A data sharing tracking method based on digital fingerprint and blockchain

Abstract

The application discloses a data sharing tracking method based on digital fingerprints and blockchains, which comprises a plurality of entities of data owners, data consumers, blockchains, third-party cloud service platforms and tracking agencies, and comprises the following steps: 1) an initialization stage; 2) a data processing stage; 3) a data publishing stage; 4) an access request and authorization stage; 5) a data acquisition and fingerprint reorganization stage; 6) a data decryption and synthesis stage; and 7) a data leakage tracking stage. The method supports data sharing among multiple parties, wherein the data owner only needs to generate a small amount of seed data to share data with a large number of data consumers, and the data owner can identify specific data leakers from a large number of data consumers once data leakage occurs.

Description

Technical Field

[0001] This invention relates to the fields of blockchain, digital fingerprint and other technologies, specifically a data sharing and tracking method based on digital fingerprint and blockchain. Background Technology

[0002] Multimedia data such as images, audio, and video are important components of IoT data, and sharing this data can improve the productivity and governance capabilities of human society. Cross-domain sharing of business data in smart manufacturing and smart transportation can help warehouses and logistics achieve intelligent management, while collecting and sharing various IoT data can accelerate the construction of smart cities. Currently, IoT data sharing models are mainly divided into two types: (i) data sharing models based on centralized architecture; and (ii) decentralized data sharing models based on blockchain. Centralized data sharing models rely on third parties, which poses the risk of malicious leakage and destruction of data by third parties; decentralized data sharing models use blockchain technology to solve the problem of excessive reliance on third parties in centralized data sharing and improve the scalability of IoT to a certain extent.

[0003] While blockchain-based IoT data sharing models address the issue of malicious third-party actions, several problems remain. For example, in current IoT data sharing models, data owners lose control over data access after sharing it with multiple data consumers. In the event of a data breach, it's difficult for the data owner to trace and identify the perpetrator from among the various consumers. Furthermore, in some scenarios, the data owner (sender) only permits data consumers (receivers) to use the data, prohibiting them from sharing it with others without permission.

[0004] Blockchain technology originated from Satoshi Nakamoto's Bitcoin and is a new application model integrating computer technologies such as distributed data storage, peer-to-peer transmission, consensus mechanisms, and encryption algorithms. Essentially, blockchain is a distributed ledger technology with characteristics such as decentralization, tamper-proofing, and traceability. Therefore, blockchain is an effective means to solve trust issues in resource sharing. Blockchain has enormous application value and potential in device authentication, data sharing, security, and privacy within the Internet of Things (IoT).

[0005] Digital fingerprinting is an important branch of information hiding technology, primarily used for digital rights management and data breach tracking. Digital fingerprints embed different, unique information (mainly corresponding to the data consumer's identity information) into the data. In the event of data piracy or leakage, the data owner can extract the identity information of the data breach perpetrator based on the leaked data. A DNA-inspired digital fingerprinting system (also known as a P2P fingerprint distribution system) is a fingerprinting system that combines the advantages of unicast and multicast. Its main feature is that data consumers obtain complete data by combining data blocks from different sources (entities that already possess the data). Data owners only need to generate a small number of data copies with different fingerprints to achieve traceable data sharing in multicast scenarios. The system segments fingerprints and data into equal numbers of fingerprint fragments and data blocks, then embeds the fingerprint fragments one by one into the data blocks. The DNA-inspired digital fingerprinting system uses a P2P system for data distribution; each distribution causes the data blocks with fingerprint fragments to be randomly recombined, thereby generating data copies with new fingerprints. The new fingerprint is unique and associated with the data consumer's identity. Summary of the Invention

[0006] The purpose of this invention is to address the lack of accountability and tracing mechanisms for data breaches in multi-party data sharing within the Internet of Things (IoT) and to provide a data sharing tracing method based on digital fingerprinting and blockchain. This method allows data owners to share data with a large number of data consumers by generating only a small amount of seed data in multi-party data sharing scenarios. In the event of a data breach, the data owner can identify the specific perpetrator from among the numerous data consumers.

