An intelligent electricity meter data protection method based on the homomorphic encryption algorithm

Abstract

An intelligent electricity meter data protection method based on a homomorphic encryption algorithm, comprising: the intelligent electricity meter collects the power consumption of users every preset period and sums up the power consumption; a trusted institution generates the public key and private key required for Paillier homomorphic encryption of the Chinese Remainder Theorem for the intelligent electricity meter, and uses the CRT-Paillier homomorphic encryption algorithm and the public key to encrypt and aggregate the summed power consumption to obtain encrypted data; the encrypted data is transmitted to the outsourcing cloud through an edge computing node, and the outsourcing cloud encrypts the encrypted data with the public key of the power grid control center and then transmits it to the power grid control center; the power grid control center sends a request to the outsourcing cloud to obtain the encrypted data of the intelligent electricity meter, and then uses the private key to decrypt the encrypted data to obtain the power consumption data of the intelligent electricity meter. The present invention can not only fully reduce the overall time cost, but also effectively ensure the reliability of the encrypted data, so as to guarantee the security of the intelligent electricity meter data.

Description

Technical Field

[0001] The present invention belongs to the fields of power systems and information security, and particularly relates to a method for protecting smart meter data based on a homomorphic encryption algorithm. Background Art

[0002] In the era of distributed assets in smart distribution networks, the data related to the operation of these assets has become extremely valuable and useful. The combination of traditional electrical networks with the latest developments in modern information and communication technologies, especially the introduction of Internet of Things connected devices, has the potential to better manage and control the distribution system. For smart meters, increasing communication with connected devices can improve operational efficiency, reduce energy losses, and enhance the reliability of the distribution system. In the big data era, this data has become very useful and valuable to system operators and energy retailers. In a distribution system, the main source of this data is smart meters, which can record energy usage in fine granularity. The use of smart meters has opened up new possibilities for interaction between energy retailers and consumers. Although this interaction can bring many benefits to all parties, the privacy of consumer data remains a concern. There is an obvious trade-off between the utility of the data and the privacy of consumers. Therefore, it is of great significance to protect consumer data under the premise of this interaction.

[0003] The patent document with the application publication number CN112751672A discloses an adaptive data encryption protection method and system based on multiple parameters. Its operation mainly encrypts the text to be encrypted twice, generates a parameter list according to requirements, and specifies that only users with identity ids 1 - 10 can receive the data within 1 minute on a terminal that defaults to using Chinese. This parameter list serves as the public key for the first encryption, and then the AES algorithm is used to perform the second encryption using the public key. This patent encrypts twice, which is of great help in improving the privacy of the text, but the decryption takes a long time and the data security cannot be fully guaranteed. The patent document with the application publication number CN113949591A discloses a data encryption protection method and system based on blockchain. It mainly responds to the request signal for the data upload terminal to store the data to be encrypted in the blockchain, obtains the security evaluation feature data of the data upload terminal; calculates the security and reliability value of the data upload terminal according to the security evaluation feature data of the data upload terminal; compares the size of the security and reliability value with a preset first threshold. If the security and reliability value is greater than the preset first threshold, the data to be encrypted of the data upload terminal is uploaded to the encryption node of the blockchain and encrypted; otherwise, the method of prohibiting the data to be encrypted of the data upload terminal from being uploaded to the blockchain is adopted. Although this patent improves the reliability of the data upload terminal, the method of calculating the security and reliability value first takes a long time and is not applicable to all terminals. The above methods are difficult to meet the two requirements of rapidity and reliability of data encryption at the same time. Summary of the Invention

[0004] The object of the present invention is to ensure the privacy and security of user data during the data transmission process of smart meters, and a smart meter data protection method based on a homomorphic encryption algorithm is proposed, which provides reliable protection for the encryption of meter data and can also provide a faster decryption speed than traditional methods.

[0005] A smart meter data protection method based on a homomorphic encryption algorithm includes the following steps:

[0006] Step 1: The smart meter collects the power consumption of the user every preset time period and sums up the power consumption.

[0007] Step 2: A trusted institution generates the public key and private key required for the Paillier homomorphic encryption of the Chinese Remainder Theorem for the smart meter, and uses the CRT-Paillier homomorphic encryption algorithm and the public key to encrypt and aggregate the total power consumption obtained in Step 1 to obtain encrypted data.

