Privacy Calculation Method, System, Electronic Device and Storage Medium for Power Data

Abstract

The present application discloses a privacy calculation method, system, electronic device and storage medium for power data. Among them, the method includes: encrypting the user power data of at least one electricity meter terminal by using a homomorphic encryption algorithm, and anonymizing the identities of at least one electricity meter terminal by using linkable ring signatures, and packing the encrypted data and anonymized information to generate ciphertext data; aggregating and statistically analyzing the ciphertext data of at least one electricity meter terminal by using at least one distribution substation; decrypting the aggregated ciphertext data by using a control center to obtain user power statistical data, and predicting the electricity consumption information of users in the power system according to the user power statistical data. Thereby, the anonymity and security of power data are effectively improved, and at the same time, the traceability of power data is ensured, realizing higher privacy efficiency.

Description

Technical Field

[0001] This application relates to the field of information security technology, and in particular to a privacy calculation method, system, electronic device and storage medium for power data. Background Art

[0002] Through in-depth research on the development status and related research results in the domestic and foreign power fields, it can be found that compared with other application industries, privacy protection in the power field has certain particularities: (1) The power system is an important industry related to national economy and people's livelihood, with high security requirements, low latency, and low fault tolerance; (2) Physically, the power data network is a multi-level transmission network composed of a control center, several power stations, and many meter terminals; (3) Power data has a simple form, generally digital data.

[0003] Power data can reflect privacy information such as users' electricity consumption habits, living patterns, and activities. The smart grid needs to collect users' power data to complete functions such as planned power generation and load analysis. Therefore, personal information needs to be protected in the statistical dataset, and the instantaneous data of specific meter users should be avoided from being leaked when collecting statistical data.

[0004] However, smart meters use a fixed identity in the network, which may cause the cumulative increase in the risk of real address / identity leakage in the long term. And current smart grid models mostly focus on the privacy carried by the data itself, or use simple reversible transformations or additional strings to protect the meter identity. Increasing the identity update frequency will lead to difficulties and costs in key distribution management. Therefore, a more perfect identity protection scheme needs to be designed, while ensuring that the data interaction process is verifiable and traceable. Summary of the Invention

[0005] This application provides a privacy calculation method, system, electronic device and storage medium for power data, which effectively improves the anonymity and security of power data, while ensuring the traceability of power data and achieving higher privacy efficiency.

[0006] In a first aspect embodiment of this application, a privacy calculation method for power data is provided, including the following steps: encrypting the user power data of at least one meter terminal by using a homomorphic encryption algorithm, and anonymizing the identity of the at least one meter terminal by using linkable ring signatures, and packaging the encrypted data and the anonymized information to generate ciphertext data; aggregating and statistically analyzing the ciphertext data of the at least one meter terminal by using the at least one substation; decrypting the aggregated ciphertext data by using a control center to obtain user power statistical data, and predicting the electricity consumption information of users in the power system according to the user power statistical data.

[0007] Optionally, in an embodiment of the present application, before encrypting the user power data of at least one electricity meter terminal using a homomorphic encryption algorithm, it further includes: performing local differential privacy processing on the user power data of the at least one electricity meter terminal according to a preset privacy budget.

[0008] Optionally, in an embodiment of the present application, it further includes: when anonymizing the identities of the at least one electricity meter terminal using the linkable ring signature, storing the signature identifier in a Bloom filter, encrypting the Bloom filter, and sending the encrypted Bloom filter to the distribution substation to which the electricity meter terminal belongs.

[0009] Optionally, in an embodiment of the present application, it further includes: querying and verifying the data hash value stored in the at least one distribution substation through the signature identifier, and homomorphically calculating the ciphertext statistical value of the ciphertext data to verify the power data of the at least one electricity meter terminal.

[0010] Optionally, in an embodiment of the present application, it further includes: detecting whether an abnormality occurs in the electricity meter terminal of the power system; when an abnormality occurs in the electricity meter terminal of the power system, using the private key of the supervision center to retrieve all Bloom filters of the distribution substation to which the abnormal electricity meter terminal belongs, and determining the electricity meter terminal corresponding to the abnormality by querying the membership relationship in the Bloom filter.