[0007] The technical solution to achieve the objective of this invention is:

[0008] A data sharing and tracking method based on digital fingerprinting and blockchain includes multiple entities such as data owners, data consumers, blockchain, third-party cloud service platforms, and tracking agencies. The method includes the following steps:

[0009] 1) Initialization Phase: Assume there is a blockchain platform that provides data on-chain storage and immutability services for data owners, data consumers, and third-party cloud service platforms. Data owners, data consumers, and third-party cloud service platforms each generate key pairs (sk, pk) using asymmetric cryptography algorithms. The private key sk is secretly kept by the relevant entity, while the public key pk is publicly available. After obtaining the key pairs, data owners, data consumers, and third-party cloud service platforms register by submitting (ID, pk) to a tracking agency. The ID represents the identity information of the data owner, data consumer, and third-party cloud service platform. After verifying the relevant information of the corresponding entity, the tracking agency adds the public key pk to the public member list. All key pairs (sk, pk) are mainly used for two aspects: (i) blockchain transaction signing and signature verification; (ii) blockchain data encryption and decryption.

[0010] 2) Data Processing Stage: Before sharing data D with a large number of data consumers, the data owner performs orthogonal decomposition, encryption, and fingerprint embedding on the data: First, the data owner decomposes data D into two parts, D1 and D2, using orthogonal decomposition; second, the data owner encrypts data D1 using an encryption algorithm to obtain ciphertext D. 1e Secondly, the data owner selects N unrelated digital fingerprints f i (i = 1, ..., N), where N is an integer less than 10, and the fingerprint f i (i = 1, ..., N) and data D2 are each divided into M fingerprint fragments. and data blocks Where i = 1, ..., N, j = 1, ..., M; finally, the data owner will use the fingerprint fragments. The hash values ​​are embedded one by one into the data blocks. Obtain data blocks with fingerprint fragments D2 corresponding to different fingerprints, i.e. Where i = 1, ..., N;

[0011] 3) Data Release Phase: After the data processing phase is completed, the data owner will... The data is sent to N third-party cloud service platforms for storage, and a data release transaction is submitted to the blockchain. The transaction format is as follows: (ID) Tx ID D Sig DPT PK DO (,Type,DD,Other)

[0012] ID Tx It is a unique identifier for a transaction, generated by hashing the transaction content; ID D It is a unique identifier for data, Sig DPTIt's a transaction signature, PK. DO It is the public key of the transaction initiator, used to verify the transaction signature Sig. DPT DD is the data description, Type is the transaction type, and the current value is DPT, which means that this is a data publishing transaction. Other is other information about the transaction; other transactions will include a unique transaction identifier, transaction signature, transaction initiator's public key, and other transaction information. These contents play a similar role in each transaction, so they will not be repeated.

[0013] 4) Access Request and Authorization Phase: Assuming DC1 is the first data consumer wanting to obtain data D, it needs to submit an access request transaction on the blockchain network. The transaction format is as follows:

[0014] (ID Tx ID D Sig ART PK DC (Type, Other)

[0015] ID D It is the unique identifier that DC1 wants to access data D, and the ID in the DPT transaction. D To maintain consistency, the current value of Type is ART, which means that this is an access request transaction;

[0016] After a data access request transaction is recorded in the blockchain global ledger, the data owner retrieves the transaction by synchronizing the latest block of the blockchain. The data owner first checks the PK (Primary Key). DC Does it exist in the tracking organization's public member list? If so, use PK. DC Verify signature Sig ART The successful verification only proves the legitimacy of DC1's identity and that ART is a valid access request transaction. Assuming the data owner ultimately agrees to authorize DC1 to access data D, an authorization transaction is published in the blockchain network, with the following format:

[0017] (ID Tx ID Auth Sig AAT PK DO EK e (Type, Other)

[0018] ID Auth It is an authorized unique identifier, which is related to the ART ID. tx Maintain consistency, EK e It is K e The corresponding ciphertext, and K e It is the key corresponding to the encrypted data D, EK eIt uses the public key pk of data consumer DC1 to encrypt K. e As a result, only DC can decrypt the data using the private key sk. The current value of Type is AAT, which means that this is an access authorization transaction.