[0008] Step 3: The encrypted data is transmitted to the outsourcing cloud through the edge computing node , and , and the outsourcing cloud and encrypt the encrypted data with the public key of the power grid control center, and only the power grid control center can decrypt it with the private key, and then transmit it to the outsourcing cloud for storage;

[0009] Step 4: The power grid control center sends a request to the outsourcing cloud to obtain the encrypted data of the smart meter, and then uses the private key to decrypt the encrypted data to obtain the power consumption data of the smart meter.

[0010] Furthermore, the preset time period is 3 - 5 minutes.

[0011] Furthermore, Step 2 specifically includes:

[0012] Step 2-1: A trusted institution generates the public key and private key required for the CRT-Paillier homomorphic encryption for the smart meter;

[0013] Step 2-2: Use the CRT-Paillier homomorphic encryption algorithm and the public key to encrypt the total power consumption obtained in Step 1 to obtain the encrypted data of the power consumption in each time period;

[0014] Step 2-3: Use CRT-Paillier homomorphic aggregation to encrypt the power consumption data at different time intervals to obtain encrypted data , and .

[0015] Furthermore, in step 2-1, the specific steps for generating the public key and private key are:

[0016] Step 2-1-1: Private Key of and are randomly selected large prime numbers of equal length and must satisfy:

[0017] (1);

[0018] In the formula: gcd is the greatest common divisor;

[0019] Step 2-1-2: Public Key middle ,calculate ,in represents the least common multiple. Then choose an integer ( express middle A set of mutually prime elements) and satisfying:

[0020] (2);

[0021] Where: , express Divide by Take the remainder.

[0022] Furthermore, the total power consumption in step 1 is encrypted using the CRT-Paillier homomorphic encryption algorithm, and the specific process is as follows:

[0023] Step 2-2-1: For different time intervals ( and ) power consumption and For encryption, enter the public key of the edge computing node and different time intervals ( and ) power consumption and ;

[0024] Step 2-2-2: Choose a random number ,and Needs to be satisfied and , where denotes the set of elements in that are relatively prime to

[0025] Step 2-2-3: Calculate the encrypted data and according to formula (3):

[0026] (3);

[0027] In the formula: denotes the th power of denotes the th power of

[0028] Step 2-2-4: Take the modulus of their product with to obtain the encrypted data and , and then send the encrypted data and to the edge computing node.

[0029] Furthermore, in Step 2-3, after receiving the encrypted data of multiple smart meters, the edge computing node uses the homomorphic property of CRT-Paillier to aggregate and re-encrypt the power consumption data at different time intervals. The specific process of aggregating and re-encrypting the power consumption data at different time intervals is as follows:

[0030] Step 2-3-1: For the encrypted data and , calculate:

[0031] (4);

[0032] Step 2-3-2: The edge computing node generates two random numbers and , and through the outsourcing cloud , and 's public keys , and , where the calculation methods of the public keys of the outsourcing cloud and the edge computing node are the same, but the specific values are different, and are given by a trusted institution respectively. Calculate , and , where is:

[0033] (5);

[0034] In the formula: is the aggregated encrypted data by the edge computing node using the private key obtained;

[0035] Step 2-3-3: Input the encrypted data and the private key , define and function:

[0036] (6);

[0037] Step 2-3-4: Calculate and through Equation (7):

[0038] (7);

[0039] Step 2-3-5: Calculate and through Equation (8):

[0040] (8);

[0041] Step 2-3-6: Use CRT to calculate , and , the formula is:

[0042] (9);

[0043] In the formula: The CRT function is used to calculate and to calculate , and .

[0044] Furthermore, in Step 3, the edge computing node respectively transmits , and to the outsourced cloud , and , and the specific process of the encrypted data in the outsourced cloud is as follows:

[0045] Step 3-1: After receiving the encrypted data , first use the private key to decrypt the encrypted data to obtain ;

[0046] Step 3-2: Use the public key of PGCC to perform re-encryption to obtain , and then transmit the encrypted data to ;

[0047] Step 3-3: After receiving the encrypted data , first use the private key to decrypt the encrypted data to obtain , and then use the public key of PGCC to perform re-encryption to obtain , and then transmit the encrypted data to ;

[0048] Step 3-4: After receiving the encrypted data from ECN and the encrypted data from and the encrypted data from , and the encrypted data from , use the private key to decrypt to obtain , use the public key to encrypt to obtain ;

[0049] Step 3-5: Calculate the encrypted data through Equation (10):

[0050] (10);

[0051] Store the data encrypted data , which is encrypted using the public key of PGCC and can only be decrypted by PGCC using the private key .

