A supply chain data management method based on privacy computing

Abstract

The present invention discloses a supply chain data management method based on privacy computing, which belongs to the field of data processing technology. By adopting privacy computing technology, it realizes encryption processing and efficient management of supply chain data, ensuring the security, privacy and reliability of data during the circulation process. At the same time, the key is fragmented and decentralized, which can effectively prevent key leakage and loss, and can greatly improve data security. This method is applicable to various supply chain scenarios, helps to improve supply chain collaboration efficiency, and reduce the risk of data leakage.

Description

Technical Field

[0001] The present invention belongs to the field of data processing technology, and specifically relates to a supply chain data management method based on privacy computing. Background Art

[0002] The supply chain refers to the collection of all links and activities involved in the entire process, from raw material procurement, manufacturing, product distribution, to final delivery to consumers. It encompasses all organizations, people, activities, information flows, and resources involved in producing goods or providing services. With the rapid development of supply chains, supply chain data management has become increasingly important. Supply chain data refers to the various information generated throughout the entire supply chain operation, including data from raw material procurement, manufacturing, inventory management, logistics distribution, sales channels, and end-user services. Existing technologies often require the collection, exchange, or sharing of specific supply chain data. However, existing technologies pose issues such as privacy leakage and data security during data sharing. Summary of the Invention

[0003] The present invention provides a supply chain data management method based on privacy computing to solve the problems of privacy leakage and data security existing in the prior art.

[0004] A supply chain data management method based on privacy computing, comprising:

[0005] Issuing a first key pair consisting of a first public key and a second private key to each supply chain node;

[0006] Obtain a privacy-preserving computing task request transmitted by a first target supply chain node for data to be calculated, and, based on the privacy-preserving computing task request, use a privacy-preserving computing algorithm to generate a second key pair consisting of a second public key and a second private key for temporarily managing the data;

[0007] Distributing the second public key in the second key pair to each supply chain node, and fragmenting the second private key in the second key pair to obtain a number of second private key fragments equal to the number of supply chain nodes;

[0008] Encrypting the second private key fragments one-to-one using the first public key of the first key pair corresponding to the supply chain node, and distributing the encrypted second private key fragments to the corresponding supply chain node;

[0009] Randomly select a supply chain node other than the first target supply chain node to obtain a second target supply chain node, and broadcast the second target supply chain node and the corresponding privacy computing task required data to all supply chain nodes, so that each supply chain node encrypts the data required for the privacy computing task using the second public key and transmits it to the second target supply chain node;

[0010] After the second target supply chain node uses a privacy computing algorithm to perform privacy computing on the data required for the privacy computing task transmitted by all supply chain nodes, it obtains the privacy computing result, and transmits the privacy computing result back to the first target supply chain node;

[0011] Randomly broadcasting the first target supply chain node and the first public key corresponding to the first target supply chain node to a preset number of supply chain nodes, so that the supply chain node encrypts its own second private key fragment using the first public key corresponding to the first target supply chain node and transmits it to the first target supply chain node;

[0012] The received second private key fragments are recovered by the first target supply chain node to obtain the second private key, and the second private key is used to decrypt the privacy calculation result to obtain the calculation result corresponding to the privacy calculation task.

[0013] Furthermore, a first key pair consisting of a first public key and a second private key is issued to each supply chain node, including:

[0014] For any supply chain node, an asymmetric encryption algorithm is used to generate a first key pair consisting of a first public key and a second private key;

[0015] Traverse all supply chain nodes to obtain a first key pair consisting of a first public key and a second private key issued by each supply chain node.

[0016] Furthermore, a privacy computing algorithm is used to generate a second key pair consisting of a second public key and a second private key for temporarily managing data, including:

[0017] Based on a preset length l, a first prime number p and a second prime number q are randomly selected from numbers whose length is greater than the preset length l;

[0018] Generate a first public key parameter n according to the first prime number p and the second prime number q, which is the first prime number p*the first prime number p*the second prime number q;

[0019] From a finite field Randomly select a generator g from g so that g p =g p-1 modp 2 The order is p, gcd(p,q-1)=1 and gcd(p-1,q)=1; where g p represents the intermediate parameter, mod represents the remainder function, and gcd represents the greatest common factor algorithm;

[0020] According to the generator g and the first public key parameter n, the second public key parameter h is generated as g n modn;

[0021] Generate effective time parameter t;

[0022] According to the first public key parameter n, the generator g and the second public key parameter h, a second public key pk for temporary management data is generated as: (n, g, h);

[0023] According to the first prime number p and the second prime number q, a second private key sk for temporary management data is generated as: (p, q);

[0024] A second key pair is obtained according to the valid time parameter t, the second public key pk and the second private key sk.

