsible for uploading his or her own task data to the cloud server.

[0026] The invention of the data range proof method based on commitment in the Internet of Things is based on a privacy-protected data range proof model proposed based on commitment: first, the mobile user commits to the task data and obtains the commitment value, and sends the corresponding commitment value to the cloud server for later data range verification; then, the cloud server, as a verifier, obtains the data commitment value from the mobile user, and interacts with the data requester to verify whether the data submitted by the mobile user to the cloud server meets the task data range requirements. If the task data range is met, it means that the data meets the requirements and the verification is passed, otherwise, the data does not meet the requirements and the verification fails; finally, the cloud server selects the mobile user who has passed the verification as a participant, obtains the task result by calculating the submitted data, and sends it to the data requester.

[0027] The present invention discloses a data range certification method based on commitment in the Internet of Things, which includes six stages: system establishment, task distribution, mobile user recruitment, task data verification, mobile user selection, and task data submission, which correspond to steps S1-S6 of the technical solution of the present invention. In the system establishment stage, a public parameter is first generated by a trusted center, specifically two large prime numbers p and q are generated, and q|p-1 is satisfied, and at the same time, two generators g and h of a cyclic group G of order q are generated; in the task distribution stage, a data requester distributes data task requests to mobile users; in the mobile user recruitment stage, a mobile user who wants to participate in the task sends a commitment value of the task data to a cloud server; in the task data verification stage, the cloud server and the data requester interact to verify whether the task data submitted by the mobile user meets the data range requirements; in the mobile user selection stage, the cloud server selects users whose submitted task data meets the data range requirements as participants; in the task data submission stage, the cloud server calculates the task data submitted by the participants and sends the calculation results to the data requester.

[0028] The following takes the data requester collecting temperature data of a certain place as an example to illustrate the technical solution of the present invention. At this time, the public and private keys of the data requester are (pk r ,sk r ), the public and private keys of the cloud server are (pk c ,sk c ), the public and private keys of the mobile user are (pk u ,sk u ).

[0029] In step S1, the trusted center generates two large prime numbers p and q, and satisfies q|p-1. At the same time, it generates two generators g and h of the cyclic group G of order q, and distributes public and private keys to data requesters, cloud servers, and mobile users through a secure channel. The role of the trusted center is only to generate public and private keys for data requesters, cloud servers, and mobile users in the initial stage, and it basically does not participate in the subsequent steps, so it is not shown in the example diagram.

[0030] In step S2, the data requester uses the public key pk of the cloud server c The encryption task T, the specific content of T is m (i.e. the collection of temperature data at a certain place), that is And C m After receiving the task, the cloud server re-encrypts the task content to ensure the privacy of the task content and distributes the re-encrypted ciphertext to mobile users;

[0031] In step S3, after the mobile user decrypts and obtains the task content, the mobile user who is willing to participate in the task submits the committed value of the temperature data and the corresponding parameters to the cloud server and the data requester. The steps for the mobile user to submit the temperature data d include:

[0032] S31, the mobile user obtains the task data (temperature data) d through the corresponding sensor. If d is a decimal, it is converted into a corresponding integer in the subsequent calculation, that is,

[0033] S32, select a random number r and

[0034] S33, calculate the commitment value Com of task data d d =g d ·h r mod p, and Com d Send to cloud server;

[0035] S34, for the convenience of verification, the mobile user encrypts the random number r with the public key of the data requester, and the ciphertext is recorded as C r ,Right now Encrypted temperature data d, ciphertext is recorded as C d ,Right now And C r and C d Sent to the data requester;

[0036] The specific process of the cloud server verifying the temperature data d in step S4 is:

[0037] S41, after receiving the task data submitted by the mobile user, the cloud server calculates the result commitment through data commitment and data range commitment in

[0038] S42, the data requester receives the ciphertext C of the task data d After that, first decrypt to obtain the task data d, that is If d≤d l or d≥d u The task data does not meet the data range requirements, and the data requester terminates the calculation. l ≤d≤d u , the data requester calculates and And {Cm 1 ,Cm 2}Send to cloud server;

[0039] S43, the cloud server verifies whether the task data of the mobile user meets the data range requirement through equation (1)

[0040]

[0041] If equation (1) holds true, it means that the task data submitted by the mobile user meets the data range requirements.

[0042] In step S5, the cloud server selects mobile users whose task data meets the data range requirement as participants.

[0043] In step S6, the cloud server aggregates the temperature data submitted by the participants, uses the corresponding algorithm to calculate the final temperature of the location and sends it to the data requester.

[0044] In the data range proof method based on commitment in the Internet of Things of the present invention, the data of mobile users are presented in the form of commitment during the interaction process. Therefore, the method realizes the range proof of user data under the condition of privacy protection, and experiments show that this method improves the efficiency of data range proof, is feasible within the range of integers, and can meet the needs of user response. At the same time, the data range proof method based on commitment in the Internet of Things proposed by the present invention realizes the data range proof based on privacy protection, improves the proof speed, and is more in line with the social needs of existing Internet of Things applications.

[0045] The above is a preferred embodiment of the present invention. It should be pointed out that a person skilled in the art can make several improvements and modifications without departing from the principle of the present invention. These improvements and modifications are also considered to be within the scope of protection of the present invention.

Claims

1. A commitment-based data range proof method in the Internet of Things, characterized in that: Includes steps: S1: The trusted center generates two large prime numbers p and q, and satisfies q|p-1. At the same time, it generates two generators g and h of the cyclic group G of order q, and distributes public and private keys to data requesters, cloud servers, and mobile users through secure channels. S2, the data requester acts as a task distributor and uses the public key of the cloud server to encrypt the task request and send the encrypted ciphertext to the cloud server. The cloud server re-encrypts the ciphertext to obtain the re-encrypted ciphertext and then distributes the re-encrypted ciphertext to the mobile users. S3, after receiving the ciphertext, the mobile user decrypts it to obtain the task request. The mobile user who wants to participate in the task uses its own sensors to sense the task data and submits the task data to the cloud server and the data requester in ciphertext, including the following steps: S31, the mobile user obtains the task data d through the corresponding sensor. If d is a decimal, it is converted into a corresponding integer in the subsequent calculation, that is, S32, select a random number r and S33, calculate the commitment value Com of task data d d =g d ·h r mod p, and Com d Send to cloud server; S34, the mobile user encrypts the random number r with the public key of the data requester, and the ciphertext is recorded as C r , encrypt the task data d, and record the ciphertext as C d , and C r and C d Sent to the data requester; S4, after the mobile user who wants to participate in this task submits the task data, the cloud server needs to verify whether the submitted data meets the scope requirements of the task data, including the following steps: S41, the cloud server calculates the result commitment through data commitment and data range commitment in S42, the data requester receives the ciphertext C of the task data d After that, first decrypt the task data d, if d≤d l or d≥d u The task data does not meet the data range requirements, and the data requester terminates the calculation. l ≤d≤d u , the data requester calculates and And send {Cm1,Cm2} to the cloud server; S43, the server verifies whether the task data of the mobile user meets the data range requirement through equation (1) If equation (1) holds true, it means that the task data submitted by the mobile user meets the data range requirement; Step S5: The cloud server selects mobile users that meet the data range requirements as participants; Step S6: The cloud server aggregates the task data submitted by the participants, calculates the task results using the corresponding method, and sends the task results to the data requester.

2. The method for proving data range based on commitment in the Internet of Things according to claim 1, characterized in that: In step S2, the data requester distributes data tasks through the cloud server, and the data task data includes but is not limited to temperature, humidity, and longitude and latitude.

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