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

Abstract

The present invention discloses a data tamper-proof method based on commitment in the Internet of Things, comprising the steps of: a mobile user commits to corresponding data to obtain a commitment value, and sends the commitment value to a cloud server for later data tampering verification; 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 is consistent with the data submitted to the data requester, if the data is consistent, it means that the data has not been tampered with and the verification is passed, otherwise, the data has been tampered with and the verification fails. In the present invention, the data of the mobile user are all presented in the form of commitment during the interaction process, the user data is tamper-proof under the condition of privacy protection, and the efficiency of data verification is improved, which is feasible within the range of integers and can meet the needs of user response.

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 tamper-proof 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 privacy and security of mobile users participating in the task. Specifically, the task data submitted by mobile users may be tampered with by malicious persons during transmission, destroying the accuracy of the task results [J.Ni,A.Zhang,X.Lin,and XSShen,“Security,privacy,and fairnessin fog-based vehicular crowdsensing,”IEEE Communications Magazine,vol.55,no.6,pp.146–152,2017.].

[0003] In response to the above problems, Sun et al. [G.Sun, S.Sun, H.Yu, and M.Guizani, "Towardincentivizing fogbased privacy-preserving mobile crowdsensing in the Internet of Vehicles," IEEE Internet of Things Journal, vol.7, no.5, pp.4128–4142, 2019.] and 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 corresponding solutions for the privacy protection of task data, but the following two problems still exist: (1) Although the privacy protection of task data is achieved, its computational overhead and communication overhead are relatively large; (2) The above scheme does not fully consider whether the task data has been tampered with. Among them, Zhao et al. considered the problem that there may be inconsistencies between the task data submitted by mobile users to the cloud server and the data requester, and adopted a secondary authentication method to achieve tamper-proof task data, but it also increased the computational overhead and communication overhead of various participants. Summary of the invention

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

[0005] The technical solution of the present invention is implemented as follows: a data tamper-proof 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 The data sent to the cloud server is committed to the cloud server as Com d =g d ·h r mod p;

[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′. If the data d has not been tampered with, then d′=d, and the ciphertext is recorded as C d′ , and C r and C d′ The data commitment sent to the data requester is recorded as Com d′ =g d′ ·h r′ mod p;

[0013] S4, after the mobile user who wants to participate in this task submits the task data, the cloud server verifies whether the submitted data is consistent, including the following steps:

[0014] S41. Data requester Randomly select parameters ω, η, η′ and calculate Com1 = g ω ·h η mod p, Com2 = g ω ·h η′ mod p and H = Hash(Com1||Com2), then the data requester decrypts C with his own private key r Get the random number r and decrypt C d′ Get the task data d′ and calculate D = ω + H·d′, D1 = η + H·r′ and D2 = η′ + H·r, where Hash() is a hash function. After the calculation is completed, the data requester sends {H, D, D1, D2, Comd′} to the cloud server;

[0015] S42, the cloud server receives {H, D, D1, D2, Com d′}After that, use the existing task data to commit to Com d Verify the task data submitted by the mobile user. The specific verification equation is as follows:

[0016]

[0017] If the cloud server verification is successful, it means that the data submitted by the mobile user to the cloud server is consistent with the data requester’s data, and there is no tampering by the adversary or deception by the mobile user;

[0018] S5, the cloud server selects the verified mobile user as a participant;

[0019] S6, the cloud server calculates the task result based on the submitted task data and sends it to the data requester.

[0020] 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.

[0021] The beneficial effect of the present invention is that, compared with the prior art, the present invention can verify whether the data submitted by the mobile user to the cloud server and the data requester are consistent and whether they are tampered with during the transmission process, thereby preventing malicious mobile users from destroying the task results; improving the accuracy of the task results; reducing the computing overhead and communication overhead of the mobile user, and being able to further meet the needs of lightweight mobile users. BRIEF DESCRIPTION OF THE DRAWINGS

[0022] Figure 1 The present invention is a flowchart of a data tamper-proof method based on commitment in the Internet of Things. DETAILED DESCRIPTION

[0023] 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.

[0024] See also Figure 1The invention idea of ​​a data tamper-proof method based on commitment in the Internet of Things is a data range proof model of privacy protection 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 verified mobile user as a participant, obtains the task result by calculating the submitted data, and sends it to the data requester.

