Block chain privacy data query method and system

Abstract

The invention discloses a block chain privacy data query method and system, and relates to the technical field of data query. Collected financial transaction data is processed, and then extraction and analysis are performed according to query requirements. According to the block chain privacy data query method and system, the collected data is classified and then subjected to multi-stage encryption operation, the query request is initiated according to a querier, the extraction operation of the required query data is realized by using an identifier matching algorithm, and the decryption verification operation is performed after the identifier data is confirmed; and after the decryption requirement is met, the encrypted data is transmitted to a querier, so that multi-level encryption is realized according to the importance of the privacy data, verification operation is gradually performed through data matching in the decryption process, the security in the data query process is ensured, the generation of an abnormal request is avoided, and the user experience is improved. And meanwhile, the required data can be extracted and queried more quickly, and the step-by-step browsing operation of a querier is reduced.

Description

Technical Field

[0001] The present invention relates to the field of data query technology, and in particular to a method and system for querying blockchain privacy data. Background Art

[0002] In recent years, blockchain technology has been widely used in many fields such as finance, medical care, and supply chain due to its decentralization, immutability, and distributed ledger characteristics. However, with the deepening of application, the protection and query of privacy data have become increasingly prominent.

[0003] The reference patent name is: A privacy data sharing query method and system based on blockchain (patent publication number: CN118245545A, patent publication date: 2024-06-25). First, a Starlink blockchain structure is constructed, and then the newly added organization is used as a child node to establish a communication connection with the main node. The user privacy data of the child node is encrypted and stored in the blockchain, and the data ciphertext stored in the blockchain is synchronized to each node on the blockchain structure for ledger data synchronization; the data query request of the child node is received, and the data ciphertext collision detection is performed according to the data query request of the child node to obtain the data query result of the child node, which solves the problem that in the big data era, sensitive information, such as identity and other privacy information, once leaked during data sharing and query, poses a threat to personal privacy and information security.

[0004] Based on the description in the above document, the existing method simply encrypts private data and directly stores the encrypted data on the blockchain, which is not convenient for query. When querying, it may be necessary to traverse and search the entire blockchain, which is inefficient and fails to quickly locate relevant private data based on the characteristics of the data. It is not accurate enough. At the same time, the decryption operation is prone to verification bias problems. Therefore, the present invention provides a method and system for querying blockchain private data. Summary of the invention

[0005] In view of the deficiencies in the prior art, the present invention provides a method and system for querying blockchain privacy data, which solves the problem that the prior art simply encrypts privacy data and directly stores the encrypted data on the blockchain, which is inconvenient to query. When querying, it may be necessary to traverse and search the entire blockchain, which is inefficient. It also fails to quickly locate relevant privacy data based on the characteristics of the data, is not accurate enough, and the decryption operation is prone to verification bias.

[0006] To achieve the above objectives, the present invention is implemented through the following technical solutions: a method for querying blockchain privacy data, specifically comprising the following steps: A1. Collect financial transaction data of individuals and store the collected data in a database using wireless communication transmission technology; A2. Process the collected data and then extract and analyze it according to the query requirements. The specific operations are as follows: a21. After the collected data is classified, multi-level encryption operations are implemented on the data to enable decryption and verification operations to be performed during subsequent inquiries; a22. Based on the query request initiated by the inquirer, the identification matching algorithm is used to extract the required query data, and after confirming the identification data, the decryption verification operation is performed, and after the decryption requirements are met, the encrypted data is transmitted to the inquirer; A3. According to the matching data results, the decrypted query data is transmitted to the display terminal of the inquirer for display.

[0007] Preferably, the multi-level encryption operation on data in a21 is: B1. Set a classification template, match the collected data with the category content in the classification template, and implement data classification. At this time, the unmatched data does not need to be encrypted; B2. Divide the data according to the classified content, determine the encryption level of the data according to the importance of the data, and implement multi-level encryption operations on the data based on the encryption level to form encrypted data with identification; B3. Store the encrypted data in different storage locations of the blockchain according to the level to facilitate traceability operations.

[0008] Preferably, the operation of matching the collected data in B1 with the category content in the classification template is: b11. The categories in the classification template specifically include personal identity information categories, transaction content information categories and amount content information categories corresponding to financial data; b12. Match the category content corresponding to the collected data with the category content in the classification template, and store the data with the same category content in the corresponding category of the classification template; b13. Unmatched data will be removed without encryption, otherwise the retained data will need to be encrypted.