[0025] Furthermore, distributing the second public key in the second key pair to each supply chain node includes: broadcasting the second public key in the second key pair to all supply chain nodes in a broadcasting manner.

[0026] Furthermore, the second private key in the second key pair is fragmented to obtain a plurality of second private key fragments equal to the number of supply chain nodes, including:

[0027] Take out the second private key sk from the second key pair, and obtain the first prime number p and the second prime number q;

[0028] Fragmenting the first prime number p to obtain a plurality of first target fragments;

[0029] Fragmenting the second prime number q to obtain a plurality of second target fragments; wherein the number of the first target fragments is the same as the number of the second target fragments;

[0030] Randomly matching the first target fragments with the second target fragments one by one to obtain mutually related first target fragments and second target fragments;

[0031] According to the mutually associated first target fragment and second target fragment, the second private key fragment is obtained as (t, s1, s2); wherein s1 represents the first target fragment, and s2 represents the second target fragment.

[0032] Furthermore, the fragmentation process of the first prime number p is the same as the fragmentation process of the second prime number q, and both include:

[0033] Obtaining a fragmentation number M of the first target fragment or the second target fragment;

[0034] For the key to be fragmented, a K-order polynomial is generated as:

[0035] f(x)=a0+a1x 1 +a2x 2 +...+aK x K

[0036] The key to be fragmented represents the first prime number p or the second prime number q, f(x) represents a K-order polynomial, a0 represents the key to be fragmented, a1, a2, ..., a K They represent the 1st, 2nd, …, Kth coefficients respectively, K is equal to M / 2, and x represents the independent variable;

[0037] Let the independent variable x be a random value, and determine the corresponding dependent variable of the K-order polynomial f(x) to be y;

[0038] According to the independent variable x and the dependent variable y, the target fragment is determined to be (t, x, y); wherein the target fragment is the first target fragment or the second target fragment;

[0039] Repeatedly obtain K different target fragments to complete the fragmentation process.

[0040] Furthermore, the data required for the privacy computing task is encrypted using the second public key as follows:

[0041] c=g m h r modn

[0042] Among them, m represents the plaintext of the data required for the privacy computing task, c represents the ciphertext of the data required for the privacy computing task, and r represents the finite field Random numbers in .

[0043] Furthermore, the second target supply chain node uses a privacy computing algorithm to perform privacy computing on the data required for the privacy computing task transmitted by all supply chain nodes, and obtains privacy computing results, including:

[0044] The data required for the privacy computing task transmitted by all supply chain nodes is summed up through the second target supply chain node, and no encryption or decryption is performed during the calculation process to obtain the privacy computing result.

[0045] Furthermore, randomly broadcasting the first target supply chain node and the first public key corresponding to the first target supply chain node to a preset number of supply chain nodes, so that the supply chain node encrypts its own second private key fragment using the first public key corresponding to the first target supply chain node and transmits it to the first target supply chain node, including:

[0046] Determine a preset number L that is greater than M / 2;

[0047] Randomly broadcast the first target supply chain node and the first public key corresponding to the first target supply chain node to L supply chain nodes;

[0048] The supply chain node determines whether the storage time of the valid time parameter t is greater than t. If so, it is determined that the second key pair has expired and the supply chain data management is terminated. Otherwise, the second private key fragment is encrypted with the first public key corresponding to the first target supply chain node and transmitted to the first target supply chain node.

[0049] Furthermore, the first target supply chain node recovers the received second private key fragments to obtain the second private key, and uses the second private key to decrypt the privacy computing result to obtain the calculation result corresponding to the privacy computing task, including:

[0050] Generate a K-order polynomial with a constant term, decrypt the K-order polynomial using the received second private key fragment through the first target supply chain node, and use the constant term in the decrypted K-order polynomial as the second private key;

[0051] The second private key is used to decrypt the privacy computing result to obtain the calculation result corresponding to the privacy computing task.

