Auditable personalized smart power grid data privacy protection method

Abstract

The invention relates to an auditable personalized smart power grid data privacy protection method, which comprises the following steps that: a gateway sends a security parameter to a block chain, and a power grid company sets a privacy budget and acceptable maximum utility loss of each type of users according to the security parameter issued by the gateway; the gateway, the block chain and the power grid company generate the same Laplacian random number list; the gateway randomly selects noise from the shuffled placian random number list based on a verifiable shuffling protocol and adds the noise to the user power consumption data to obtain noise-added user power consumption data; the block chain operates a certification protocol corresponding to the verifiable shuffling protocol to verify the related data uploaded by the gateway, and after the verification is passed, the related data is recorded in the block chain and sent to a power grid company; according to the method, privacy protection levels of different degrees can be provided for different users, the privacy of the users with relatively high data sensitivity is guaranteed, the data value of the users with relatively low data sensitivity is fully utilized, and the privacy protection level of the users with relatively high data sensitivity is guaranteed. And better privacy protection is realized.

Description

Technical Field

[0001] The present invention belongs to the technical field of data security, and in particular relates to an auditable personalized smart grid data privacy protection method. Background Art

[0002] The core development concept of smart grid is to optimize power production, transportation and distribution by analyzing how and how users use electricity. The electric energy data collected by smart grid in various links such as power generation, transmission, distribution, power consumption and dispatching are characterized by large scale, multiple types and high availability. Smart grid collects and analyzes power usage and supply conditions, adjusts power production and transmission and distribution efficiency, thereby reducing power transmission losses and saving electric energy.

[0003] In order to analyze the load conditions of the power grid, power grid companies usually collect power consumption data periodically and frequently, usually every 15 minutes or less, to estimate the real-time power consumption of the power grid, manage the power generation, transmission and distribution of the smart grid, and prevent large-scale power collapse. Furthermore, dynamic electricity price strategies can be formulated based on statistical results. In the task of collecting power data, the number of meter nodes is quite large, and each collection task may require the participation of thousands of nodes. Smart grid system model such as Figure 1 As shown, the gateway is responsible for collecting, aggregating and processing a large amount of user power data, and then storing it in the cloud server of the control center to reduce the system transmission overhead.

[0004] However, in this process, attackers can eavesdrop on the communication path and steal the power data, which may lead to the leakage of sensitive information of users contained in the power data, such as the user's home occupancy rate, economic status, and whether there is anyone at home, threatening the user's privacy. Figure 2 In addition, the importance of data privacy varies from user to user. For example, the power data of confidential units is highly sensitive. If it is not adequately protected, it will cause privacy leakage. Therefore, it is urgent to protect the privacy of power data and provide different privacy protection levels for power data of different sensitivities.

[0005] The data collection process of smart grid has the following characteristics: 1) frequent data collection; 2) a large number of smart meter nodes; 3) limited computing power of smart meters; 4) a large amount of electricity consumption data; 5) high real-time data. Therefore, while protecting the privacy of user data, it is necessary to minimize the computing and communication overhead of smart meters. Compared with traditional privacy technologies such as encryption, differential privacy technology has low computational complexity, can process real-time data more efficiently, and better meet the privacy protection in smart grid data collection. Therefore, the gateway can use differential privacy technology to add noise to the electricity data while aggregating the user's electricity data.

[0006] However, for power grid companies, fog nodes as gateways are semi-trusted. They will honestly protect the privacy of electricity data, but the amount of noise they add is random, and the gateway can publish electricity data with any noise. Without access to the original data, the power grid company cannot accurately assess the utility loss. If the added noise does not meet the requirements of the power grid company, the data utility will be greatly reduced. At this time, the service quality of the electricity data is unacceptable to the power grid company, resulting in serious losses.

[0007] Blockchain technology has the characteristics of decentralization and tamper-proof. It uses blockchain as a reliable intermediary between the gateway and the power grid company. The verification node in the blockchain verifies whether the noise added to the power data by the gateway meets the user's utility loss, without the need for an additional secure channel to transmit the specific amount of noise added. In addition, the blockchain can record the interactions between different parties to ensure efficient and secure transmission and sharing of data. Therefore, by combining blockchain with differential privacy, achieving secure and auditable privacy protection of personalized power data is the current research focus of the digital drive of the power industry. Summary of the invention

[0008] In order to solve the problems existing in the background technology, the present invention provides an auditable personalized smart grid data privacy protection method, comprising:

[0009] S1: The gateway generates corresponding security parameters based on the user's electricity consumption data it collects, and uploads the generated security parameters to the blockchain record; the security parameters include: a set of user categories, a maximum privacy budget for each type of user, and a probability quantum parameter;

[0010] S2: After the power grid company obtains the security parameters of the gateway from the blockchain, it sends the query request for the user's electricity consumption data, the set privacy budget for each type of user, and the maximum acceptable utility loss to the blockchain;

[0011] S3: The gateway, power grid company and blockchain generate the same Laplace random number list based on the probability quantum parameter, maximum utility loss and the privacy budget of each type of user respectively; the gateway queries the privacy budget of each type of user from the blockchain;

[0012] S4: The power grid company shuffles the generated Laplace random number list to obtain a shuffled Laplace random number list, and uploads the shuffled Laplace random number list to the blockchain;

[0013] S5: The blockchain verifies whether the shuffled Laplace random number list is valid based on the generated Laplace random number list. If the verification is successful, step S6 is executed. Otherwise, the query failure is fed back to the power grid company.