[0011] An embodiment of the second aspect of the present application provides a privacy calculation system for power data, including: at least one electricity meter terminal, configured to encrypt user power data using a homomorphic encryption algorithm, anonymize the identities of the at least one electricity meter terminal using a linkable ring signature, and package the encrypted data and the anonymized information to generate ciphertext data; at least one distribution substation, configured to perform aggregated statistics on the ciphertext data of the at least one electricity meter terminal and store the aggregated statistical data; a control center, configured to decrypt the aggregated ciphertext data using the control center to obtain user power statistical data, and predict the electricity consumption information of users in the power system according to the user power statistical data.

[0012] Optionally, in an embodiment of the present application, the at least one electricity meter terminal is further configured to perform local differential privacy processing on the user power data of the at least one electricity meter terminal according to a preset privacy budget.

[0013] Optionally, in an embodiment of the present application, the at least one electricity meter terminal is further configured to, when anonymizing the identities of the at least one electricity meter terminal using the linkable ring signature, store the signature identifier in a Bloom filter, encrypt the Bloom filter, and send the encrypted Bloom filter to the distribution substation to which the electricity meter terminal belongs.

[0014] In the third aspect of the present application, an embodiment provides an electronic device, including: a memory, a processor, and a computer program stored on the memory and executable on the processor, where the processor executes the program to perform the privacy calculation method of power data as described in the above embodiments.

[0015] In the fourth aspect of the present application, an embodiment provides a computer-readable storage medium, on which a computer program is stored, and the program is executed by a processor to perform the privacy calculation method of power data as described in the above embodiments.

[0016] The embodiments of the present application adopt an efficient BGN (Boneh-Goh-Nissim, a homomorphic encryption algorithm) to achieve ciphertext aggregation of data transmission; use the differential privacy random response algorithm to achieve data statistical analysis; design and implement a key-isolated linkable ring signature based on the national cryptographic algorithms SM2 and SM9, and cooperate with the Bloom filter and public key cryptography algorithm to achieve identity traceability, effectively improving the anonymity and security of power data, while ensuring the traceability of power data and achieving higher privacy efficiency.

[0017] Some of the additional aspects and advantages of the present application will be given in the following description, some will become obvious from the following description, or will be understood through the practice of the present application. BRIEF DESCRIPTION OF THE DRAWINGS

[0018] The above and / or additional aspects and advantages of the present application will become obvious and easy to understand from the following description of the embodiments in conjunction with the drawings, where:

[0019] Figure 1 is a flowchart of a privacy calculation method of power data according to an embodiment of the present application;

[0020] Figure 2 is an organizational structure diagram of power big data privacy calculation according to an embodiment of the present application;

[0021] Figure 3 is a power data transmission diagram according to an embodiment of the present application;

[0022] Figure 4 is a technical roadmap adopted to implement privacy calculation according to an embodiment of the present application;

[0023] Figure 5 is an improved linkable ring signature key encapsulation algorithm flow according to an embodiment of the present application;

[0024] Figure 6 is an improved linkable ring signature decapsulation algorithm flow according to an embodiment of the present application;

[0025] Figure 7An example diagram of a privacy computing system for power data according to an embodiment of the present application;

[0026] Figure 8 A schematic structural diagram of an electronic device provided by an embodiment of the application. Detailed implementation manners

[0027] The embodiments of the present application will be described in detail below. The examples of the embodiments are shown in the accompanying drawings, where the same or similar reference numerals denote the same or similar elements or elements having the same or similar functions throughout. The embodiments described below with reference to the accompanying drawings are exemplary and are intended to explain the present application, and should not be construed as a limitation to the present application.

[0028] The privacy computing method, system, electronic device, and storage medium for power data according to the embodiments of the present application will be described below with reference to the accompanying drawings. The present application provides a privacy computing method for power data. During the transmission and aggregation of power data by edge electricity meter terminals, without affecting the analysis and other operation performances, this method realizes the dual privacy protection of the identities of electricity meter users and power data and the traceability of the externally provided data. In addition, the power control center also provides a privacy statistics query function. When an abnormal situation occurs, the law enforcement and supervision department can perform non-interactive forced traceability, restore the identities of malicious communication parties inside the power grid, and give corresponding penalties. Thereby, the anonymity and security of power data are effectively improved, while ensuring the traceability of power data, and higher privacy efficiency is achieved.