[0019] 5) Data Acquisition and Fingerprint Reconstruction Stage: After obtaining authorization, DC1 arbitrarily selects β (1 < β ≤ N) third-party cloud service platforms from N to form a data source set. Before distributing data to DC1, each third-party cloud service platform (i.e., the data source) needs to synchronize the latest blockchain block to verify whether the data consumer DC1 has been authorized. Only when the third-party cloud service platform (i.e., the data source) confirms that DC1 is the authorized entity of the data owner will the third-party cloud service platform (i.e., the data source) distribute the data to DC1. DC1 then acquires D from any of the data sources. 1e Then, data blocks that make up D2 are obtained from different data sources. The data sources use the public key of the tracking agency to encrypt the data distribution record and send it to the blockchain for secure storage. The data distribution record contains the public key of DC1, which can obtain the identity information ID of DC1 through the tracking agency.

[0020] Assuming β = 2, DC1 obtains a portion of the data blocks that make up D2 from the first third-party cloud service platform, i.e., the data source. All data blocks have fingerprints. Then, it obtains the remaining data blocks from the second third-party cloud service platform, i.e., the data source. Since these data blocks contain different fingerprint fragments, DC1 obtains D2 with a new fingerprint f' through random recombination, i.e., (D2). f′ Suppose that during the data processing stage, the data owner selects three unrelated fingerprints f1, f2, and f3, then divides the digital fingerprints f1, f2, and f3 and the data D2 into 128 fingerprint fragments and data blocks respectively, and then embeds each fingerprint fragment into a data block. Then, there are 3... 128 With a combination of fingerprints, in such a fingerprint space, DC1 can automatically generate a unique new fingerprint that corresponds to its own identity by randomly combining data blocks containing fingerprint fragments;

[0021] The process of data consumers acquiring data D after DC1 is similar to that of DC1. The difference is that in the selection of data source sets, data consumers are no longer limited to N third-party cloud service platforms, but can also choose data sources from data consumers that have already acquired data D.

[0022] 6) Data decryption and synthesis stage: Obtaining data D 1e and (D2) f′ Subsequently, the data consumer decrypts D using the key obtained during the access request and authorization phases. 1e We obtain D1, where the data consumer is no longer limited to the first data consumer. Then, the data consumer will combine D1 and (D2). f′Through orthogonal synthesis, data D with a new fingerprint is obtained, namely D f′ ;

[0023] 7) Data Breach Tracking Stage: Once the data owner discovers that data D has been leaked, they extract the relevant digital fingerprint from the leaked data. This fingerprint corresponds to the identity of the data breacher. Then, the data owner initiates a tracking application to a tracking agency. With the help of the tracking agency, they search the blockchain ledger records, which contain the data distribution records of the stored data, thereby tracking the identity information of the data breacher.

[0024] The data sharing method of this technical solution is as follows: First, the data owner processes the data locally; then, the data owner hands the data over to a third-party cloud service platform for storage; second, the first data consumer obtains data blocks from different third-party cloud service platforms to form a complete set of data; finally, subsequent data consumers obtain data blocks from different third-party cloud service platforms and consumers who have already obtained data to form a complete set of data.

[0025] The sharing method of this technical solution is divided into: the data publishing stage in step 3) and the data acquisition and fingerprint reconstructing stage in step 5). The access request and authorization stage in step 4) is actually the process of obtaining the data decryption key.

[0026] Compared with existing technologies, this technical solution has the following advantages:

[0027] 1. Compared with traditional data sharing and tracking technologies based on digital fingerprinting, this technical solution decouples data owners from data leakers in data breach tracking and accountability. That is, data owners do not need to know the number and identity information of data consumers in advance, and can still track and hold the data leaker accountable when a data breach occurs.