[0014] S6: The blockchain encrypts each element in the shuffled Laplace random number list according to the public key of the gateway, the public key of the power grid company and the first random number list generated by the elliptic curve algorithm to obtain a first cipher text list, and sends the first cipher text list and the first random number list to the gateway;

[0015] S7: The gateway shuffles the first ciphertext list through a verifiable shuffling protocol, and re-encrypts the shuffled first ciphertext list using a second random number list generated by an elliptic curve algorithm to obtain a second ciphertext list; and decrypts the second ciphertext list using the second random number list and the first random number list to obtain a noise list, and determines whether the noise list is valid based on the Laplace random number list. If so, the gateway randomly selects noise from the noise list for each type of user's electricity consumption data and adds it to the user's electricity consumption data to obtain the noisy user electricity consumption data;

[0016] S8: The gateway uses its own public key, the public key of the power grid company and the third random number list generated by the elliptic curve algorithm to encrypt the user's electricity usage data to obtain encrypted user electricity usage data, and generates a zero-knowledge proof based on the third random number list and the hash value of the third random number list; the encrypted user electricity usage data, the second cipher text list, the hash value of the third random number list, the decryption key, the zero-knowledge proof, and the hash value of the noisy user electricity usage data are sent to the blockchain for recording;

[0017] S9: The blockchain verifies whether the second ciphertext list is correctly generated from the first ciphertext list through a proof protocol corresponding to the verifiable shuffle protocol, and verifies whether the hash value of the third random number list is correct based on the zero-knowledge proof using a zero-knowledge verification algorithm. If all verifications are successful, the encrypted user electricity consumption data, the second ciphertext list, the hash value of the third random number list, the decryption key, the zero-knowledge proof, and the hash value of the noisy user electricity consumption data are sent to the power grid company;

[0018] S10: The power grid company verifies whether the hash value of the third random number list is correct based on the zero-knowledge proof and the zero-knowledge verification algorithm. If the verification is successful, the encrypted user electricity usage data is decrypted based on the second ciphertext list and the decryption key using the properties of homomorphic encryption to obtain the noisy user electricity usage data, and the hash value of the noisy user electricity usage data is used to verify the noisy user electricity usage data. If the verification is successful, the query is successful.

[0019] The present invention has at least the following beneficial effects

[0020] In terms of data security, the present invention uses multiple rounds of encryption using an elliptic curve algorithm, such as encrypting the Laplace random number list and user electricity consumption data, to prevent data from being stolen and tampered with. At the same time, the multi-link verification mechanism, such as the verification of relevant data by blockchain and power grid companies, prevents illegal data from entering, and effectively guarantees the authenticity and reliability of the data. In terms of privacy protection, personalized privacy budgets are set according to different user categories, and Laplace random number lists are generated in combination with probability quantum parameters, etc., and noise disturbances are added to the original electricity consumption data to effectively prevent user privacy leakage. Regarding data availability and accuracy, the maximum utility loss acceptable to the power grid company is used as the basis to reasonably control data quality during the privacy protection process. The multi-round verification mechanism also ensures that the data is free of errors or deviations in each processing link, meeting the business analysis needs of the power grid company. In terms of auditability, the tamper-proof characteristics of the blockchain are used to upload security parameters to the gateway, and to subsequently record encrypted data, keys and other information. All operations can be fully traced, which is convenient for reviewing the compliance and transparency of the entire data privacy protection process. The present invention can provide different degrees of privacy protection for different users, safeguard the privacy of users with higher data sensitivity, make full use of the data value of users with lower data sensitivity, and achieve better privacy protection. BRIEF DESCRIPTION OF THE DRAWINGS

[0021] Figure 1 It is a schematic diagram of the system model of the present invention;

[0022] Figure 2 Schematic diagram of the attack model;

[0023] Figure 3 It is a schematic diagram of the method flow of the present invention;

[0024] Figure 4 It is a schematic diagram of the user type composition in the power grid of the present invention. DETAILED DESCRIPTION

[0025] The following describes the embodiments of the present invention by specific examples, and those skilled in the art can easily understand other advantages and effects of the present invention from the contents disclosed in this specification. The present invention can also be implemented or applied through other different specific embodiments, and the details in this specification can also be modified or changed in various ways based on different viewpoints and applications without departing from the spirit of the present invention. It should be noted that the illustrations provided in the following embodiments only illustrate the basic concept of the present invention in a schematic manner, and the following embodiments and features in the embodiments can be combined with each other without conflict.