[0009] Preferably, the multi-level encryption operation in B2 is: b21. Classify the data according to its importance, and form a three-level encryption method to encrypt the three types of data after the data is divided; b22, and the three-level encryption method is specifically: Level 1 encryption method: used for SMS verification of the inquirer; Secondary encryption method: used to identify and verify the face of the inquirer; Level 3 encryption method: used to identify and verify the signature of the inquirer; b23. The encryption applied to the three types of data is encrypted in a combined manner. For example, the important type of data is encrypted in sequence through the first, second and third level encryption methods, and the decryption also needs to be processed from the first to the third level. The less important type of data is encrypted in sequence through the first and second level encryption methods, and the last type of data is encrypted through the first level encryption method; b24. The encrypted data is identified by data category, data source and data generation time.

[0010] Preferably, the specific operation of the identification matching algorithm in a22 is: C1. Establish a protocol between the queryer and the stored data and implement the entry and confirmation of the queryer's information. After it is correct, enter the query content of the queryer based on the search bar, and classify the encrypted data identifiers to form an identification data set marked as P; C2. Segment the query content, perform search operations in the identified data set P based on the segmented query content, and then increase the query requirements based on the searched and displayed content to determine the final required data content; C3. Decrypt the final required data content.

[0011] Preferably, the operation of segmenting the query requirement content in C2 is: c21. Set the window function to extract content based on the query requirement content and match it with the content in the identification data set P; c22. If there is the same required data content, there is no need to split it. Otherwise, the extraction length of the window function is shortened, and it is gradually reduced from the end of the query required content until the extracted content matches the content in the identification data set P. c23. Then, a new round of window function extraction operation starts after the content extracted from the query requirement content, until all the query requirement content is traversed, and then sorted by the number of occurrences of the searched identification data for personnel confirmation.

[0012] Preferably, the operation of performing decryption verification after confirming the identification data in a22 is: D1. Click to confirm according to the finalized identification data, check the importance level of the identification data, and determine the encryption method level according to the importance level to perform corresponding step-by-step decryption operations; D2. The specific decryption operation results are: Result 1: If the data is the last category identifier, the inquirer enters his / her own number and requests the terminal to send a PIN code to achieve input matching. After the match is achieved, the decryption operation is verified; Result 2: It is the identification data of the less important category. After completing the verification operation of result 1, the terminal realizes the recognition operation of the inquirer's face and matches it with the input information when the protocol is initially established. After the match is achieved, the decryption operation is verified; Result 3 is important category identification data. After completing the verification operation of result 2, the inquirer implements the signature verification operation at the terminal and matches it with the input information when the agreement was initially established. After the match is achieved, the decryption operation is verified; D3. After the decryption verification operation is completed, the queried data is displayed through the terminal, and the request that has not completed the decryption operation is intercepted and marked.

[0013] Preferably, in the second result, the terminal implements the following operations to recognize the face of the inquirer: d201. Using the terminal to realize three-dimensional scanning of the inquirer's face, and realizing video data obtained by detecting the inquirer's movements according to the instruction requirements, and the video data is scaled in proportion to the actual face size; d202, dividing the video data into image data according to the set number of frames, and then extracting the image data entered when the protocol is established, by converting the collected image data and the extracted image data into images with the same pixels, and performing coverage comparison according to the image corner point position alignment based on the image data at the corresponding position; d203, setting a plurality of comparison points based on the centers of the characteristic parts of the two image data, and visualizing the upper image data, and observing whether the spacing of the same comparison points of the corresponding characteristic parts on the plane is within the deviation threshold; By obtaining the same comparison point spacing of the corresponding feature part as L 1 , and the deviation threshold is set to L 2 , and the number of comparison points on a single image data is M, the judgment formula for whether facial recognition is passed is obtained: F = (m / M) ≥ f; m is the number of comparison points that meet the requirements after the same comparison point spacing is compared with the set deviation threshold, that is, L 1 ≤L 2 , m / M represents the ratio of the number of comparison points that meet the requirements to the total number of comparison points, and f is the set minimum threshold for passing facial recognition, that is, if the judgment formula is met, the facial recognition verification passes, otherwise it fails and the query request needs to be intercepted.