[0029] Specifically, Figure 1 A flowchart of a privacy computing method for power data according to an embodiment of the present application.

[0030] As Figure 1 shown, the privacy computing method for power data includes the following steps:

[0031] In step S101, the user power data of at least one electricity meter terminal is encrypted using a homomorphic encryption algorithm, and the identities of at least one electricity meter terminal are anonymized using linkable ring signatures. The encrypted data and anonymized information are packaged to generate ciphertext data.

[0032] Specifically, the embodiments of the present application use a homomorphic encryption algorithm to encrypt the user power data of at least one electricity meter terminal. The homomorphic encryption mechanism can help perform aggregated calculations on power data in ciphertext state, enabling the control center (power company) to obtain the required statistical data rather than the power records of specific users. The basis for selecting the homomorphic encryption method in the present application includes: First, the adopted homomorphic encryption method needs to meet relatively high performance requirements and should not introduce excessive costs. Second, the statistical calculation complexity required in the power scenario of the present application is not high, mainly consisting of a limited number of addition calculations. Therefore, the fully homomorphic encryption family that satisfies arbitrary circuit homomorphic calculation and introduces a large amount of computation and public key size is not suitable for implementing privacy calculation in this scenario. Considering the characteristics of comprehensive calculation features, performance, implementation scale, security, etc., the present application selects a homomorphic encryption method to implement privacy calculation of power data.

[0033] Optionally, in an embodiment of the present application, before encrypting the user power data of at least one electricity meter terminal using a homomorphic encryption algorithm, it further includes: performing local differential privacy processing on the user power data of at least one electricity meter terminal according to a preset privacy budget.

[0034] Specifically, before encrypting the user power data of at least one electricity meter terminal using a homomorphic encryption algorithm in the present application, local differential privacy processing can also be performed on the power data according to a preset privacy budget. The local differential privacy mechanism ensures the privacy of power data by introducing randomness and can provide unbiased statistical results for the smart grid through calibration; the basis for selecting the privacy budget of local differential privacy in the present application is to select a smaller privacy budget according to the number of users to ensure the availability of statistical results and improve the user privacy protection level. The present application selects the classical random response mechanism to implement statistical queries of power data.

[0035] As Figure 2 shown, the entities involved in the present application include: electricity meter terminals, distribution substations, control centers, and supervision centers (representing relevant administrative law enforcement departments that have no interest in the power company). The intelligent electricity meter terminals are located at the network edge, regularly collect, package, and upload the electricity consumption data of this household (planned), which can reflect the user's electricity consumption habits and belongs to privacy data. The distribution substation receives the uploaded data from the terminals within its jurisdiction, verifies it, aggregates the legal data, and forwards it to the control center. The control center receives the power data and performs statistical calculations according to production requirements. The supervision center supervises the correctness and legality in the life cycle of power data generation - transmission - use and is responsible for handling disputes.

[0036] Through the information interaction of the above three entities, the present application mainly realizes the following functions: 1. The power control center has the functions of data privacy statistics and calculation; 2. Privacy protection during the power data transmission and aggregation process; 3. Anonymity of the identity of the data terminal (electric meter); 4. Verifiable anonymity to ensure the integrity and validity of data during the transmission and calculation process; 5. The privacy protection measures used do not affect the traceability of data; 6. When an abnormality (error or attack) occurs, the regulatory department has the ability to restore the true identity of the communication parties in the power grid.

[0037] The specific implementation method will be introduced through the following embodiments.

[0038] As Figure 3 shown, it includes a power data upload stage and a power consumption verification stage. The power data upload stage is to upload power data to the distribution substation through the electric meter terminal, and the power consumption verification stage is to verify the power consumption data through the supervision center.

[0039] First, the power data upload stage: Smart meter: Upload information to the distribution substation: <H ij , E ij , T, B i , σ>, where i represents the label of the user, j represents the time-sharing label of data upload, m ij is the time-sharing power consumption of the user, N represents the total number of smart meters; The smart meter changes the data to the upper bound of power consumption as the discrete power consumption value with probability and changes the data to the lower bound of power consumption as the discrete power consumption value with probability 1 - Pr[upper]. Then, under the condition of privacy budget ε, the true answer of the discrete power consumption value with p = e ε / (1 + e ε ) is used as the upload value, and the opposite answer is used as the upload value m ij ' with probability 1 - p, H ij = hash(T, E ij ), E ij = ENC pkcc (m ij ), T is the timestamp; Ring signature σ ij (H ij , E ij , T, B i ) := (C 1 , r 1 ,..., r n , I ij ); I ij is the unique identification code for signature generation, and it is added to the Bloom filter Bloom i ← I ij ; B i = ENC pksc (Bloomi , MPK).