[0026] See also Figure 1 , Figure 2 and Figure 3 The present invention provides an auditable personalized smart grid data privacy protection method, comprising:

[0027] S1: The gateway generates corresponding security parameters based on the user's electricity consumption data it collects, and uploads the generated security parameters to the blockchain record; the security parameters include: user category set A m , the maximum privacy budget ε of each user class max and the probability quantum parameter δ;

[0028] In this embodiment, after the gateway and the power grid company register with the Trusted Center (CA), they can join the blockchain network and become a common node. The CA grants the gateway a pair of EC-Elgamal keys (P G ,S G ), giving the power grid company a key pair (P C ,S C ). These two types of nodes interact with each other by calling the smart contract SC on the blockchain. The transactions generated on the SC will be recorded in the ledger B. There are two types of nodes in the blockchain network: verification nodes are responsible for verifying transactions, generating blocks, and running consensus algorithms to maintain a public ledger; ordinary nodes are responsible for transmitting transactions and broadcasting blocks, and do not participate in ledger maintenance.

[0029] In order to facilitate data processing, the present invention assumes that all user grid data sets can be statistically analyzed as histogram data. The power consumption data set of all users is D = {D1, ..., D N}, where D n Represents the electricity consumption data of the nth user. The gateway aggregates the electricity consumption data according to the user attributes. Let the attribute value set be A = {A1,...,A M}, each attribute represents each type of user, and the power data of all users are aggregated into histogram data, expressed as D'={f1,...,f M}; where f m Indicates the mth attribute value A m The corresponding electricity consumption data set; each user's electricity consumption data set f m From V data {d1,...,d V At this time, the transmission of all M types of data can be regarded as the transmission of M separate data sets.

[0030] Since different categories of user attributes have different levels of privacy protection, different categories of users have different maximum privacy budgets, which are jointly negotiated and set in advance by all relevant parties. The probability quantum parameters are also jointly negotiated and set in advance by all relevant parties.

[0031] In this embodiment, according to the attribute A of the demand side power data m Different users are divided into the following categories:

[0032] Home Users:

[0033] The electricity consumed by household users is mainly used for living and household equipment, including powering household appliances such as lighting, air conditioning, televisions, refrigerators, washing machines, water heaters, as well as charging, entertainment and other needs.

[0034] The electricity consumption data of residential users may reflect private information such as personal living habits, living conditions, and family population. For example, electricity consumption data may expose the user's residence time, living habits, number of family members, and other private information. The leakage of this information may lead to the violation of personal privacy, such as being used for theft, surveillance, and other bad behaviors.

[0035] Commercial users:

[0036] Electricity consumed by commercial users is mainly used for commercial operations and office spaces, including lighting, air conditioning, refrigeration equipment, computers, POS machines, etc. in shops, office buildings, restaurants, supermarkets, etc.

[0037] The sensitivity of commercial users' electricity data is mainly reflected in business operations. These data may contain information such as the company's production costs, sales, profit margins, and operational efficiency. Disclosure of this information may allow competitors to obtain business secrets, affecting the company's business status and profitability.

[0038] Industrial users:

[0039] Electricity consumed by industrial users is mainly used for production and industrial equipment, including production lines, mechanical equipment, lighting, air conditioning, heating equipment, etc.

[0040] The electricity data of industrial users is usually associated with the production activities and equipment operation of the enterprise. These data may contain key information such as the production capacity, equipment utilization, and production efficiency of the enterprise. The leakage of such information may lead to the exposure of the company's trade secrets. Competitors may obtain sensitive information about the company's production situation by analyzing the electricity data, thus affecting the company's competitiveness and market position.

[0041] Agricultural users:

[0042] Electricity consumed by agricultural users is mainly used for agricultural production and facilities and equipment, including irrigation, greenhouse equipment, breeding equipment, agricultural machinery, etc.

[0043] Electricity consumption data of agricultural users may leak private information such as crop information, irrigation conditions, agricultural activity cycles, economic conditions and land resource utilization, which may lead to risks and problems in commercial competition, water resource management, agricultural production and land use.

[0044] Government users:

[0045] The electricity consumed by government agency users is mainly used for administrative offices, and power support is needed for office spaces, conference halls, administrative buildings, etc. to ensure the normal operation of daily office and administrative management; government agencies are responsible for the management and operation of various public facilities, including transportation, public transportation, municipal infrastructure, cultural and sports facilities, etc.; government agencies are responsible for maintaining social public security and public order, including police stations, fire stations, emergency management and other agencies; government agencies are responsible for environmental protection and ecological construction, including environmental monitoring, ecological protection, water resources management, etc.

[0046] As an important player in power management and supervision, government agencies’ electricity data may involve sensitive information such as energy usage in the public service sector and government procurement. These data are of great significance to government decision-making and public resource allocation, and leakage may have a negative impact on public interests.

[0047] Transportation users:

[0048] The electricity consumed by transportation users is mainly used for transportation vehicles and charging facilities, including the power supply for electric vehicles, electric bicycles and public transportation vehicles and related charging pile equipment.

[0049] The electricity consumption data of transportation users may expose sensitive information such as the number of transportation vehicles, operation routes, transportation frequency, etc., which may lead to security risks such as traffic flow monitoring and transportation plan leakage. In addition, these data may also reveal confidential information on business competition, transportation strategies, etc., which may affect the business interests of enterprises. Figure 4 The different types of users in the power grid system are specifically described.

[0050] Therefore, different levels of privacy protection are needed for different types of users, and the privacy budget is determined according to the privacy protection level.