[0028] 2. Compared to other traceable data sharing technologies, the data owner in this technical solution only needs to generate a small amount of seed data to share the data with a large number of data consumers. Therefore, this technical solution has a significant low computational overhead characteristic for the data owner, and this characteristic becomes more pronounced as the number of data consumers increases.

[0029] 3. This technical solution integrates blockchain and digital fingerprint technology. By using blockchain, it ensures the immutability of data transaction records, supports the extraction of key information about the data leaker from the leaked data, and realizes a secure and reliable data leak tracking and accountability mechanism.

[0030] This method enables data owners to share data with a large number of data consumers by generating only a small amount of seed data in multi-party data sharing scenarios. In the event of a data breach, the data owner can identify the specific data breach perpetrator from among the large number of data consumers. Attached Figure Description

[0031] Figure 1 This is a schematic diagram of an embodiment;

[0032] Figure 2 This is a schematic diagram of a supply chain data sharing method as an example. Detailed Implementation

[0033] The present invention will be further described below with reference to embodiments, but these are not intended to limit the scope of the invention. Embodiments:

[0034] In a supply chain, core enterprise A needs to share data D with upstream and downstream enterprises (assuming there are 20 such enterprises) to achieve precise logistics management. However, because data D involves sensitive information, it can only be used within the supply chain and cannot be disclosed to individuals or organizations outside the supply chain. Disclosing data D to individuals or organizations outside the supply chain could threaten the security of the entire supply chain. However, due to the large number of upstream and downstream enterprises (assuming 20), if data D is leaked, core enterprise A will find it difficult to trace and hold specific individuals or organizations accountable for the leak. To address these problems and challenges, core enterprise A can use this method for data sharing.

[0035] Reference Figure 1 A data sharing and tracking method based on digital fingerprinting and blockchain includes multiple entities such as a core enterprise A (data owner), upstream and downstream enterprises (data consumers), blockchain, third-party cloud service platforms (three different cloud service platforms in this example), and tracking agencies. The method includes the following steps:

[0036] 1) Initialization Phase: Assume there is a blockchain platform that provides data on-chain notarization and tamper-proof storage services for core enterprise A, upstream and downstream enterprises (20 in total), and a third-party cloud service platform. Core enterprise A, upstream and downstream enterprises, and the third-party cloud service platform each generate key pairs (sk, pk) using asymmetric cryptography algorithms. The private key sk is kept secret by each entity, while the public key pk is made public. After obtaining the key pairs, core enterprise A, upstream and downstream enterprises, and the third-party cloud service platform register by submitting (ID, pk) to a tracking agency. Here, ID is the identity information of the corresponding core enterprise A, upstream and downstream enterprises, and third-party cloud service platform. After verifying the relevant information of the corresponding entity, the tracking agency adds the public key pk to the member public list. All key pairs (sk, pk) are mainly used for two aspects: (i) blockchain transaction signing and signature verification; (ii) blockchain data encryption and decryption.

[0037] 2) Data Processing Stage: Before sharing data D with upstream and downstream enterprises, core enterprise A first performs orthogonal decomposition, encryption, and fingerprint embedding on data D: First, core enterprise A decomposes data D into two disjoint subsets, D1 and D2, using orthogonal decomposition; second, core enterprise A uses an encryption algorithm (which can be a symmetric or asymmetric encryption algorithm) to encrypt data D1, obtaining ciphertext D. 1e Secondly, core enterprise A selects three unrelated digital fingerprints. i (i = 1, ..., 3), and the fingerprint f i (i = 1, ..., 3) and data D2 are each divided into 128 fingerprint fragments. and data blocks Where i = 1,...,3,j = 1,...128; finally, core enterprise A will provide the fingerprint fragments. The hash values ​​are embedded one by one into the data blocks. Obtain data blocks with fingerprint fragments D2 corresponding to different fingerprints, i.e. Where i = 1, ..., 3;