[0040] Optionally, in an embodiment of the present application, it further includes: when using linkable ring signature to anonymize the identities of at least one electricity meter terminal, storing the signature identifier in a Bloom filter, encrypting the Bloom filter, and sending the encrypted Bloom filter to the distribution substation to which the electricity meter terminal belongs.

[0041] As introduced in the above embodiment, during linkable ring signature, the generated signature identifier I ij is stored in the Bloom filter for calling the signature identifier I stored in the Bloom filter during subsequent electricity consumption verification and anomaly tracing phases ij for tracing.

[0042] As Figure 4 shown, it includes some technologies adopted to achieve data privacy and identity privacy. ε-local differential privacy and BGN homomorphic encryption protect data privacy, RSA public key encryption and HMAC authentication code ensure message security and integrity, and key-isolated linkable ring signature provides identity privacy.

[0043] Furthermore, the embodiment of the present application can adopt derived identity linkable ring signature based on SM2. The security of this signature scheme is based on the SM2 national cryptographic algorithm, that is, the hardness assumption of the elliptic curve discrete logarithm problem. Among them, the hash function can use the SM3 algorithm. The derived key isolation method and the linkable identifier generation process refer to the design structure of SALRS in [reference], and the key encapsulation mechanism KEM is called to implement key isolation; the ring structure and signature design are improved from the ring signature scheme based on the SM2 cryptographic algorithm in related technologies. When generating the signature ring, the master public key is replaced with the derived public key, and a keyimage for implementing linkability is added. The specific signature scheme is as follows:

[0044] (1) MasterKeyGen(PP) → MPK;

[0045] random d i ∈ [1, n - 2], P i = [d i ·G;

[0046] Π kem .KeyGen(GP kem ) → (pk kem , sk kem );

[0047] output MPK := (P i , pk kem ), MSK := (d i , sk kem );

[0048] (2) DPKGen(MPK) → DPK;

[0049] Π kem .Encaps(pk kem ) → (κ, c);

[0050] Hash 1 (κ) → s′, s′·G → t′,

[0051]

[0052] (3) Sign(m, R, DPK, (MPK, MSK)) → σ;

[0053] (R = {DPK 1 ,..., DPK n}, DPK ∈ R);

[0054] ① for(i = 1,..., n);

[0055] Let

[0056]

[0057] Note that

[0058]

[0059] ② random k s , C s+1 := Hash SM3 (m, R, [k s ·G, I);

[0060] And convert the type of e to an integer;

[0061] for(i = s + 1,..., n, 1,..., s - 1);

[0062] random k i , there is a curve point (x i , y i ) = [k i ·G, and convert the type of x i to a large integer;

[0063] r i = (e + x i ) mod N (N is the order of G);

[0064]

[0065] C i+1 := Hash SM3 (m, R, z i , I), and denote C n+1 = C 1 ;

[0066]

[0067] output σ := (C 1 , r 1 ,..., r n , I);

[0068] (4) Verify(m′, R, σ) → 1 / 0;

[0069] And convert the type of e′ to a large integer;

[0070] Verify

[0071] for(i = 1,..., n);

[0072] Verify

[0073] for(i = 1,..., n);

[0074]

[0075] C′ i+1 := Hash SM3 (m′, R, z i ′, I′);

[0076] Verify C′ n + 1 = C′ 1 ;

[0077] If it holds, output 1; otherwise output 0.

[0078] (5) Link(m 0 , R 0 , σ 0 , m 1 , R 1 , σ 1 ) → 1 / 0;

[0079] Verify I 0 = I 1 , if it holds, output 1.