[0051] S2: After the power grid company obtains the security parameters of the gateway from the blockchain, it sends the query request for the user's electricity consumption data, the set privacy budget for each type of user, and the maximum acceptable utility loss to the blockchain;

[0052] In this embodiment, after receiving the security parameters of the gateway, the power grid company sets a privacy budget and an acceptable maximum utility loss for each type of user. When setting the privacy budget, it is necessary to ensure that the privacy budget of each type of user is less than the agreed maximum privacy budget ε max , we get the privacy budget set ε = {ε1,...,ε M The power grid sets the acceptable maximum utility loss α so that the subsequent gateway noise-added data meets the following conditions:

[0053]

[0054] Where M represents the number of user categories, f m represents the original electricity consumption data of the mth user collected by the gateway, It represents the electricity consumption data of the mth user after the gateway adds noise, and α is the maximum acceptable utility loss.

[0055] When the power grid company sends the query request for user electricity consumption data, the set privacy budget for each type of user, and the acceptable maximum utility loss to the blockchain, the blockchain verifies whether the privacy budget of each type of user uploaded by the power grid company is less than its maximum privacy budget. If the verification is successful, a verification success message is sent to the gateway and the power grid company, and step S3 is executed. Otherwise, the query failure is fed back to the power grid company.

[0056] In this embodiment, the security parameters generated by the gateway in S1 include the maximum privacy budget for each type of user, and the power grid company sets the privacy budget for each type of user in S2. The entire process fully considers the differences in privacy requirements of different user categories. Subsequent steps are based on these privacy budgets, such as combining privacy budgets in the generation of Laplace random number lists, to ensure that while meeting data query requirements, user privacy is protected to the maximum extent possible, and to prevent user privacy leakage due to excessive queries.

[0057] S3: The gateway, power grid company and blockchain generate the same Laplace random number list based on the probability quantum parameter, maximum utility loss and the privacy budget of each type of user respectively; the gateway queries the privacy budget of each type of user from the blockchain;

[0058] Preferably, the Laplace random number list includes:

[0059] S31: Determine input parameters, the input parameters include: probability quantum parameter δ, acceptable maximum utility loss α, and privacy budget ε for each type of user m ;

[0060] S32: Create an empty list N m , define a range set Initialize variable z to -α; initialize p to 0, and initialize d to be equal to list N m Length;

[0061] S33: When z≤|α| and When F Lap (,) means generating the corresponding random number according to the Laplace cumulative distribution probability; add the current value z to the list N m ;

[0062] S34: Let p = p + δ, z = z + 1 and repeat steps S33 to S34 until z > |α| or So far, we get the Laplace random number list N m .

[0063] In this embodiment, the gateway, the power grid company and the blockchain all generate Laplace random number lists. The power grid company shuffles the generated Laplace random number list to obtain a shuffled Laplace random number list. The blockchain needs to verify whether the shuffled Laplace random number list uploaded by the power grid company is valid based on the Laplace random number list generated by itself. If the initial Laplace random number lists generated by the three parties are different, the blockchain cannot determine whether the shuffling operation of the power grid company is correct and compliant, and it is difficult to determine whether the data has been tampered with or there is an error in processing. This verification can ensure the authenticity and reliability of the data and lay a solid foundation for subsequent data processing links. For example, in subsequent steps, the noise list generated based on the verified valid shuffled Laplace random number list can be used by the gateway to add noise to the user's electricity consumption data, thereby ensuring the normal operation of the user's privacy protection mechanism. The gateway, the power grid company and the blockchain all play a key role in the entire data processing process. The gateway is responsible for collecting and preliminarily processing user electricity consumption data, the power grid company initiates data query requests and finally uses the processed data, and the blockchain serves as an important link in data storage and verification. The three parties generate the same Laplace random number list, which provides the same basis for their subsequent data processing operations, avoids inconsistency problems caused by different data processing bases, and ensures the smooth operation of the entire solution. At the same time, this embodiment is based on the set probability quantum parameter δ, the acceptable maximum utility loss α, and the privacy budget ε of each type of user. m The noise in the generated Laplace random number list meets the maximum utility loss requirement acceptable to the power grid company.

[0064] S4: The power grid company shuffles the generated Laplace random number list to obtain a shuffled Laplace random number list, and uploads the shuffled Laplace random number list to the blockchain;

[0065] In this embodiment, a list N is generated. m Afterwards, the power grid company m Shuffle and get a new list N′ m Then, the power grid company calls the smart contract to send the new list to the blockchain network. In the consensus process, each verification node first uses its own generated list N m Check N′ m Is it effective? Make sure that the grid company does not add other noises to the noise generation list.

[0066] S5: The blockchain verifies whether the shuffled Laplace random number list is valid based on the generated Laplace random number list. If the verification is successful, step S6 is executed. Otherwise, the query failure is fed back to the power grid company.

[0067] S6: The blockchain encrypts each element in the shuffled Laplace random number list according to the public key of the gateway, the public key of the power grid company and the first random number list generated by the elliptic curve algorithm to obtain a first cipher text list, and sends the first cipher text list and the first random number list to the gateway;

[0068] Preferably, encrypting each element in the shuffled Laplace random number list to obtain a first ciphertext list comprises:

[0069] S61: Construct a joint public key based on the gateway's public key and the grid company's public key

[0070] S62: Generate a first random number list using an elliptic curve algorithm;

[0071] S63: Encrypt each element in the shuffled Laplace random number list using the joint public key and the first random number list to obtain a first ciphertext list, B represents the base point of the elliptic curve; β i represents the i-th random number in the first random number list, z i represents the i-th element in the first ciphertext list; σ i Represents the i-th element in a list of shuffled Laplace random numbers.