[0025] The present invention discloses a data tamper-proof 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, corresponding to steps S1-S6. 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. At the same time, two generators g and h of the cyclic group G of order q are generated; in the task distribution stage, the data requester distributes data task requests to mobile users; in the mobile user recruitment stage, mobile users who want to participate in the task send the commitment value of the task data to the cloud server and the data requester at the same time; in the task data verification stage, the cloud server and the data requester interactively verify whether the task data submitted by the mobile user is consistent and whether it has been tampered by a malicious person during transmission; in the mobile user selection stage, the cloud server selects users with consistent task data and no tampering as participants; in the task data submission stage, the cloud server calculates the task data submitted by the participant and sends the calculation result to the data requester.

[0026] The following uses the example of a data requester collecting temperature data of a certain place to illustrate the technical solution of the present invention.

[0027] A commitment-based data tamper-proof method in the Internet of Things, comprising the steps of:

[0028] 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.

[0029] In step S2, the data requester uses the public key pk of the cloud server cThe 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.

[0030] In step 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 the sensor equipped by itself to perceive the task data and submits the task data d to the cloud server and the data requester in the form of ciphertext, including the following steps:

[0031] S31, the mobile user obtains task data d (temperature data) through the corresponding sensor. If d is a decimal, it is converted into a corresponding integer in the subsequent calculation, that is,

[0032] S32, select a random number r and

[0033] S33, calculate the commitment value Com of task data d d =g d ·h r mod p, and Com d The data commitment sent to the cloud server and the data requester is recorded as Com d =g d ·h r mod p

[0034] 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′. If the data d has not been tampered with, then d′=d, and the ciphertext is recorded as C d′ , and C r and C d′ The data commitment sent to the data requester is recorded as Com d′ =g d′ ·h r′ mod p;

[0035] S4, after the mobile user who wants to participate in this task submits the task data, the cloud server verifies whether the submitted data is consistent, including the following steps:

[0036] S41. Data requester Randomly select parameters ω, η, η′ and calculate Com1 = g ω ·h η mod p, Com2 = g ω ·h η′modp and H = Hash(Com1||Com2), and then the data requester decrypts C with his own private key r Get the random number r and decrypt C d′ Get the task data d′ and calculate D = ω + H·d′, D1 = η + H·r′ and D2 = η′ + H·r, where Hash() is a hash function. After the calculation is completed, the data requester sends {H, D, D1, D2, Com d′} to the cloud server;

[0037] S42, the cloud server receives {H, D, D1, D2, Com d′}After that, use the existing task data to commit to Com d Verify the task data submitted by the mobile user. The specific verification equation is as follows:

[0038]

[0039] If the cloud server verification is successful, it means that the data submitted by the mobile user to the cloud server is consistent with the data requester’s data, and there is no tampering by the adversary or deception by the mobile user;

[0040] S5, the cloud server selects the verified mobile user as a participant;

[0041] S6, the cloud server calculates the task result based on the submitted task data and sends it to the data requester.

[0042] 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 data tamper-proof method based on commitment 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 The data sent to the cloud server is committed to the cloud server as Com d =g d ·h r mod p; 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′. If the data d has not been tampered with, then d′=d, and the ciphertext is recorded as C d′ , and C r and C d′ The data commitment sent to the data requester is recorded as Com d′ =g d′ ·h r′ mod p; S4, after the mobile user who wants to participate in this task submits the task data, the cloud server verifies whether the submitted data is consistent, including the following steps: S41. Data requester Randomly select parameters ω, η, η′ and calculate Com1 = g ω ·h η mod p, Com2 = g ω ·h η′ mod p and H = Hash (Com1||Com2), and then the data requester uses his own private Key decryption C r Get the random number r and decrypt C d′ Get the task data d′ and calculate D=ω+H·d′, D1=η+H·r′ and D2=η′+H·r, where Hash() is a hash function. After the calculation is completed, the data requester sends {H, D, D1, D2, Com d′ } to the cloud server; S42, the cloud server receives {H, D, D1, D2, Com d′ }After that, use the existing task data to commit to Com d Verify the task data submitted by the mobile user. The specific verification equation is as follows: If the cloud server verification is successful, it means that the data submitted by the mobile user to the cloud server is consistent with the data requester’s data, and there is no tampering by the adversary or deception by the mobile user; S5, the cloud server selects the verified mobile user as a participant; S6, the cloud server calculates the task result based on the submitted task data and sends it to the data requester.

2. The data tamper-proof method based on commitment in the Internet of Things as claimed in claim 1, characterized in that: In step S2, the data requester distributes the data task through the cloud server, and the data in the data task includes but is not limited to temperature, humidity, and longitude and latitude.

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