[0080] Proof: Correctness of the round function:

[0081] Substitute C 1 ;

[0082]

[0083] C 2 : = Hash SM3 (m, R, z 1 , I);

[0084]

[0085] C 3 : = Hash SM3 (m, R, z 2 , I);

[0086] ……

[0087]

[0088] C s+1 = Hash SM3 (m, R, [k s ·G, I) = Hash SM3 (m, R, z s , I);

[0089]

[0090] C n+1 = Hash SM3 (m, R, z n , I) = C 1 ;

[0091] Correctness of the linking function:

[0092] When DPK 0 ≠ DPK 1 , and then there is and consistent, random, and different;

[0093] Also, ∵ and are also different ∴ with negligible probability I 0 = I 1 holds;

[0094] Assume c 0 ≠ c 1 , then unless accidentally finding a collision that satisfies and (happening with only negligible probability), otherwise there must be Therefore, there must be I 0= I 1 。

[0095] The two cases where the latter occurs:

[0096] 1) d 0 ≠ d 1 and s' 0 ≠ s' 1 However, s' 0 + d 0 = s' 1 + d 1 because of the randomness generated by s' 0 , d 0 , s' i , d 1 This situation occurs only with a negligible probability.

[0097] 2) d 0 = d 1 and s' 0 = s' 1 If d 0 , d 1 are generated by two different MasterKeyGen algorithms, then the probability that d 0 = d 1 is negligible. In addition, if the DPKGen algorithm generates two c 0 ≠ c 1 , then the corresponding s' 0 , s' 1 should be different with overwhelming probability.

[0098] In addition, this signature also satisfies security and privacy properties such as unforgeability, derived key isolation, anonymity, linkability, etc.

[0099] The key encapsulation mechanism enables the encapsulator to generate and encrypt a secret key for the target user, and only the target user can decrypt the secret key and use it as a further session key. The key encapsulation mechanism of SM9 is implemented by an identity-based elliptic curve pair. The decapsulating user holds an identity and a corresponding encrypted private key, which is generated by the key generation center by combining the encrypted master private key and the identity of the decapsulating user. The encapsulator uses the identity of the decapsulating user to generate and encrypt a secret key for the other party, and the decapsulating user decrypts the secret key with the corresponding encrypted private key. The key encapsulation and decapsulation algorithm processes are as shown in Figure 5 and Figure 6 shown.

[0100] In step S102, at least one distribution substation is used to perform aggregated statistics on the ciphertext data of at least one electricity meter terminal.

[0101] The distribution substation verifies, stores, processes, and packs and forwards the data sent by the electricity meter terminal.

[0102] (1) Verify the signature Verify((H ij , E ij , T, B i ), R, σ); where R is the set of all derived addresses of the ring;

[0103] (2) Save <H ij , I ij >, B i ;

[0104] (3) Send <ID SS , E j , T′, H j , HMAC(ID SS , E j , T′, H j )> to the control center, where

[0105] Homomorphic encryption is used to verify the actual electricity consumption and the planned electricity consumption.

[0106] The distribution substation sends the aggregated and statistically processed data to the control center.

[0107] In step S103, the control center decrypts the aggregated ciphertext data to obtain the user power statistical data, and predicts the electricity consumption information of the users in the power system according to the user power statistical data.

[0108] Specifically, the control center verifies the received data; decrypts m′ = DEC pkcc (E j ), corrects the result to obtain an unbiased estimated value of the electricity consumption, which is used for production activities such as power generation in the power plant.

[0109] Optionally, in an embodiment of the present application, it further includes: querying and verifying the data hash value stored in at least one distribution substation through a signature identifier, and homomorphically calculating the ciphertext statistical value of the ciphertext data to verify the power data of at least one electricity meter terminal.

[0110] Specifically, in the stage of verifying the electricity meter data by the distribution substation, the embodiment of the present application can query and verify the data hash value stored in the distribution substation through the signature identification code I, and homomorphically calculate the ciphertext statistical value. This is the first traceability function in the present application. By interacting with the electricity meter terminal once, the distribution substation can know the ownership relationship of the derived identity of the electricity meter.

[0111] (1) The smart electricity meter submits ∪ all j in period <T, E ij , Iij , HMAC(T, E ij , I ij ) >;

[0112] (2) The distribution substation uses all I ij to query the data it stores and verify the corresponding H ij ;

[0113] (3) The distribution substation calculates and forwards it to the control center.

[0114] Optionally, in an embodiment of the present application, it further includes: detecting whether there is an abnormality in the meter terminal of the power system; when there is an abnormality in the meter terminal of the power system, using the private key of the supervision center to retrieve all the Bloom filters of the distribution substation to which the abnormal meter terminal belongs, and determining the abnormal corresponding meter terminal by querying the membership relationship in the Bloom filter.