[0072] In this embodiment, the elliptic curve algorithm is used to generate the first random number list, which includes: setting the elliptic curve parameters, assuming that in this embodiment, the base point B = 2, the group order n = 17, and the public key P CR =5 and the shuffled noise random number list N′ sent by the power grid company k ={3,-1,4}. For each element σ in the shuffled noise random number list i , use a secure random number generator (such as Python's secrets module) to generate the corresponding random number β i ,The random number generation range is [1,16], as follows:

[0073] β1=7、β2=11、β3=13

[0074] Calculate the ciphertext:

[0075] For σ1=3, z1=(β1·B,σ1+β1·P CR )=(7·2,3+7·5)=(14,38)

[0076] For σ2=-1, z2=(β2·B,σ2+β2·P CR )=(11·2,-1+11·5)=(22,54)

[0077] For σ3=4, z3=(β3·B,σ3+β3·P CR )=(13·2,4+13·5)=(26,69)

[0078] The encrypted ciphertext list is: {z1,z2,z3}={(14,38),(22,54),(26,69)}

[0079] In this embodiment, the shuffled Laplace random number list is encrypted using the public key of the gateway and the power grid company and the first random number list through the elliptic curve algorithm, and the original random number list is converted into the first cipher text list. The elliptic curve cryptography system (ECC) has high security. Based on the difficulty of the discrete logarithm problem, it is difficult for an attacker to reverse the original random number information from the encrypted cipher text. For example, even if the attacker intercepts the first cipher text list, it is almost impossible to restore the content of the shuffled Laplace random number list without knowing the private key and the specific encryption algorithm details (including the random number generation method, etc.), thereby effectively protecting the confidentiality of the data. The encryption process adds a layer of security protection to the data. Because any tampering with the cipher text will result in an erroneous result when decrypting, the receiver (gateway) can detect whether the data has been tampered with by verifying whether the decryption is successful. This ensures the integrity of the data during transmission from the blockchain to the gateway, and ensures the authenticity and reliability of the data. At the same time, the blockchain plays a key role in this process. It records the public key used for encryption, the generated first random number list, and the encrypted first cipher text list. These complete data records can be used for auditing purposes. When it is necessary to check whether the data processing process is compliant, whether there is a risk of data leakage, etc., these records can provide detailed information. At the same time, due to the tamper-proof nature of blockchain, the authenticity and reliability of these records are guaranteed, which facilitates subsequent tracing and responsibility identification.

[0080] S7: The gateway shuffles the first ciphertext list through a verifiable shuffling protocol, and re-encrypts the shuffled first ciphertext list using a second random number list generated by an elliptic curve algorithm to obtain a second ciphertext list; and decrypts the second ciphertext list using the second random number list and the first random number list to obtain a noise list, and determines whether the noise list is valid based on the Laplace random number list. If so, the gateway randomly selects noise from the noise list for each type of user's electricity consumption data and adds it to the user's electricity consumption data to obtain the noisy user electricity consumption data;

[0081] In this embodiment, the gateway receives the first ciphertext list (z1, ..., z d ) Apply the verifiable shuffling protocol, first shuffle the ciphertext list using the shuffling function π(i), and then re-encrypt it to obtain z i ′=((γ i +β π(i) )B,σ π(i) +(γ i +β π(i) ) GC ), where γ i represents the i-th element in the second random number list generated by the elliptic curve algorithm; π(i) represents the position of the i-th element in the first ciphertext list after shuffling; β π(i) represents the π(i)th random number in the first random number list; B represents the base point of the elliptic curve; P GC represents the joint public key; P G and P C Represents the public key of the gateway and the public key of the power grid company; π(i) represents the π(i)th element in the shuffled Laplace random number list; z i ′ represents the i-th element in the second ciphertext list. For the gateway, σ π(i) , β π(i) , γ i , B and P GC are all known, so the gateway can i ′ is decrypted to obtain the decrypted noise list σ π(i) , and randomly select σ π(i) Added to the data. The data after noise addition is