[0052] Furthermore, in Step 4, the grid control center sends two requests to the outsourced cloud : one is an ID-based query, and the other is a time-based query.

[0053] Furthermore, in step 4, when the power grid control center needs to query the power consumption of a specific smart meter, an ID-based query is initiated; when the power grid control center needs to query the power consumption of a smart meter for a period of time, a time-based query is initiated; the specific process is:

[0054] Step 4-1: PGCC will contain smart meter ID information Send to ;

[0055] Step 4-2: After receiving the query request, The ID in is mapped to the encrypted data stored The corresponding ID in;

[0056] Step 4-3: Perform multiplication operation on the encrypted power consumption data of all smart meters within the query range at the corresponding time. calculate:

[0057] (11);

[0058] Step 4-4: Outsourcing Cloud Will contain the request The encrypted power consumption is sent to PGCC. After receiving it, PGCC uses its own private key Decrypt it to get the actual power consumption data and obtain these Power consumption during a specific period of time;

[0059] Step 4-5: PGCC will U time = { SM i , [ t 1 , t p ] } Send inquiries to , which contains a single An identifier and a time interval arrive The time between Calculate the number of queries received within a specified time interval Encryption power consumption:

[0060] (12);

[0061] Steps 4-6: The calculated Sent to PGCC, PGCC uses the private key Decrypt it to obtain exist arrive The actual power consumption data within the time interval, to understand Electricity usage during a specific time period.

[0062] Compared with the prior art, the present invention has the following technical effects:

[0063] 1) Based on CRT-Paillier homomorphic encryption, the present invention encrypts and protects the electricity meter data, and through the optimization of the key generation, encryption, and decryption processes, reduces the overall computational complexity, thereby reducing the computational complexity and significantly reducing the decryption time.

[0064] 2) The present invention proposes a method and system for protecting smart meter data based on a homomorphic encryption algorithm, which can provide an effective solution for protecting data privacy and security. By aggregating data in the ciphertext state, the leakage of sensitive information can be avoided, and the obtained data aggregation result is highly consistent with the plaintext data. BRIEF DESCRIPTION OF THE DRAWINGS

[0065] Figure 1 is a schematic diagram of the encryption transmission system of the present invention;

[0066] Figure 2 is a flowchart of a method for protecting smart meter data based on a homomorphic encryption algorithm according to the present invention;

[0067] Figure 3 is a schematic diagram of the number of smart meters and the computational time cost of each part according to the present invention. DETAILED DESCRIPTION OF THE EMBODIMENTS

[0068] To make the objectives, technical solutions, and advantages of the embodiments of the present invention clearer, the technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings in the embodiments of the present invention. Apparently, the described embodiments are some, but not all, of the embodiments of the present invention. All other embodiments obtained by those of ordinary skill in the art based on the embodiments of the present invention without creative efforts shall fall within the protection scope of the present invention.

[0069] An embodiment of the present invention proposes a method for protecting smart meter data based on a homomorphic encryption algorithm, as Figure 2 shown, the method includes the following steps:

[0070] Step 1: The smart meter collects the power consumption of the user at preset intervals and sums up the power consumption;

[0071] Step 2: A trusted institution generates the public key and private key required for the Paillier homomorphic encryption of the Chinese Remainder Theorem for the smart meter, and encrypts and aggregates the total power consumption obtained in Step 1 using the CRT-Paillier homomorphic encryption algorithm and the public key to obtain encrypted data;

[0072] Step 3: Transmit the encrypted data to the outsourcing cloud through the edge computing node respectively , and , and After processing, new encrypted data is obtained. This encrypted data is encrypted with the public key of the power grid control center and can only be decrypted with the private key by the power grid control center, and then transmitted to for storage;

[0073] Step 4: The power grid control center sends a request to the outsourced cloud to obtain the encrypted data of the smart meter, and then uses the private key to decrypt the encrypted data to obtain the power consumption data of the smart meter.

[0074] In Step 1, the preset time period is 3 - 5 minutes.

[0075] Step 2 specifically includes:

[0076] Step 2 - 1: The trusted agency generates the public key and private key required for CRT - Paillier homomorphic encryption for the smart meter;

[0077] Step 2 - 2: Use the CRT - Paillier homomorphic encryption algorithm and the public key to encrypt the total power consumption obtained in Step 1 to obtain the encrypted data of the power consumption in each time period;

[0078] Step 2 - 3: Utilize the homomorphism of CRT - Paillier to aggregate and re - encrypt the power consumption data at different time intervals to obtain the encrypted data , and .