[0052] The present invention provides a supply chain data management method based on privacy computing. By adopting privacy computing technology, it realizes encryption processing and efficient management of supply chain data, ensuring the security, privacy and reliability of data during the circulation process. At the same time, the key is fragmented and decentralized, which can effectively prevent key leakage and loss, and can greatly improve data security. This method is applicable to various supply chain scenarios, helps to improve supply chain collaboration efficiency, and reduce the risk of data leakage. BRIEF DESCRIPTION OF THE DRAWINGS

[0053] The accompanying drawings, which are incorporated in and constitute a part of this specification, illustrate embodiments consistent with the invention and, together with the description, serve to explain the principles of the invention.

[0054] Figure 1 A flowchart of a supply chain data management method based on privacy computing provided in an embodiment of the present invention.

[0055] The above drawings illustrate specific embodiments of the present invention, which will be described in more detail below. These drawings and the accompanying description are not intended to limit the scope of the present invention in any way, but rather to illustrate the concept of the present invention to those skilled in the art by reference to specific embodiments. DETAILED DESCRIPTION

[0056] Exemplary embodiments will be described in detail herein, examples of which are illustrated in the accompanying drawings. In the following description, when referring to the drawings, like numbers in different figures represent like or similar elements unless otherwise indicated. The embodiments described in the following exemplary embodiments are not intended to represent all possible embodiments consistent with the present invention. Rather, they are merely examples of apparatus and methods consistent with certain aspects of the present invention, as detailed in the appended claims.

[0057] The embodiments of the present invention will be described in detail below with reference to the accompanying drawings.

[0058] like Figure 1 As shown, an embodiment of the present invention provides a supply chain data management method based on privacy computing, including:

[0059] S101. Issue a first key pair consisting of a first public key and a second private key to each supply chain node;

[0060] In supply chain management, to ensure data security and privacy, key pairs, consisting of public and private keys, can be issued to each supply chain node. The primary key pair can be generated centrally or by each supply chain node. When a supply chain node generates its primary key pair, it must broadcast its public key to all other supply chain nodes for information exchange.

[0061] It is worth noting that in addition to suppliers, supply chain nodes can also include demanders, which facilitates private data interaction, greatly ensures data security, and can effectively avoid privacy leaks.

[0062] S102: Obtain a privacy-preserving computing task request transmitted by a first target supply chain node for data to be calculated, and generate, based on the privacy-preserving computing task request, a second key pair consisting of a second public key and a second private key for temporarily managing the data using a privacy-preserving computing algorithm;

[0063] The privacy computing task request transmitted by the first target supply chain node of the data to be calculated can be a statistic of a certain data or a vote on a certain option. Then, a privacy computing algorithm is used to generate a second key pair consisting of a second public key and a second private key for temporary management of data. Privacy computing can be performed based on the second key pair, thereby effectively ensuring the data security of each supply chain node.

[0064] S103: Distribute the second public key in the second key pair to each supply chain node, and fragment the second private key in the second key pair to obtain a number of second private key fragments equal to the number of supply chain nodes;

[0065] The second public key can encrypt data and perform privacy calculations, thereby effectively ensuring data security. Therefore, the second public key in the second key pair needs to be distributed to each supply chain node so that each supply chain node can perform privacy encryption calculations.

[0066] By fragmenting the second private key in the second key pair, joint key management can be achieved. Only after obtaining the consent of multiple parties can the corresponding key be used for decryption, thereby greatly improving data security.

[0067] S104: Encrypt the second private key fragments one-to-one using the first public key in the first key pair corresponding to the supply chain node, and distribute the encrypted second private key fragments to the corresponding supply chain node;

[0068] In order to avoid key leakage, an embodiment of the present invention constructs a key fragmentation method to fragment the second private key in the second key pair, thereby realizing key decentralization. The second private key fragments can be encrypted and transmitted through the first public key corresponding to each supply chain node, thereby increasing the difficulty of cracking exponentially, which can greatly improve the security of the algorithm and be applicable to more scenarios.

[0069] S105. Randomly select another supply chain node other than the first target supply chain node to obtain a second target supply chain node, and broadcast the second target supply chain node and the corresponding privacy-preserving computing task data to all supply chain nodes, so that each supply chain node encrypts the privacy-preserving computing task data using the second public key and transmits the encrypted data to the second target supply chain node.

[0070] Since the second target supply chain node can only have its own second private key fragments and cannot obtain the second private key fragments corresponding to other supply chain nodes, the second target supply chain node cannot view the encrypted data. Therefore, the second target supply chain node can be broadcast to enable other supply chain nodes to encrypt the data required for the privacy computing task and then transmit it to the second target supply chain node for privacy computing, thereby effectively protecting the data security and privacy corresponding to each supply chain node.