[0082] In this embodiment, the verifiable shuffle protocol includes three steps: re-encryption algorithm, shuffle and proof system. Re-encryption is part of the verifiable shuffle protocol. After the gateway shuffles (shuffles) and re-encrypts, the verification node will run the corresponding proof. Once re-encrypted, the data becomes tamper-proof (regardless of how the power grid company and the verification node cheat), and privacy protection is still maintained. The verification node can use the verifiable shuffle algorithm (proof) to ensure that the re-encryption process is correct, so that even if the verification node cannot directly see the content of the encrypted data, the correctness of the data can be verified by this method; since the noise list and the Laplace random number list of the gateway are generated based on the same parameters and the same algorithm, the noise list and the Laplace random number list should be consistent. Judging whether the noise list is valid through the Laplace random number list can determine whether the data in the noise list has changed. The gateway shuffles the first ciphertext list through the verifiable shuffle protocol, breaking the original data order and further increasing the randomness of the data. This makes the original arrangement information of the data completely disrupted after processing. Even if the attacker obtains part of the data, it is difficult to infer the pattern or regularity of the original information, which greatly enhances the obfuscation of the data and provides additional security protection for the data. The second random number list generated by the elliptic curve algorithm is used to re-encrypt the first ciphertext list after shuffling to obtain the second ciphertext list, which introduces a new random factor again. This re-encryption process is based on the complexity and randomness of the elliptic curve algorithm, which further improves the security of the data and makes the data more difficult to crack. Even if someone knows the information encrypted for the first time, the original information of the final encrypted data cannot be easily obtained due to the use of new random numbers in the re-encryption process, thereby protecting the privacy of user data. The use of a verifiable shuffling protocol allows the shuffling process to be verified in subsequent operations. This means that other participants (such as blockchain or power grid companies) can check whether the shuffling operation is performed correctly, ensuring the transparency and reliability of the data processing process. This verifiability helps prevent malicious or erroneous operations in the data processing process, ensure the fairness and accuracy of the data processing process, and ensure the credibility of the entire system. The second ciphertext list is decrypted by the second random number list and the first random number list to obtain the noise list, and the validity of the noise list is determined according to the Laplace random number list, ensuring that the processed data meets the expected noise distribution and privacy protection requirements. This verification mechanism ensures the reliability of the noise list, thereby ensuring the effectiveness of the user's electricity consumption data after the final noise addition in terms of privacy protection, and avoiding the failure of user privacy protection due to incorrect noise processing. Step S7 uses a variety of data processing and verification methods to not only strengthen the security and privacy protection of the data, but also ensure the verifiability of the data processing process, while taking into account the availability of the data, which plays an important role in the reliability and effectiveness of the entire smart grid data privacy protection system.

[0083] S8: The gateway uses its own public key, the public key of the power grid company and the third random number list generated by the elliptic curve algorithm to encrypt the user's electricity usage data to obtain encrypted user electricity usage data, and generates a zero-knowledge proof based on the third random number list and the hash value of the third random number list; the encrypted user electricity usage data, the second cipher text list, the hash value of the third random number list, the decryption key, the zero-knowledge proof, and the hash value of the noisy user electricity usage data are sent to the blockchain for recording; in this embodiment, the decryption key μ m,i =β π(i) +γ i +η k .

[0084] Gateway zero-knowledge proof generation algorithm

[0085] Goal: Generate zero-knowledge proof ZKP(η k );

[0086] Input: Elliptic curve parameter base point B and group order n, gateway's private random number η k .

[0087] Output: Zero-knowledge proof: commitment value C and response value s;

[0088] 1. The gateway selects a random number r, satisfying r∈{1,2,...,n-1}. The random number generation method is the same as the previous one.

[0089] 2. Calculate the commitment value s: Use the random number r and the elliptic curve base point B to calculate the commitment value:

[0090] C=r·B

[0091] 3. The verification node generates a random challenge value c, satisfying c∈{1,2,...,n-1}, and the gateway receives this challenge value c.

[0092] 4. Calculate the response value: The gateway calculates the response value based on the challenge value c, the random number r, and its private value η k Calculate the response value s:

[0093] s=(r+c·η k )mod n

[0094] 5. Proof generation: The generated zero-knowledge proof is published to the verification node as a binary pair (C, s), namely: ZKP(η k )=(C,s).

[0095] In this embodiment, the user power data is encrypted using an elliptic curve algorithm and a generated third random number list, and the user power data is converted into encrypted user power data, making use of the strong security of elliptic curve cryptography. Elliptic curve encryption is based on the difficulty of the discrete logarithm problem, ensuring that only entities with the corresponding private key can decrypt the data, protecting the user power data from unauthorized access and tampering. In the above example, the encrypted user power data is incomprehensible to a third party without the correct decryption key, greatly improving the confidentiality of the data. Generating a zero-knowledge proof allows the gateway to prove its knowledge and correct generation of the third random number list without leaking the list, thereby ensuring the privacy of the data. This means that even when it is necessary to verify certain attributes of the data (such as whether the generation of random numbers complies with regulations), sensitive information will not be exposed, adding an additional layer of privacy protection to the entire system, while ensuring the reliability and compliance of the data processing process. The hash value of the third random number list and the hash value of the user power data after noise are sent to the blockchain for recording, ensuring the integrity of the data. Any tampering with these data will change their hash values, allowing the verifier to easily check whether the data has been tampered with. For example, if an attacker attempts to modify encrypted user electricity data or other information, the corresponding hash value will not match and will be detected, ensuring the integrity of the data during transmission and storage. Zero-knowledge proof allows blockchain or other verifiers to verify the correctness of information without obtaining sensitive information. Through the zero-knowledge proof protocol, the verifier can check whether the gateway has generated the third random number list in the prescribed manner without knowing the actual random number list, which enhances the verifiability and trust of the system. Sending all key information to the blockchain for recording takes advantage of the tamper-proof nature of the blockchain. In this way, every operation step in the system can be traced on the blockchain, making it convenient for auditors to review the entire data processing process and ensure that the data processing process complies with regulations and privacy protection standards. In the event of data leakage or dispute, the problem can be found based on the records on the blockchain, and it can be used as evidence, which improves the transparency and reliability of the entire system.