[0079] In Step 2 - 1, the specific generation steps of the public key and private key are:

[0080] Step 2 - 1 - 1: The and of the private key are randomly selected large prime numbers of equal length and must satisfy:

[0081] (1);

[0082] where gcd is the greatest common divisor.

[0083] Step 2 - 1 - 2: In the public key , calculate , where represents the least common multiple. Then select an integer ( ( represents China a set of relatively prime elements), and must satisfy:

[0084] (2);

[0085] In the formula: , represents divided by taking the remainder.

[0086] In step 2-2, the power consumption of the total in step 1 is encrypted using the CRT-Paillier homomorphic encryption algorithm. The specific process is mainly as follows:

[0087] Step 2-2-1: Encrypt the power consumption at different time intervals ( and ), input the public key of the edge computing node and and the power consumption at different time intervals ( and and ), the power consumption and ;

[0088] Step 2-2-2: Select a random number , while needs to satisfy and , where represents the set of elements relatively prime to in

[0089] Step 2-2-3: Calculate the encrypted data and according to formula (3):

[0090] (3);

[0091] In the formula: represents to the th power, represents to the th power;

[0092] Step 2-2-4: Take the modulus of their product with to obtain the encrypted data and , and then send the encrypted data and to the edge computing node.

[0093] In Step 2-3, after receiving the encrypted data from multiple smart meters, the edge computing node aggregates and re-encrypts the power consumption data at different time intervals by using the homomorphic property of CRT-Paillier. The specific process of aggregating and re-encrypting the power consumption data at different time intervals is as follows:

[0094] Step 2-3-1: For the encrypted data and , calculate:

[0095] (4);

[0096] Step 2-3-2: The edge computing node generates two random numbers and , and through the outsourcing cloud , and 's public keys , and , where the calculation methods of the public keys of the outsourcing cloud and the edge computing node are the same, but the specific values are different, and are given by a trusted institution respectively. Calculate , and , where is:

[0097] (5);

[0098] In the formula: is what the edge computing node obtains by using the private key for the aggregated encrypted data ;

[0099] Step 2-3-3: Input the encrypted data and the private key , and define and functions:

[0100] (6);

[0101] Step 2-3-4: Calculate and through Equation (7):

[0102] (7);

[0103] Step 2-3-5: Calculate and through Equation (8):

[0104] (8);

[0105] Step 2-3-6: Calculate using CRT , and , the formula is:

[0106] (9);

[0107] Where: CRT function is used according to and To calculate , and .

[0108] In step 3, the edge computing nodes respectively , and Transfer to outsourced cloud , and ,The specific process of encrypting data in the outsourcing cloud is:

[0109] Step 3-1: Receive encrypted data Then, use the private key Encrypted data Decrypt it and get ;

[0110] Step 3-2: Use PGCC's public key Re-encrypt to get ,Then The encrypted data Transfer to ;

[0111] Step 3-3: Receive encrypted data Then, use the private key Encrypted data Decrypt it and get ,after Use PGCC's public key Re-encrypt to get ,Then The encrypted data Transfer to ;

[0112] Step 3-4: Receive encrypted data from ECN and from Encrypted data , Encrypted data After Use the private key To decrypt To obtain , Use the public key To encrypt , to obtain ;

[0113] Step 3-5: Calculate the encrypted data through Equation (10) :

[0114] (10);

[0115] Store the data encrypted data , and this data is encrypted using the public key of PGCC, and only PGCC can use the private key To decrypt it.

[0116] In Step 4, the power grid control center sends two requests to the outsourced cloud : One is an ID-based query, and the other is a time-based query.

[0117] In Step 4, when the power grid control center needs to query the power consumption of a specific smart meter, it will initiate an ID-based query; when the power grid control center needs to query the power consumption of a smart meter for a period of time, it will initiate a time-based query. Their specific processes are as follows:

[0118] Step 4-1: PGCC sends the one containing the smart meter ID information To ;

[0119] Step 4-2: After receiving the query request, it will map the ID in To the corresponding ID in the stored encrypted data ;

[0120] Step 4-3: Calculate (perform multiplication operation) the encrypted power consumption data of all smart meters within the query range at the corresponding time. This calculation utilizes the homomorphic encryption property of the Paillier cryptosystem and operates on the encrypted data without decryption. Calculate:

[0121] (11);

[0122] Step 4-4: The outsourced cloud Sends the one containing the encrypted power consumption of the request To PGCC. After receiving it, PGCC uses its own private key Decrypt it to obtain the actual power consumption data and acquire this power consumption usage within a specific time period;

[0123] Step 4-5: PGCC will U time = { SM i , [ t 1 , t p ] } send the query to , which contains the identifier of a single and a time interval from to the time between Calculate the encrypted power consumption within the specified time interval according to the received query :

[0124] (12);

[0125] Step 4-6: Send the calculated to PGCC, and PGCC uses the private key to decrypt it to obtain the actual power consumption data within the time interval from to and understand the electricity consumption situation within a specific time period.

[0126] Example:

[0127] The example used in the present invention is based on Intel Celeron CPU B840 @ 1.90 GHz, Ubuntu 20.04 operating system, and Python version 3.7.4 with 4GB RAM. A series of experiments were carried out on the publicly available REDD dataset. This dataset contains the electricity consumption of 6 different households, where each household contains the electricity consumption of 20 different appliances over 3 to 19 days. This section analyzes the communication and computational costs and decryption time between the smart meter, edge computing node, outsourced cloud, and grid control center. These costs depend on the processing speed of the network and the machine and must be taken into account. Therefore, we compare the proposed system (as Figure 1 shown) with previous work. The performance of the proposed model is analyzed in terms of message transmission cost, and the message flow parameters are described next. The cryptographic operations are implemented through the well-known cryptographic library Paillier. Finally, the characteristics of the existing method are compared with the proposed work.

[0128] Key generation time , encryption time , decryption time and aggregation time The calculation and description are shown in Table 1. The key is generated once for all entities, such as SM, ECN, C1, C2, C3, and PGCC. The relationship between the number of smart meters and the computational time cost is as Figure 3 shown. Therefore, the key generation time has a relatively poor effect on the overall time cost of the proposed model.

[0129] Table 1

[0130] The smart meter data protection model (Smart Meter Data Protect, SMDP) proposed in the present invention is compared with existing models and solutions that provide privacy protection for smart meter data aggregation. Table 2 shows the feature comparison between the proposed model and existing models and solutions. The features are compared in terms of privacy protection, data aggregation, consideration of smart grid architecture, query processing, and encryption algorithms. It can be concluded from the comparison that the solution proposed in the present invention is functionally superior to existing models and solutions.

[0131] Table 2

[0132] It can be seen from the test results that the smart meter data protection method based on the homomorphic encryption algorithm proposed in the present invention can effectively reduce the overall time cost, which is of great significance for the privacy protection of smart meter data.

[0133] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention and are not intended to limit them. Those of ordinary skill in the art can still modify the specific implementation manners of the present invention or make equivalent replacements according to the above embodiments. Any modifications or equivalent replacements that do not depart from the spirit and scope of the present invention are within the scope of the claims of the present invention pending approval.

Claims

1. An intelligent electric meter data protection method based on a homomorphic encryption algorithm, characterized in that It includes the following steps: Step 1: The smart meter collects the power consumption of the user every preset period and sums up the power consumption; Step 2: A trusted institution generates the public key and private key required for the Paillier homomorphic encryption of the Chinese Remainder Theorem for the smart meter, and uses the CRT-Paillier homomorphic encryption algorithm and the public key to encrypt and aggregate the total power consumption obtained in Step 1 to obtain encrypted data; Step 3: Transmit the encrypted data to the outsourced cloud through the edge computing node respectively , and , and the outsourced cloud and encrypts the encrypted data with the public key of the power grid control center, and only the power grid control center can decrypt it with the private key, and then transmits it to the outsourced cloud for storage; Step 4: The power grid control center sends a request to the outsourced cloud to obtain the encrypted data of the smart meter, and then uses the private key to decrypt the encrypted data to obtain the power consumption data of the smart meter; In step 4, the power grid control center sends two requests to the outsourced cloud: one is an ID-based query and the other is a time-based query; ​ In Step 4, when the power grid control center needs to query the power consumption usage of a specific smart meter, it initiates an ID-based query; when the power grid control center needs to query the power consumption of a certain smart meter for a period of time, it initiates a time-based query; the specific process is as follows: Step 4-1: PGCC sends the one containing the smart meter ID information to ; Step 4-2: After receiving the query request, map the ID in to the corresponding ID in the stored encrypted data ; Step 4-3: Perform a multiplication operation on the encrypted power consumption data of all smart meters within the query range at the corresponding time, Calculate: (11); Step 4-4: Outsourced Cloud Send the encrypted power consumption containing the request to PGCC. After receiving it, PGCC uses its own private key to decrypt it, so as to obtain the actual power consumption data and get these power consumption usage within a specific time; Step 4-5: The PGCC will send the query to , which contains the identifier of a single and a time interval from to Based on the received query, calculate the encrypted power consumption of within the specified time interval: (12); Step 4 - 6: Send the calculated to PGCC. PGCC uses the private key to decrypt it, so as to obtain the actual power consumption data within the to time interval, and understand the electricity consumption situation during a specific period.