[0071] S106. After performing privacy computing on the data required for the privacy computing task transmitted by all supply chain nodes using a privacy computing algorithm, the second target supply chain node obtains a privacy computing result, and transmits the privacy computing result back to the first target supply chain node.

[0072] For example, suppose the privacy computing task is to count a certain data or vote on a certain question. In order to ensure the authenticity and privacy of the data, it is necessary to keep it confidential from each data holder and only display the final privacy computing result. The second target supply chain node can use the privacy computing algorithm to perform privacy computing on the data required for the privacy computing task transmitted by all supply chain nodes, so that the data can be calculated in an encrypted state, which can effectively ensure the privacy and data security of each supply chain.

[0073] S107. Randomly broadcast the first target supply chain node and the first public key corresponding to the first target supply chain node to a preset number of supply chain nodes, so that the supply chain node encrypts its own second private key fragment using the first public key corresponding to the first target supply chain node and transmits the encrypted fragment to the first target supply chain node.

[0074] The preset number refers to the number of second private keys that can be recovered through the second private key fragments. As long as it is greater than the minimum recovery number, the supply chain node will encrypt its own second private key fragments with the first public key corresponding to the first target supply chain node and transmit it to the first target supply chain node, and finally enable the first target supply chain node to decrypt the data, which ensures the security of each supply chain data and prevents others from obtaining the data, greatly improving the security and privacy of the data.

[0075] S108. Recover the received second private key fragments through the first target supply chain node to obtain the second private key, and use the second private key to decrypt the privacy computing result to obtain the calculation result corresponding to the privacy computing task.

[0076] The privacy calculation result is obtained by encrypting the data using the second public key. Therefore, the privacy calculation result can be decrypted after the second private key is restored through the second private key fragments.

[0077] The present invention provides a supply chain data management method based on privacy computing. By adopting privacy computing technology, it realizes encryption processing and efficient management of supply chain data, ensuring the security, privacy and reliability of data during the circulation process. At the same time, the key is fragmented and decentralized, which can effectively prevent key leakage and loss, and can greatly improve data security. This method is applicable to various supply chain scenarios, helps to improve supply chain collaboration efficiency, and reduce the risk of data leakage.

[0078] In an embodiment of the present invention, issuing a first key pair consisting of a first public key and a second private key to each supply chain node includes:

[0079] For any supply chain node, an asymmetric encryption algorithm is used to generate a first key pair consisting of a first public key and a second private key;

[0080] Traverse all supply chain nodes to obtain a first key pair consisting of a first public key and a second private key issued by each supply chain node.

[0081] Asymmetric encryption, also known as public-key encryption, is an encryption technique that uses a pair of keys: a public key and a private key. These two keys are mathematically related, but it's impossible to derive one from the other. Therefore, embodiments of the present invention use an asymmetric encryption algorithm to generate a first key pair consisting of a first public key and a second private key. This allows each supply chain node to encrypt and transmit fragments of the second private key, making it infinitely difficult to obtain or crack the second private key, significantly improving data security.

[0082] In an embodiment of the present invention, a privacy computing algorithm is used to generate a second key pair consisting of a second public key and a second private key for temporarily managing data, including:

[0083] Based on a preset length l, a first prime number p and a second prime number q are randomly selected from numbers whose length is greater than the preset length l;

[0084] Generate a first public key parameter n according to the first prime number p and the second prime number q, which is the first prime number p*the first prime number p*the second prime number q;

[0085] From a finite field Randomly select a generator g from g so that g p =g p-1 modp 2 The order is p, gcd(p,q-1)=1 and gcd(p-1,q)=1; where g p represents the intermediate parameter, mod represents the remainder function, and gcd represents the greatest common factor algorithm;

[0086] According to the generator g and the first public key parameter n, the second public key parameter h is generated as g n modn;

[0087] Generate effective time parameter t;

[0088] According to the first public key parameter n, the generator g and the second public key parameter h, a second public key pk for temporary management data is generated as: (n, g, h);

[0089] According to the first prime number p and the second prime number q, a second private key sk for temporary management data is generated as: (p, q);

[0090] A second key pair is obtained according to the valid time parameter t, the second public key pk and the second private key sk.