[0096] S9: The blockchain verifies whether the second ciphertext list is correctly generated from the first ciphertext list through a proof protocol corresponding to the verifiable shuffle protocol, and verifies whether the hash value of the third random number list is correct based on the zero-knowledge proof using a zero-knowledge verification algorithm. If all verifications are successful, the encrypted user electricity consumption data, the second ciphertext list, the hash value of the third random number list, the decryption key, the zero-knowledge proof, and the hash value of the noisy user electricity consumption data are sent to the power grid company;

[0097] S10: The power grid company verifies whether the hash value of the third random number list is correct based on the zero-knowledge proof and the zero-knowledge verification algorithm. If all the verifications are successful, the encrypted user electricity usage data is decrypted using the properties of homomorphic encryption according to the second ciphertext list and the decryption key to obtain the noisy user electricity usage data, and the hash value of the noisy user electricity usage data is used to verify the noisy user electricity usage data. If the verification is successful, the query is successful.

[0098] Parameters known to the verification node: public key η k B, challenge value c, elliptic curve base point B, group order n, hash value recorded in the blockchain. Please note that if the verifier knows η k B and B, in theory, η can be calculated by the inverse operation of elliptic curve point multiplication k . However, this is not feasible in the framework of elliptic curve cryptography, because this operation depends on solving the elliptic curve discrete logarithm problem (ECDLP), which is extremely difficult with existing mathematical and computing resources. Therefore, the verifier cannot obtain the value of η from k B and B derive η k .

[0099] Gateway provides: ZKP(η k )=(C,s), hash(η k )

[0100] First verify hash(η k ) is consistent with the hash value recorded in the blockchain. If not, the verification fails. If they are consistent, then the proof sent by the gateway is verified as follows:

[0101] L=s·B

[0102] R=C+c·(η k B)

[0103] Compare L and R to see if they are equal. If they are equal, the verification passes.

[0104] Preferably, decrypting the encrypted user power usage data using the properties of homomorphic encryption includes:

[0105]

[0106] μ m,i =β π(i) +γ i +η k

[0107]

[0108] in, Indicates encrypted user electricity consumption data, z′i represents the second ciphertext list, Indicates the user's electricity consumption data after adding noise.

[0109] The requester passes the hash value To verify that the decryption is correct.

[0110] In summary, the present invention uses elliptic curve algorithm for multiple rounds of encryption, such as encryption of Laplace random number lists, user electricity consumption data, etc., to prevent data from being stolen and tampered. At the same time, the multi-link verification mechanism, such as the verification of relevant data by blockchain and power grid companies, prevents illegal data from entering, and effectively guarantees the authenticity and reliability of data. At the privacy protection level, personalized privacy budgets are set according to different user categories, and Laplace random number lists are generated in combination with probability quantum parameters, etc., and noise disturbances are added to the original electricity consumption data to effectively prevent user privacy leakage. Regarding data availability and accuracy, the maximum utility loss acceptable to the power grid company is used as the basis to reasonably control data quality in the privacy protection process. The multi-round verification mechanism also ensures that the data is free of errors or deviations in each processing link, meeting the business analysis needs of the power grid company. In terms of auditability, the tamper-proof characteristics of the blockchain are used to upload security parameters to the gateway, and to subsequently record encrypted data, keys and other information. All operations can be fully traced, which is convenient for reviewing the compliance and transparency of the entire data privacy protection process. The present invention can provide different degrees of privacy protection for different users, safeguard the privacy of users with higher data sensitivity, make full use of the data value of users with lower data sensitivity, and achieve better privacy protection.

[0111] Finally, it should be noted that the above embodiments are only used to illustrate the technical solution of the present invention rather than to limit it. Although the present invention has been described in detail with reference to the preferred embodiments, those skilled in the art should understand that the technical solution of the present invention can be modified or replaced by equivalents without departing from the purpose and scope of the technical solution, which should be included in the scope of the claims of the present invention.