2. The method according to claim 1, wherein: In Step 1, the preset period is 3 - 5 minutes.

3. The method according to claim 1, characterized in that: Step 2 specifically includes: Step 2-1: The trusted institution generates the public key and private key required for the CRT-Paillier homomorphic encryption for the smart meter. and the private key ; Step 2-2: Use the public key to encrypt the total power consumption obtained in Step 1 to obtain the encrypted data of the power consumption in each time period; Step 2-3: Use CRT-Paillier homomorphic aggregation to encrypt the power consumption data at different time intervals to obtain encrypted data , and .

4. The method according to claim 3, wherein: In Step 2-1, the specific generation steps of the public key and private key are: Step 2-1-1: Private key and are randomly selected large prime numbers of equal length, and must satisfy: (1); In the formula: gcd is the greatest common divisor; Step 2-1-2: Public key in , calculate , where denotes the least common multiple, and then select an integer , denotes in the set of elements that are relatively prime, and must satisfy: (2); In the formula: , represents divided by taking the remainder.

5. The method according to claim 3, wherein: In Step 2-2, the total power consumption obtained in Step 1 is encrypted using the CRT-Paillier homomorphic encryption algorithm, and its specific process is mainly: Step 2-2-1: Encrypt the power consumption at different time intervals and , input the public key of the edge computing node and the power consumption at different time intervals and ; Step 2-2-2: Select a random number , while needs to satisfy and , where represents the set of elements relatively prime to in; Step 2-2-3: Calculate the encrypted data according to formula (3) and : (3); In the formula: represents to the power, represents to the power; Step 2-2-4: Take the modulo of their product with to obtain the encrypted data and , and then send the encrypted data and to the edge computing node.

6. The method according to claim 3, wherein: In Step 2-3, after receiving the encrypted data of multiple smart meters, the edge computing node aggregates and re-encrypts the power consumption data at different time intervals using the homomorphic property of CRT-Paillier. The specific process of aggregating and re-encrypting the power consumption data at different time intervals is: Step 2-3-1: For the encrypted data and , calculate: (4); Step 2-3-2: The edge computing node generates two random numbers and , and through the outsourcing cloud , and 's public keys , and . Here, the calculation methods of the public keys of the outsourcing cloud and the edge computing node are the same, but the specific values are different, which are given by the trusted institution respectively. Calculate , and , where is: (5); In the formula: is the aggregated encrypted data by the edge computing node using the private key obtained; Step 2-3-3: Input encrypted data and the private key , define and function: (6); Step 2-3-4: Calculate through Equation (7) and : (7); Step 2-3-5: Calculate using Equation (8) and : (8); Step 2-3-6: Calculate using CRT , and , the formula is: (9); Where: The CRT function is used to calculate according to and to calculate , and .

7. The method according to claim 1, wherein: In step 3, the edge computing nodes respectively transmit , and to the outsourcing cloud , and . The specific process of the encrypted data in the outsourcing cloud is as follows: Step 3-1: After receiving the encrypted data , first use the private key to decrypt the encrypted data and obtain ; Step 3-2: Use the public key of PGCC to perform re-encryption to obtain , and then transfer the encrypted data to ; Step 3-3: Receive the encrypted data After that, first use the private key to decrypt the encrypted data to obtain , and then use the public key of PGCC to re-encrypt to obtain , and then transfer the encrypted data to ; Step 3-4: Receive the encrypted data from the ECN and the encrypted data from the , the encrypted data of After that, Use the private key to decrypt to obtain , Use the public key to encrypt to obtain ; Step 3-5: Calculate the encrypted data using Equation (10) :[[]]END]] (10); Stored data encrypted data , which is encrypted using the public key of PGCC and can only be decrypted by PGCC using the private key to decrypt it.

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