[0038] like Figure 2 As shown, 3) Data release phase: After completing the data processing phase, core enterprise A will... The data is sent to three third-party cloud service platforms for storage, and a data release transaction is submitted to the blockchain network. The transaction format is as follows:

[0039] (ID Tx ID D Sig DPT PK DO (,Type,DD,Other)

[0040] ID Tx It is a unique identifier for the transaction (generated by hashing the transaction content), ID D It is a unique identifier for data, Sig DPT It's a transaction signature, PK. DO It is the public key of the transaction initiator (core enterprise A), used to verify the transaction signature Sig. DPT DD is the data description, Type is the transaction type (currently valued as DPT, meaning this is a data publishing transaction), and Other is other information about the transaction. Other transactions will include a unique transaction identifier, transaction signature, transaction initiator's public key, and other transaction information. These contents play a similar role in each transaction, so they will not be repeated here.

[0041] 4) Access Request and Authorization Phase: Assuming DC1 is the first upstream and downstream enterprise to want to obtain data D, it needs to submit an access request transaction on the blockchain network. The transaction format is as follows:

[0042] (ID Tx ID D Sig ART PK DC (Type, Other)

[0043] ID D It is the unique identifier that DC1 wants to access data D, and the ID in the DPT transaction. D To maintain consistency, the current value of Type is ART, which means that this is an access request transaction;

[0044] After the data access request transaction is recorded in the blockchain global ledger, core enterprise A obtains the transaction by synchronizing the latest blockchain block. Core enterprise A first checks the PK. DC Does it exist in the tracking organization's public member list? If so, use PK. DC Verify signature Sig ART The successful verification only proves that DC1's identity is legitimate and that ART is a valid access request transaction. Assuming that core enterprise A ultimately agrees to authorize DC1 to access data D, an authorization transaction is published in the blockchain network, with the following format:

[0045] (ID Tx ID Auth Sig AAT PK DO EK e (Type, Other)

[0046] ID Aut It is an authorized unique identifier, which is related to the ART ID. tx Maintain consistency, EK e It is K e The corresponding ciphertext, and K e It is the key corresponding to the encrypted data D, EK e It uses the public key pk of the upstream and downstream enterprise DC1 to encrypt K. e As a result, only DC1 can decrypt the data using the private key sk. The current value of Type is AAT, which means that this is an access authorization transaction.

[0047] 5) Data Acquisition and Fingerprint Reconstruction Stage: After obtaining authorization, upstream and downstream enterprise DC1 randomly selects two third-party cloud service platforms from the three to form a data source set. Before distributing data to upstream and downstream enterprise DC1, the third-party cloud service platform (data source) needs to synchronize the latest blockchain block to verify whether upstream and downstream enterprise DC1 has been authorized. Only when the third-party cloud service platform (data source) confirms that upstream and downstream enterprise DC1 is the entity authorized by core enterprise A will the third-party cloud service platform (data source) distribute the data to upstream and downstream enterprise DC1. The data source uses the public key of the tracking agency to encrypt the data distribution record (containing DC1's public key, which can be obtained through the tracking agency's identity information ID) and sends it to the blockchain for secure storage.

[0048] Suppose DC1 obtains a portion of the data blocks that make up D2 from the first third-party cloud service platform (data source) (all data blocks have fingerprints), and then obtains the remaining data blocks from the second third-party cloud service platform (data source). Since these data blocks contain different fingerprint fragments, through the above random recombination method, DC1 obtains D2 with a new fingerprint f′, i.e., (D2). f′ During the data processing phase, core enterprise A selected three unrelated fingerprints, f1, f2, and f3. Then, it divided the digital fingerprints f1, f2, and f3, along with data D2, into 128 fingerprint fragments and data blocks, respectively. Finally, it embedded each fingerprint fragment into a data block. This results in 3... 128 With a combination of fingerprints, in such a fingerprint space, DC1 can automatically generate a unique new fingerprint that corresponds to its own identity by randomly combining data blocks containing fingerprint fragments;

[0049] The process of upstream and downstream enterprises acquiring data D after DC1 is basically similar to that of DC1. The difference is that the choice of data source set is no longer limited to 3 third-party cloud service platforms. Data sources can also be selected from upstream and downstream enterprises that have already acquired data D.