[0115] When the smart meter refuses to provide verification information or suffers an internal attack during the electricity consumption verification phase, the supervision center has the right to use its own private key to retrieve all the Bs in all distribution substations i to verify the true identity of the user, determine the corresponding smart meter by querying the membership relationship in the Bloom filter, and take corresponding measures. This is the second traceability function in this application. When the monitoring center intervenes, the subordinate relationship between the uploaded derived key and the master key can be obtained without the participation of the meter terminal.

[0116] The formal definition of the ring signature involved in this application is as follows:

[0117] - MasterKeyGen(PP) → MPK

[0118] - DPKGen(MPK) → DPK

[0119] - Sign(m, R, DPK, (MPK, MSK)) → σ(·,..., I)

[0120] - Verify(m′, R, σ) → 1 / 0

[0121] - Link(m 0 , R 0 , σ 0 , m 1 , R 1 , σ 1 ) → 1 / 0

[0122] Through the above introduction, the present application uses elliptic curves with good properties for large number operations, meeting the requirements of big data processing. Through functional testing, the actual operation of each module of this solution is verified, and the results show that each module executes normally and correctly according to the functional expectations. Performance testing measures the actual operation cost of each module in processing data of different scales. The present application introduces a relatively small acceptable time and storage cost, achieving higher privacy efficiency.

[0123] According to the privacy calculation method of power data proposed in the embodiments of the present application, the smart meter anonymously sends the encrypted power consumption data after homomorphic encryption to the distribution substation through linkable ring signature. The distribution substation aggregates them and then sends them to the control center. Finally, the control center performs aggregate decryption to predict the power consumption of users. When an error occurs during the verification phase of the power system or an internal attack occurs, without the participation of the smart meter, the monitoring center can trace the actual belonging meter of the derived identity of the uploaded data by querying the encrypted Bloom filter stored in the distribution substation. Thereby, the anonymity and security of power data are effectively improved, while ensuring the traceability of power data, achieving higher privacy efficiency.

[0124] Next, refer to the accompanying drawings to describe the privacy calculation system of power data proposed in the embodiments of the present application.

[0125] Figure 7 It is a block schematic diagram of the privacy calculation system of power data according to the embodiments of the present application.

[0126] As Figure 7 shown, the privacy calculation system 10 of the power data includes: at least one meter terminal 100, at least one distribution substation 200, and a control center 300.

[0127] Among them, at least one meter terminal 100 is used to encrypt the user power data using the homomorphic encryption algorithm, and use linkable ring signature to anonymize the identity of at least one meter terminal, and package the encrypted data and anonymization information to generate ciphertext data. At least one distribution substation 200 is used to aggregate and statistically analyze the ciphertext data of at least one meter terminal, and store the aggregated and statistically analyzed data. The control center 300 is used to decrypt the aggregated ciphertext data using the control center to obtain the user power statistical data, and predict the power consumption information of users in the power system according to the user power statistical data.

[0128] Optionally, in an embodiment of the present application, at least one meter terminal is further used to perform local differential privacy processing on the user power data of at least one meter terminal according to a preset privacy budget.

[0129] Optionally, in an embodiment of the present application, at least one electricity meter terminal is further configured to, when anonymizing the identities of at least one electricity meter terminal by using linkable ring signatures, store the signature identifier in a Bloom filter, encrypt the Bloom filter, and send the encrypted Bloom filter to the distribution substation to which the electricity meter terminal belongs.

[0130] Optionally, in an embodiment of the present application, at least one distribution substation is further configured to query and verify the data hash value stored in at least one distribution substation through the signature identifier, and homomorphically calculate the ciphertext statistical value of the ciphertext data, so as to verify the power data of at least one electricity meter terminal.

[0131] Optionally, in an embodiment of the present application, it further includes: a detection module, configured to detect whether an abnormality occurs in the electricity meter terminal of the power system; a tracing module, configured to, when an abnormality occurs in the electricity meter terminal of the power system, use the private key of the supervision center to retrieve all Bloom filters of the distribution substation to which the abnormal electricity meter terminal belongs, and determine the electricity meter terminal corresponding to the abnormality by querying the membership relationship in the Bloom filter.