[0014] Preferably, in the third result, the operation of the inquirer at the terminal to implement the signature verification is: d211. Use the terminal to provide a signature interface and facilitate the inquirer to perform the signature operation. After confirmation, collect the signature data, extract the various signature data entered when the agreement was established, and match the collected signature data with the extracted signature data; d212. Analyze and operate the input signature data to extract the common outline features and connected stroke features in the process of multiple signatures, intercept and mark the partial image, and then extract the corresponding partial position image of the collected signature data and compare it with the intercepted partial image; d213. If the corresponding local position image of the collected signature data is consistent with the intercepted local image, the signature verification operation passes; otherwise, it fails and the query request needs to be intercepted.

[0015] The present invention also discloses a blockchain privacy data query system, including: The data processing module is used to collect personal financial transaction data, classify it, and perform multi-level encryption operations on private data; The index query module establishes a connection protocol between the queryer and the data. By inputting the queryer's exploration requirements, the verification and decryption operations are performed based on the queryer's information. After the verification and decryption are completed, the verified data is transmitted to the queryer. The display terminal is convenient for the inquirer to operate and collect the verification data of the inquirer, and is also convenient for reference.

[0016] The present invention provides a method and system for querying blockchain privacy data. Compared with the prior art, it has the following beneficial effects: 1. The method and system for querying privacy data on the blockchain classifies the collected data and performs multi-level encryption operations. Based on the query request initiated by the inquirer, the identification matching algorithm is used to extract the required query data, and the decryption verification operation is performed after the identification data is confirmed. After the decryption requirements are met, the encrypted data is transmitted to the inquirer, thereby realizing multi-level encryption according to the importance of the privacy data, and the verification operation is gradually performed through data matching during the decryption process to ensure the security of the data query process and avoid the generation of abnormal requests. At the same time, the required data can be extracted and queried more quickly, reducing the inquirer's step-by-step browsing operation.

[0017] 2. The query method and system for blockchain privacy data extracts content based on the query requirement content by setting a window function and matches it with the content in the identification data set. If there is the same and required data content, there is no need to split it. Otherwise, the extraction length of the window function is shortened, and it is reduced one by one from the tail of the query requirement content until the extracted content matches the content in the identification data set P. Then, a new round of window function extraction operation is started after the content extracted from the query requirement content until all the query requirement content is traversed, so as to determine the required data content according to the index content, and sort the data content according to the number of times it appears after the content is split, which can facilitate the inquirer to find the privacy data identification required to view more quickly.

[0018] 3. The query method and system for blockchain privacy data realizes input matching by the inquirer requesting the terminal to send a PIN code by inputting his / her own number, realizing the recognition operation of the inquirer's face, and the signature verification operation of the inquirer at the terminal, and performing different analysis, matching and verification operations on the collected data and the entered data, and realizing the data viewing operation after meeting the requirements. It can effectively solve the problems of low efficiency of privacy data query, imperfect privacy protection and inaccurate data level management in the blockchain environment, and realize efficient, safe and accurate privacy data query. BRIEF DESCRIPTION OF THE DRAWINGS

[0019] Figure 1 This is an operation flow chart of the privacy data query method of the present invention; Figure 2 It is a multi-level encryption operation flow chart of the present invention; Figure 3 This is a principle block diagram of the privacy data query system of the present invention. DETAILED DESCRIPTION

[0020] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0021] See also Figure 1-Figure 3 , the present invention provides three technical solutions: Embodiment 1: A method for querying blockchain privacy data, specifically comprising the following steps: A1. Collect financial transaction data of individuals and store the collected data in a database using wireless communication transmission technology; A2. Process the collected data and then extract and analyze it according to the query requirements. The specific operations are as follows: a21. After the collected data is classified, multi-level encryption operations are implemented on the data to enable decryption and verification operations to be performed during subsequent inquiries; a22. Based on the query request initiated by the inquirer, the identification matching algorithm is used to extract the required query data, and after confirming the identification data, the decryption verification operation is performed, and after the decryption requirements are met, the encrypted data is transmitted to the inquirer; A3. According to the matching data results, the decrypted query data is transmitted to the display terminal of the inquirer for display.

[0022] By classifying the collected data and performing multi-level encryption operations, the query request is initiated by the inquirer, and the required query data is extracted using the identification matching algorithm. After confirming the identification data, decryption verification operations are performed, and the encrypted data is transmitted to the inquirer after the decryption requirements are met. In this way, multi-level encryption is achieved based on the importance of privacy data, and verification operations are gradually performed through data matching during the decryption process to ensure the security of the data query process and avoid the generation of abnormal requests. At the same time, the required data can be extracted and queried more quickly, reducing the inquirer's step-by-step browsing operations.