[0050] 6) Data decryption and synthesis stage: Obtaining data D 1e and (D2) f′ Subsequently, upstream and downstream enterprises (no longer limited to the first upstream or downstream enterprise) can decrypt D using the key obtained during the access request and authorization phases. 1e This yields D1, and then upstream and downstream companies synthesize D1 and (D2) through orthogonal synthesis. f′ Perform synthesis to obtain data D with the new fingerprint, i.e., D f′ ;

[0051] 7) Data Breach Tracking Stage: Once core enterprise A discovers that data D has been leaked, it can extract relevant digital fingerprints from the leaked data (these fingerprints correspond to the identities of upstream and downstream enterprises). Then, core enterprise A can initiate a tracking application to the tracking agency. With the help of the tracking agency, it can search the blockchain ledger records (including data source distribution records) to track the identity information of upstream and downstream enterprise A.

Claims

1. A data sharing and tracking method based on digital fingerprints and blockchain, characterized in that, The method, which includes multiple entities such as data owners, data consumers, blockchain, third-party cloud service platforms, and tracking agencies, comprises the following steps: 1) Initialization Phase: Assume there is a blockchain platform that provides data on-chain storage and immutability services for data owners, data consumers, and third-party cloud service platforms. Data owners, data consumers, and third-party cloud service platforms each generate key pairs (sk, pk) using asymmetric cryptography algorithms. The private key sk is secretly kept by the relevant entity, while the public key pk is publicly available. After obtaining the key pairs, data owners, data consumers, and third-party cloud service platforms register by submitting (ID, pk) to a tracking agency. The ID represents the identity information of the data owner, data consumer, and third-party cloud service platform. After verifying the relevant information of the corresponding entity, the tracking agency adds the public key pk to the public member list. All key pairs (sk, pk) are used for two purposes: (i) blockchain transaction signing and signature verification; (ii) blockchain data encryption and decryption. 2) Data Processing Stage: Before sharing data D with a large number of data consumers, the data owner performs orthogonal decomposition, encryption, and fingerprint embedding on the data: First, the data owner decomposes data D into two parts, D1 and D2, using orthogonal decomposition; second, the data owner encrypts data D1 using an encryption algorithm to obtain ciphertext D. 1e Secondly, the data owner selects N unrelated digital fingerprints f i (i = 1, ..., N), where N is an integer not exceeding 10, and the fingerprint f i (i = 1, ..., N) and data D2 are each divided into M fingerprint fragments. and data blocks Where i = 1, ..., N, j = 1, ..., M; finally, the data owner will use the fingerprint fragments. The hash values ​​are embedded one by one into the data blocks. Obtain data blocks with fingerprint fragments D2 corresponding to different fingerprints, i.e. Where i = 1, ..., N; 3) Data Release Phase: After the data processing phase is completed, the data owner will... The data is sent to N third-party cloud service platforms for storage, and a data release transaction is submitted to the blockchain. The transaction format is as follows: (ID) Tx ID D Sig DPT PK DO (,Type,DD,Other) ID Tx It is a unique identifier for a transaction, generated by hashing the transaction content; ID D It is a unique identifier for data, Sig DPT It's a transaction signature, PK. DO It is the public key of the transaction initiator, used to verify the transaction signature Sig. DPT DD is the data description, Type is the transaction type, and the current value is DPT, which means that this is a data publishing transaction. Other is other information about the transaction; other transactions will include a unique transaction identifier, transaction signature, transaction initiator's public key, and other transaction information. These contents play a similar role in each transaction. 