[0091] In an embodiment of the present invention, by setting the valid time parameter t, the second key pair can be made valid within a certain period of time, so that the second key pair is updated regularly. Even if a supply chain node has obtained the second private key, it is difficult to view the data in subsequent interactions. In addition, the second target supply chain node is randomly selected, which further increases the difficulty for the data to be obtained by illegal persons.

[0092] In an embodiment of the present invention, distributing the second public key in the second key pair to each supply chain node includes: broadcasting the second public key in the second key pair to all supply chain nodes in a broadcasting manner.

[0093] In an embodiment of the present invention, the second private key in the second key pair is fragmented to obtain a plurality of second private key fragments equal to the number of supply chain nodes, including:

[0094] Take out the second private key sk from the second key pair, and obtain the first prime number p and the second prime number q;

[0095] Fragmenting the first prime number p to obtain a plurality of first target fragments;

[0096] Fragmenting the second prime number q to obtain a plurality of second target fragments; wherein the number of the first target fragments is the same as the number of the second target fragments;

[0097] Randomly matching the first target fragments with the second target fragments one by one to obtain mutually related first target fragments and second target fragments;

[0098] According to the mutually associated first target fragment and second target fragment, the second private key fragment is obtained as (t, s1, s2); wherein s1 represents the first target fragment, and s2 represents the second target fragment.

[0099] In this embodiment of the present invention, the fragmentation process of the first prime number p is the same as the fragmentation process of the second prime number q, and both include:

[0100] Obtaining a fragmentation number M of the first target fragment or the second target fragment;

[0101] For the key to be fragmented, a K-order polynomial is generated as:

[0102] f(x)=a0+a1x 1 +a2x 2 +...+a K x K

[0103] The key to be fragmented represents the first prime number p or the second prime number q, f(x) represents a K-order polynomial, a0 represents the key to be fragmented, a1, a2, ..., a K They represent the 1st, 2nd, …, Kth coefficients respectively, K is equal to M / 2, and x represents the independent variable;

[0104] Let the independent variable x be a random value, and determine the corresponding dependent variable of the K-order polynomial f(x) to be y;

[0105] According to the independent variable x and the dependent variable y, the target fragment is determined to be (t, x, y); wherein the target fragment is the first target fragment or the second target fragment;

[0106] Repeatedly obtain K different target fragments to complete the fragmentation process.

[0107] In this embodiment of the present invention, the data required for the privacy computing task is encrypted using the second public key as follows:

[0108] c=g m h r modn

[0109] Among them, m represents the plaintext of the data required for the privacy computing task, c represents the ciphertext of the data required for the privacy computing task, and r represents the finite field Random numbers in .

[0110] In this embodiment of the present invention, after the second target supply chain node uses a privacy computing algorithm to perform privacy computing on the data required for the privacy computing task transmitted by all supply chain nodes, the privacy computing results obtained include:

[0111] The data required for the privacy computing task transmitted by all supply chain nodes is summed up through the second target supply chain node, and no encryption or decryption is performed during the calculation process to obtain the privacy computing result.

[0112] In an embodiment of the present invention, randomly broadcasting a first target supply chain node and a first public key corresponding to the first target supply chain node to a preset number of supply chain nodes, so that the supply chain node encrypts its own second private key fragment using the first public key corresponding to the first target supply chain node and transmits the encrypted fragment to the first target supply chain node, includes:

[0113] Determine a preset number L that is greater than M / 2;

[0114] Randomly broadcast the first target supply chain node and the first public key corresponding to the first target supply chain node to L supply chain nodes;

[0115] The supply chain node determines whether the storage time of the valid time parameter t is greater than t. If so, it is determined that the second key pair has expired and the supply chain data management is terminated. Otherwise, the second private key fragment is encrypted with the first public key corresponding to the first target supply chain node and transmitted to the first target supply chain node.

[0116] In this embodiment of the present invention, the first target supply chain node recovers the received second private key fragments to obtain the second private key, and uses the second private key to decrypt the privacy-preserving computing result to obtain the calculation result corresponding to the privacy-preserving computing task, including:

[0117] Generate a K-order polynomial with a constant term, decrypt the K-order polynomial using the received second private key fragment through the first target supply chain node, and use the constant term in the decrypted K-order polynomial as the second private key;

[0118] The second private key is used to decrypt the privacy computing result to obtain the calculation result corresponding to the privacy computing task.

[0119] Optionally, an embodiment of the present invention provides a decryption algorithm, which may include:

[0120] First define a function as Where x represents c p-1 modp 2 or g p-1 modp 2 .