Claims

1. An auditable personalized smart grid data privacy protection method, characterized in that: include: S1: The gateway generates corresponding security parameters based on the user's electricity consumption data it collects, and uploads the generated security parameters to the blockchain record; The security parameters include: a set of user categories, a maximum privacy budget for each category of users, and a probability quantum parameter; S2: After the power grid company obtains the security parameters of the gateway from the blockchain, it sends the query request for the user's electricity consumption data, the set privacy budget for each type of user, and the maximum acceptable utility loss to the blockchain; S3: The gateway, power grid company and blockchain generate the same Laplace random number list based on the probability quantum parameter, maximum utility loss and the privacy budget of each type of user respectively; the gateway queries the privacy budget of each type of user from the blockchain; S4: The power grid company shuffles the generated Laplace random number list to obtain a shuffled Laplace random number list, and uploads the shuffled Laplace random number list to the blockchain; S5: The blockchain verifies whether the shuffled Laplace random number list is valid based on the generated Laplace random number list. If the verification is successful, step S6 is executed. Otherwise, the query failure is fed back to the power grid company. S6: The blockchain encrypts each element in the shuffled Laplace random number list according to the public key of the gateway, the public key of the power grid company and the first random number list generated by the elliptic curve algorithm to obtain a first cipher text list, and sends the first cipher text list and the first random number list to the gateway; S7: The gateway shuffles the first ciphertext list through a verifiable shuffling protocol, and re-encrypts the shuffled first ciphertext list using a second random number list generated by an elliptic curve algorithm to obtain a second ciphertext list; and decrypts the second ciphertext list using the second random number list and the first random number list to obtain a noise list, and determines whether the noise list is valid based on the Laplace random number list. If so, the gateway randomly selects noise from the noise list for each type of user's electricity consumption data and adds it to the user's electricity consumption data to obtain the noisy user electricity consumption data; S8: The gateway uses its own public key, the public key of the power grid company and the third random number list generated by the elliptic curve algorithm to encrypt the user's electricity usage data to obtain encrypted user electricity usage data, and generates a zero-knowledge proof based on the third random number list and the hash value of the third random number list; the encrypted user electricity usage data, the second cipher text list, the hash value of the third random number list, the decryption key, the zero-knowledge proof, and the hash value of the noisy user electricity usage data are sent to the blockchain for recording; S9: The blockchain verifies whether the second ciphertext list is correctly generated from the first ciphertext list through a proof protocol corresponding to the verifiable shuffle protocol, and verifies whether the hash value of the third random number list is correct based on the zero-knowledge proof using a zero-knowledge verification algorithm. If all verifications are successful, the encrypted user electricity consumption data, the second ciphertext list, the hash value of the third random number list, the decryption key, the zero-knowledge proof, and the hash value of the noisy user electricity consumption data are sent to the power grid company; S10: The power grid company verifies whether the hash value of the third random number list is correct based on the zero-knowledge proof and the zero-knowledge verification algorithm. If the verification is successful, the encrypted user electricity usage data is decrypted based on the second ciphertext list and the decryption key using the properties of homomorphic encryption to obtain the noisy user electricity usage data, and the hash value of the noisy user electricity usage data is used to verify the noisy user electricity usage data. If the verification is successful, the query is successful.

2. The auditable personalized smart grid data privacy protection method according to claim 1, characterized in that: The blockchain verifies whether the privacy budget of each user uploaded by the power grid company is less than its maximum privacy budget. If the verification is successful, a verification success message is sent to the gateway and the power grid company, and step S3 is executed. Otherwise, the query failure is fed back to the power grid company.

3. The auditable personalized smart grid data privacy protection method according to claim 1, characterized in that: Generating a list of Laplace random numbers involves: S31: Determine input parameters, the input parameters include: probability quantum parameter δ, acceptable maximum utility loss α, and privacy budget ε for each user m ; S32: Create an empty list N m , define a range set Initialize variable z to -α; initialize p to 0, and initialize d to be equal to list N m Length; S33: When z≤|α| and When F Lap (,) means generating the corresponding random number according to the Laplace cumulative distribution probability; add the current value z to the list N m ; S34: Let p = p + δ, z = z + 1 and repeat steps S33 to S34 until z > |α| or So far, we get the Laplace random number list N m .

4. The auditable personalized smart grid data privacy protection method according to claim 1, characterized in that: The step of encrypting each element in the shuffled Laplace random number list to obtain a first ciphertext list comprises: S61: Construct a joint public key based on the gateway's public key and the grid company's public key S62: Generate a first random number list using an elliptic curve algorithm; S63: Encrypt each element in the shuffled Laplace random number list using the joint public key and the first random number list to obtain a first ciphertext list, B represents the base point of the elliptic curve; β i represents the i-th random number in the first random number list, z i represents the i-th element in the first ciphertext list; σ i Represents the i-th element in a list of shuffled Laplace random numbers.

5. The auditable personalized smart grid data privacy protection method according to claim 1, characterized in that: The re-encrypting the shuffled first ciphertext list by using the second random number list generated by the elliptic curve algorithm comprises: z i ′=((γ i +b π(i) )B,s π(i) +(c i +b π(i) )P GC ) Among them, z i ′ represents the i-th element in the second ciphertext list, γ i represents the i-th element in the second random number list generated by the elliptic curve algorithm; π(i) represents the position of the i-th element in the first ciphertext list after shuffling; β π(i) represents the π(i)th random number in the first random number list; B represents the base point of the elliptic curve; P GC represents the joint public key; P G and P C Represents the public key of the gateway and the public key of the power grid company; π(i) Represents the π(i)th element in a list of shuffled Laplace random numbers.

6. The auditable personalized smart grid data privacy protection method according to claim 1, characterized in that: The step of encrypting the user power usage data to obtain the encrypted user power usage data comprises: in, Indicates encrypted user electricity consumption data, η k represents a random number in the third random number list; P GC represents the joint public key; P G and P C Represents the public key of the gateway and the public key of the power grid company; B represents the base point of the elliptic curve.

7. The auditable personalized smart grid data privacy protection method according to claim 1, characterized in that: Decrypting the encrypted user electricity consumption data by using the properties of homomorphic encryption includes: in, Indicates encrypted user electricity consumption data, η k represents the random number in the third random number list, z′ i represents the second ciphertext list, represents the user electricity consumption data after adding noise, σ π(i) represents the π(i)th element in the shuffled Laplace random number list, f m Indicates user electricity consumption data.

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