[0132] It should be noted that the foregoing explanation of the embodiments of the privacy calculation method for power data also applies to the privacy calculation system for power data in this embodiment, and will not be elaborated here.

[0133] According to the privacy calculation system for power data proposed in the embodiments of the present application, the smart electricity meter anonymously sends the homomorphically encrypted electricity consumption data to the distribution substation through linkable ring signatures. After aggregation by the distribution substation, it is sent to the control center, and finally the control center performs aggregation and decryption to predict the user's electricity consumption. When an error occurs in the power system verification stage or an internal attack occurs, without the participation of the smart electricity meter, the monitoring center can trace the actual electricity meter to which the derived identity of the uploaded data belongs by querying the encrypted Bloom filter stored in the distribution substation. Thereby, the anonymity and security of power data are effectively improved, and at the same time, the traceability of power data is ensured, realizing a higher privacy efficiency.

[0134] Figure 8 The following is a schematic structural diagram of an electronic device provided by an embodiment of the present application. The electronic device may include:

[0135] A memory 801, a processor 802, and a computer program stored on the memory 801 and executable on the processor 802.

[0136] When the processor 802 executes the program, it implements the privacy calculation method for power data provided in the foregoing embodiments.

[0137] Furthermore, the electronic device further includes:

[0138] A communication interface 803, configured for communication between the memory 801 and the processor 802.

[0139] A memory 801 for storing a computer program that can run on a processor 802.

[0140] The memory 801 may include high-speed RAM memory and may also include non-volatile memory, such as at least one disk memory.

[0141] If the memory 801, the processor 802, and the communication interface 803 are implemented independently, the communication interface 803, the memory 801, and the processor 802 can be interconnected through a bus and communicate with each other. The bus can be an Industry Standard Architecture (ISA) bus, a Peripheral Component Interconnect (PCI) bus, an Extended Industry Standard Architecture (EISA) bus, etc. The bus can be divided into an address bus, a data bus, a control bus, etc. For ease of representation, Figure 8 only a thick line is used to represent it in the figure, but it does not mean that there is only one bus or one type of bus.

[0142] Optionally, in a specific implementation, if the memory 801, the processor 802, and the communication interface 803 are integrated on a chip, the memory 801, the processor 802, and the communication interface 803 can communicate with each other through an internal interface.

[0143] The processor 802 may be a Central Processing Unit (CPU), or an Application Specific Integrated Circuit (ASIC), or one or more integrated circuits configured to implement the embodiments of the present application.

[0144] This embodiment also provides a computer-readable storage medium, on which a computer program is stored, and the program, when executed by a processor, implements the above-mentioned privacy calculation method for power data.

[0145] In the description of this specification, the descriptions referring to terms such as "one embodiment", "some embodiments", "example", "specific example", or "some examples" mean that the specific features, structures, materials, or characteristics described in connection with the embodiment or example are included in at least one embodiment or example of this application. In this specification, the schematic representations of the above terms do not necessarily refer to the same embodiment or example. Moreover, the specific features, structures, materials, or characteristics described can be combined in any one or N embodiments or examples in a suitable manner. In addition, without contradiction, those skilled in the art can combine and combine the different embodiments or examples described in this specification and the features of different embodiments or examples.

[0146] In addition, the terms "first" and "second" are used for descriptive purposes only and cannot be construed as indicating or implying relative importance or implicitly specifying the quantity of the indicated technical features. Thus, the features defined with "first" and "second" may explicitly or implicitly include at least one of the features. In the description of this application, the meaning of "N" is at least two, such as two, three, etc., unless otherwise specifically defined.

[0147] Any process or method description shown in the flowchart or described in other ways herein can be understood to represent a module, segment, or part of code including one or more N executable instructions for implementing a customized logic function or process, and the scope of the preferred embodiments of this application includes additional implementations, where the functions can be executed in a substantially simultaneous manner or in a reverse order according to the functions involved, rather than in the order shown or discussed, which should be understood by those skilled in the art to which the embodiments of this application belong.