[0121] Then, the ciphertext c of the data required for the privacy computing task can be decrypted according to the second private key sk(p,q):

[0122]

[0123] Here, m represents plain text.

[0124] To further illustrate privacy-preserving computing, the present invention provides examples that may include:

[0125] Assume that there are ciphertext m1 and ciphertext m2, then Enc(m1)Enc(m2)=g m1 h r modn*g m2 h r modn;g m1 h r modn*g m2 h r modn=g m1+m2 h r modn=Enc(m1+m2), where Enc represents the encryption algorithm.

[0126] Therefore, privacy computing can be performed using the above algorithm. During the privacy computing process, the key is transmitted in fragments. After fragmentation, the key is encrypted with the first public key. Even if an illegal person cracks a public key encryption, it is difficult to obtain other fragments. When the number of fragments is less than a certain number, it is also difficult to crack the data, thereby ensuring the privacy of the supply chain node. Since the supply chain node only holds one fragment, it is difficult to view the data. Privacy computing can be performed through another node, and the data can be decrypted through the first target supply chain node, thereby effectively ensuring the security of the data.

[0127] Those skilled in the art will readily appreciate other embodiments of the present invention after considering the specification and practicing the invention disclosed herein. The present invention is intended to cover any variations, uses, or adaptations of the present invention that follow the general principles of the present invention and include common knowledge or customary techniques in the art not disclosed herein. It should be understood that the present invention is not limited to the precise structure described above and shown in the accompanying drawings, and various modifications and variations can be made without departing from the scope thereof. The scope of the present invention is limited only by the appended claims.

Claims

1. A supply chain data management method based on privacy computing, characterized in that: include: Issuing a first key pair consisting of a first public key and a second private key to each supply chain node; Obtain a privacy-preserving computing task request transmitted by a first target supply chain node for data to be calculated, and, based on the privacy-preserving computing task request, use a privacy-preserving computing algorithm to generate a second key pair consisting of a second public key and a second private key for temporarily managing the data; Distributing the second public key in the second key pair to each supply chain node, and fragmenting the second private key in the second key pair to obtain a plurality of second private key fragments equal to the number of supply chain nodes; Encrypting the second private key fragments one-to-one using the first public key in the first key pair corresponding to the supply chain node, and distributing the encrypted second private key fragments to the corresponding supply chain node; Randomly select a supply chain node other than the first target supply chain node to obtain a second target supply chain node, and broadcast the second target supply chain node and the corresponding privacy computing task required data to all supply chain nodes, so that each supply chain node encrypts the data required for the privacy computing task using the second public key and transmits it to the second target supply chain node; After the second target supply chain node uses a privacy computing algorithm to perform privacy computing on the data required for the privacy computing task transmitted by all supply chain nodes, it obtains the privacy computing result, and transmits the privacy computing result back to the first target supply chain node; Randomly broadcasting the first target supply chain node and the first public key corresponding to the first target supply chain node to a preset number of supply chain nodes, so that the supply chain node encrypts its own second private key fragment using the first public key corresponding to the first target supply chain node and transmits it to the first target supply chain node; The received second private key fragments are recovered by the first target supply chain node to obtain the second private key, and the second private key is used to decrypt the privacy calculation result to obtain the calculation result corresponding to the privacy calculation task.

2. The supply chain data management method based on privacy computing according to claim 1 is characterized in that: The first key pair consisting of the first public key and the second private key is issued to each supply chain node, including: For any supply chain node, an asymmetric encryption algorithm is used to generate a first key pair consisting of a first public key and a second private key; Traverse all supply chain nodes to obtain a first key pair consisting of a first public key and a second private key issued by each supply chain node.

3. The supply chain data management method based on privacy computing according to claim 1 is characterized in that: A second key pair consisting of a second public key and a second private key for temporarily managing data is generated using a privacy computing algorithm, including: Based on a preset length l, a first prime number p and a second prime number q are randomly selected from numbers whose length is greater than the preset length l; Generate a first public key parameter n according to the first prime number p and the second prime number q, which is the first prime number p*the first prime number p*the second prime number q; From a finite field Randomly select a generator g from g so that g p =g p-1 mod p 2 The order is p, gcd(p,q-1)=1 and gcd(p-1,q)=1; where g p represents the intermediate parameter, mod represents the remainder function, and gcd represents the greatest common factor algorithm; According to the generator g and the first public key parameter n, the second public key parameter h is generated as g n mod n; Generate effective time parameter t; According to the first public key parameter n, the generator g and the second public key parameter h, a second public key pk for temporary management data is generated as: (n, g, h); According to the first prime number p and the second prime number q, a second private key sk for temporary management data is generated as: (p, q); A second key pair is obtained according to the valid time parameter t, the second public key pk and the second private key sk.