[0023] In the embodiment of the present invention, the multi-level encryption operation on data in a21 is: B1. Set a classification template, match the collected data with the category content in the classification template, and implement data classification. At this time, the unmatched data does not need to be encrypted; B2. Divide the data according to the classified content, determine the encryption level of the data according to the importance of the data, and implement multi-level encryption operations on the data based on the encryption level to form encrypted data with identification; B3. Store the encrypted data in different storage locations of the blockchain according to the level to facilitate traceability operations.

[0024] In the embodiment of the present invention, the operation of matching the collected data in B1 with the category content in the classification template is: b11. The categories in the classification template specifically include personal identity information categories, transaction content information categories and amount content information categories corresponding to financial data; b12. Match the category content corresponding to the collected data with the category content in the classification template, and store the data with the same category content in the corresponding category of the classification template; b13. Unmatched data will be removed without encryption, otherwise the retained data will need to be encrypted.

[0025] In the embodiment of the present invention, the multi-level encryption operation in B2 is: b21. Classify the data according to its importance, and form a three-level encryption method to encrypt the three types of data after the data is divided; b22, and the three-level encryption method is specifically: Level 1 encryption method: used for SMS verification of the inquirer; Secondary encryption method: used to identify and verify the face of the inquirer; Level 3 encryption method: used to identify and verify the signature of the inquirer; b23. The encryption applied to the three types of data is encrypted in a combined manner. For example, the important type of data is encrypted in sequence through the first, second and third level encryption methods, and the decryption also needs to be processed from the first to the third level. The less important type of data is encrypted in sequence through the first and second level encryption methods, and the last type of data is encrypted through the first level encryption method; b24. The encrypted data is identified by data category, data source and data generation time.

[0026] In the embodiment of the present invention, the specific operation of the identification matching algorithm in a22 is: C1. Establish a protocol between the queryer and the stored data and implement the entry and confirmation of the queryer's information. After it is correct, enter the query content of the queryer based on the search bar, and classify the encrypted data identifiers to form an identification data set marked as P; C2. Segment the query content, perform search operations in the identified data set P based on the segmented query content, and then increase the query requirements based on the searched and displayed content to determine the final required data content; C3. Decrypt the final required data content.

[0027] In the embodiment of the present invention, the operation of segmenting the query requirement content in C2 is: c21. Set the window function to extract content based on the query requirement content and match it with the content in the identification data set P; c22. If there is the same required data content, there is no need to split it. Otherwise, the extraction length of the window function is shortened, and it is gradually reduced from the end of the query required content until the extracted content matches the content in the identification data set P. c23. Then, a new round of window function extraction operation starts after the content extracted from the query requirement content, until all the query requirement content is traversed, and then sorted by the number of occurrences of the searched identification data for personnel confirmation.

[0028] For example, the inquirer inputs the query requirement content as "this month's food bill". At this time, the required data cannot be directly obtained by relying solely on "this month's food bill". Instead, the word "this month" is analyzed by gradually reducing the vocabulary, and the current day is determined as the deadline, and the starting time is the 1st of the month. Then all transaction identification data about this month are screened out, and a new round of matching operations is started from "food bill". If the content exists in the identification data, the data is sorted according to the number of occurrences, and the data with the same number of occurrences is randomly sorted. Then the inquirer can further match by adding query content, such as adding "amount exceeds five hundred". After the above-mentioned addition conditions are met, the data will be re-sorted until the required content is found and click to confirm.

[0029] By setting the window function to extract content based on the query requirement content and match it with the content in the identification data set, if there is identical and required data content, there is no need to split it. Otherwise, the extraction length of the window function is shortened, and it is reduced one by one from the tail of the query requirement content until the extracted content matches the content in the identification data set P. Then, a new round of window function extraction operation is started after the content extracted from the query requirement content until all query requirement content is traversed, so as to determine the required data content according to the index content, and sort the data content according to the number of times it appears after the content is split, which can facilitate the inquirer to find the privacy data identification required to view more quickly.