[0148] It should be understood that the various parts of this application can be implemented by hardware, software, firmware, or a combination thereof. In the above embodiments, the N steps or methods can be implemented by software or firmware stored in a memory and executed by a suitable instruction execution system. For example, if implemented by hardware as in another embodiment, any one or a combination of the following techniques well known in the art can be used: discrete logic circuits having logic gate circuits for implementing logic functions on data signals, application specific integrated circuits having appropriate combinational logic gate circuits, programmable gate arrays (PGAs), field programmable gate arrays (FPGAs), etc.

[0149] Those of ordinary skill in the art of this technology can understand that all or part of the steps carried by the method for implementing the above embodiments can be completed by instructing relevant hardware through a program, and the program can be stored in a computer-readable storage medium. When the program is executed, it includes one or a combination of the steps of the method embodiment.

Claims

1. A privacy calculation method for power data, characterized in that, it includes the following steps: Encrypt the user power data of at least one electricity meter terminal using a homomorphic encryption algorithm, and anonymize the identity of the at least one electricity meter terminal using linkable ring signatures, and package the encrypted data and anonymization information to generate ciphertext data; Use at least one substation to perform aggregation statistics on the ciphertext data of the at least one electricity meter terminal; Use the control center to decrypt the aggregated ciphertext data to obtain user power statistics data, and predict the electricity consumption information of users in the power system according to the user power statistics data; Before encrypting the user power data of at least one electricity meter terminal using the homomorphic encryption algorithm, it further includes: Perform local differential privacy processing on the user power data of the at least one electricity meter terminal according to a preset privacy budget; It further includes: When anonymizing the identity of the at least one electricity meter terminal using the linkable ring signature, store the signature identifier in a Bloom filter, encrypt the Bloom filter, and send the encrypted Bloom filter to the substation to which the electricity meter terminal belongs; Storing the signature identifier into the Bloom filter means that represents the label of the user, represents the time-sharing label for data upload, is the unique identification code for signature generation. Add to the Bloom filter ; It further includes: Detect whether there is an abnormality in the electricity meter terminals of the power system; When there is an abnormality in the electricity meter terminals of the power system, use the private key of the supervision center to retrieve all the Bloom filters of the substation to which the abnormal electricity meter terminal belongs, and determine the electricity meter terminal corresponding to the abnormality by querying the membership relationship in the Bloom filter.

2. The method according to claim 1, characterized in that, it further includes: Query and verify the data hash value stored in the at least one substation through the signature identifier, and homomorphically calculate the ciphertext statistical value of the ciphertext data to verify the power data of the at least one electricity meter terminal.

3. A privacy calculation system for power data, characterized in that, it includes: At least one electricity meter terminal, which is used to encrypt user power data using a homomorphic encryption algorithm, and anonymize the identity of the at least one electricity meter terminal using linkable ring signatures, and package the encrypted data and anonymization information to generate ciphertext data; At least one substation, which is used to perform aggregation statistics on the ciphertext data of the at least one electricity meter terminal and store the aggregated statistical data; A control center, which is used to decrypt the aggregated ciphertext data using the control center to obtain user power statistics data, and predict the electricity consumption information of users in the power system according to the user power statistics data; The at least one electricity meter terminal is also used to perform local differential privacy processing on the user power data of the at least one electricity meter terminal according to a preset privacy budget; The at least one electricity meter terminal is also used to store the signature identifier in a Bloom filter when anonymizing the identity of the at least one electricity meter terminal using the linkable ring signature, encrypt the Bloom filter, and send the encrypted Bloom filter to the substation to which the electricity meter terminal belongs; Storing the signature identifier into the Bloom filter means that, represents the label of the user, represents the time-sharing label of data upload, is the unique identification code for signature generation. Add to the Bloom filter ; It further includes: Detect whether there is an abnormality in the electricity meter terminals of the power system; When an abnormality occurs in the electricity meter terminal of the power system, all Bloom filters of the distribution substation to which the abnormal electricity meter terminal belongs are retrieved using the private key of the supervision center, and the electricity meter terminal corresponding to the abnormality is determined by querying the membership relationship in the Bloom filters.

4. An electronic device, characterized in that, comprising: a memory, a processor, and a computer program stored on the memory and executable on the processor, wherein the processor executes the program to implement the privacy calculation method of power data according to any one of claims 1-2.

5. A computer-readable storage medium having a computer program stored thereon, characterized in that, the program is executed by a processor for implementing the privacy calculation method of power data according to any one of claims 1-2.

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