4. The supply chain data management method based on privacy computing according to claim 3 is characterized in that: Distributing the second public key in the second key pair to each supply chain node includes: broadcasting the second public key in the second key pair to all supply chain nodes in a broadcasting manner.

5. The supply chain data management method based on privacy computing according to claim 3 is characterized in that: The second private key in the second key pair is fragmented to obtain a plurality of second private key fragments equal to the number of supply chain nodes, including: Take out the second private key sk from the second key pair, and obtain the first prime number p and the second prime number q; Fragmenting the first prime number p to obtain a plurality of first target fragments; Fragmenting the second prime number q to obtain a plurality of second target fragments; wherein the number of the first target fragments is the same as the number of the second target fragments; Randomly matching the first target fragments with the second target fragments one by one to obtain mutually related first target fragments and second target fragments; According to the mutually associated first target fragment and second target fragment, the second private key fragment is obtained as (t, s1, s2); wherein s1 represents the first target fragment, and s2 represents the second target fragment.

6. The supply chain data management method based on privacy computing according to claim 5 is characterized in that: The fragmentation process of the first prime number p is the same as the fragmentation process of the second prime number q, and both include: Obtaining a fragmentation number M of the first target fragment or the second target fragment; For the key to be fragmented, a K-order polynomial is generated as follows: f(x)=a0+a1x 1 +a2x 2 +...+a K x K The key to be fragmented represents the first prime number p or the second prime number q, f(x) represents a K-order polynomial, a0 represents the key to be fragmented, a1, a2, ..., a K They represent the 1st, 2nd, …, Kth coefficients respectively, K is equal to M / 2, and x represents the independent variable; Let the independent variable x be a random value, and determine the corresponding dependent variable of the K-order polynomial f(x) to be y; According to the independent variable x and the dependent variable y, the target fragment is determined to be (t, x, y); wherein the target fragment is the first target fragment or the second target fragment; Repeatedly obtain K different target fragments to complete the fragmentation process.

7. The supply chain data management method based on privacy computing according to claim 6 is characterized in that: The data required for the privacy computing task is encrypted using the second public key: c=g m h r mod n Among them, m represents the plaintext of the data required for the privacy computing task, c represents the ciphertext of the data required for the privacy computing task, and r represents the finite field Random numbers in .

8. The supply chain data management method based on privacy computing according to claim 7 is characterized in that: After the second target supply chain node uses the privacy computing algorithm to perform privacy computing on the data required for the privacy computing task transmitted by all supply chain nodes, the privacy computing results are obtained, including: The data required for the privacy computing task transmitted by all supply chain nodes is summed up through the second target supply chain node, and no encryption or decryption is performed during the calculation process to obtain the privacy computing result.

9. The supply chain data management method based on privacy computing according to claim 8 is characterized in that: Randomly broadcasting a first target supply chain node and a first public key corresponding to the first target supply chain node to a preset number of supply chain nodes, so that the supply chain node encrypts its own second private key fragment using the first public key corresponding to the first target supply chain node and transmits the encrypted fragment to the first target supply chain node, including: Determine a preset number L that is greater than M / 2; Randomly broadcast the first target supply chain node and the first public key corresponding to the first target supply chain node to L supply chain nodes; The supply chain node determines whether the storage time of the valid time parameter t is greater than t. If so, it is determined that the second key pair has expired and the supply chain data management is terminated. Otherwise, the second private key fragment is encrypted with the first public key corresponding to the first target supply chain node and transmitted to the first target supply chain node.

10. The supply chain data management method based on privacy computing according to claim 9 is characterized in that: The first target supply chain node recovers the received second private key fragments to obtain the second private key, and uses the second private key to decrypt the privacy computing result to obtain the calculation result corresponding to the privacy computing task, including: Generate a K-order polynomial with a constant term, decrypt the K-order polynomial using the received second private key fragment through the first target supply chain node, and use the constant term in the decrypted K-order polynomial as the second private key; The second private key is used to decrypt the privacy computing result to obtain the calculation result corresponding to the privacy computing task.

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