4) Access Request and Authorization Phase: Assuming DC1 is the first data consumer wanting to obtain data D, it needs to submit an access request transaction in the blockchain network. The transaction format is as follows: (ID Tx ,ID D ,Sig ART ,PK DC ,Type,Other), ID D It is the unique identifier that DC1 wants to access data D, and the ID in the DPT transaction. D To maintain consistency, the current value of Type is ART, which means that this is an access request transaction; After a data access request transaction is recorded in the blockchain global ledger, the data owner retrieves the transaction by synchronizing the latest block of the blockchain. The data owner first checks the PK (Primary Key). DC Does it exist in the tracking organization's public member list? If so, use PK. DC Verify signature Sig ART The successful verification only proves the legitimacy of DC1's identity and that ART is a valid access request transaction. Assuming the data owner ultimately agrees to authorize DC1 to access data D, an authorization transaction is published in the blockchain network, with the following format: (ID Tx ,ID Auth ,Sig AAT ,PK DO ,EK e ,Type,Other), ID Auth It is an authorized unique identifier, which is related to the ART ID. tx Maintain consistency, EK e It is K e The corresponding ciphertext, and K e It is the key corresponding to the encrypted data D, EK e It uses the public key pk of data consumer DC1 to encrypt K. e As a result, only DC can decrypt the data using the private key sk. The current value of Type is AAT, which means that this is an access authorization transaction. 5) Data Acquisition and Fingerprint Reconstruction Stage: After obtaining authorization, DC1 arbitrarily selects β third-party cloud service platforms from N third-party cloud service platforms to form a data source set, where 1 < β ≤ N. Before distributing data to DC1, each third-party cloud service platform (i.e., the data source) needs to synchronize the latest blockchain block to verify whether the data consumer DC1 has been authorized. Only when the third-party cloud service platform (i.e., the data source) confirms that DC1 is the authorized entity of the data owner will it distribute the data to DC1. DC1 then acquires D from any of the data sources. 1e Then, data blocks that make up D2 are obtained from different data sources. The data sources use the public key of the tracking agency to encrypt the data distribution record and send it to the blockchain for secure storage. The data distribution record contains the public key of DC1, which can obtain the identity information ID of DC1 through the tracking agency. Assuming β = 2, DC1 obtains a portion of the data blocks that make up D2 from the first third-party cloud service platform, i.e., the data source. All data blocks have fingerprints. Then, it obtains the remaining data blocks from the second third-party cloud service platform, i.e., the data source. Since these data blocks contain different fingerprint fragments, DC1 obtains D2 with a new fingerprint f' through random recombination, i.e., (D2). f′ Suppose that during the data processing stage, the data owner selects three unrelated fingerprints f1, f2, and f3, then divides the digital fingerprints f1, f2, and f3 and the data D2 into 128 fingerprint fragments and data blocks respectively, and then embeds each fingerprint fragment into a data block. Then, there are 3... 128 With a combination of fingerprints, in such a fingerprint space, DC1 can automatically generate a unique new fingerprint that corresponds to its own identity by randomly combining data blocks containing fingerprint fragments; The process of data consumers acquiring data D after DC1 is similar to that of DC1. The difference is that the selection of data consumers in the data source set is no longer limited to N third-party cloud service platforms, but can also select data sources from data consumers that have already acquired data D. 6) Data decryption and synthesis stage: Obtaining data D 1e and (D2) f′ Subsequently, the data consumer decrypts D using the key obtained during the access request and authorization phases. 1e We obtain D1, where the data consumer is no longer limited to the first data consumer. Then, the data consumer will combine D1 and (D2). f′ Through orthogonal synthesis, data D with a new fingerprint is obtained, namely Di. f′ ; 7) Data Breach Tracking Phase: Once the data owner discovers that data D has been leaked, they extract a digital fingerprint from the leaked data. This fingerprint corresponds to the identity of the data breach perpetrator. The data owner then initiates a tracking application with a tracking agency. With the help of the tracking agency, they search the blockchain ledger records, which contain data distribution records of the data storage, thereby tracking the identity information of the data breach perpetrator.

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