[0030] In the embodiment of the present invention, the operation of decryption verification after confirming the identification data in a22 is: D1. Click to confirm according to the finalized identification data, check the importance level of the identification data, and determine the encryption method level according to the importance level to perform corresponding step-by-step decryption operations; D2. The specific decryption operation results are: Result 1: If the data is the last category identifier, the inquirer enters his / her own number and requests the terminal to send a PIN code to achieve input matching. After the match is achieved, the decryption operation is verified; Result 2: It is the identification data of the less important category. After completing the verification operation of result 1, the terminal realizes the recognition operation of the inquirer's face and matches it with the input information when the protocol is initially established. After the match is achieved, the decryption operation is verified; Result 3 is important category identification data. After completing the verification operation of result 2, the inquirer implements the signature verification operation at the terminal and matches it with the input information when the agreement was initially established. After the match is achieved, the decryption operation is verified; D3. After the decryption verification operation is completed, the queried data is displayed through the terminal, and the request that has not completed the decryption operation is intercepted and marked.

[0031] In the embodiment of the present invention, the terminal implements the face recognition operation of the queryer in the second result as follows: d201. Using the terminal to realize three-dimensional scanning of the inquirer's face, and realizing video data obtained by detecting the inquirer's movements according to the instruction requirements, and the video data is scaled in proportion to the actual face size; d202, dividing the video data into image data according to the set number of frames, and then extracting the image data entered when the protocol is established, by converting the collected image data and the extracted image data into images with the same pixels, and performing coverage comparison according to the image corner point position alignment based on the image data at the corresponding position; d203, setting a plurality of comparison points based on the centers of the characteristic parts of the two image data, and visualizing the upper image data, and observing whether the spacing of the same comparison points of the corresponding characteristic parts on the plane is within the deviation threshold; By obtaining the same comparison point spacing of the corresponding feature part as L 1 , and the deviation threshold is set to L 2 , and the number of comparison points on a single image data is M, the judgment formula for whether facial recognition is passed is obtained: F = (m / M) ≥ f; m is the number of comparison points that meet the requirements after the same comparison point spacing is compared with the set deviation threshold, that is, L 1 ≤L 2 , m / M represents the ratio of the number of comparison points that meet the requirements to the total number of comparison points, and f is the set minimum threshold for passing facial recognition, that is, if the judgment formula is met, the facial recognition verification passes, otherwise it fails and the query request needs to be intercepted.

[0032] In the embodiment of the present invention, in result 3, the operation of the queryer at the terminal to implement signature verification is: d211. Use the terminal to provide a signature interface and facilitate the inquirer to perform the signature operation. After confirmation, collect the signature data, extract the various signature data entered when the agreement was established, and match the collected signature data with the extracted signature data; d212. Analyze and operate the input signature data to extract the common outline features and connected stroke features in the process of multiple signatures, intercept and mark the partial image, and then extract the corresponding partial position image of the collected signature data and compare it with the intercepted partial image; d213. If the corresponding local position image of the collected signature data is consistent with the intercepted local image, the signature verification operation passes; otherwise, it fails and the query request needs to be intercepted.

[0033] The inquirer enters his or her own number and requests the terminal to send a PIN code to achieve input matching, realize the recognition operation of the inquirer's face, and the inquirer is located at the terminal to realize the signature verification operation, and perform different analysis, matching and verification operations on the collected data and the entered data, and realize the data viewing operation after meeting the requirements. It can effectively solve the problems of low efficiency of privacy data query, imperfect privacy protection and inaccurate data level management in the blockchain environment, and realize efficient, safe and accurate privacy data query.

[0034] Embodiment 2 is different from Embodiment 1 in that: the present invention further discloses a blockchain privacy data query system, including: The data processing module is used to collect personal financial transaction data, classify it, and perform multi-level encryption operations on private data; The index query module establishes a connection protocol between the queryer and the data. By inputting the queryer's exploration requirements, the verification and decryption operations are performed based on the queryer's information. After the verification and decryption are completed, the verified data is transmitted to the queryer. The display terminal is convenient for the inquirer to operate and collect the verification data of the inquirer, and is also convenient for reference.

[0035] Embodiment 3 is different from Embodiment 1 and Embodiment 2 in that the query method of blockchain privacy data and the existing privacy data query method are used to realize the synchronous processing operation of multiple different data, and then the matching and positioning operation is performed based on the inquirer inputting the same query content at the same time, and the inquirer who has not established the agreement is set to perform the verification operation, and the detection results are shown in the following table: Table 1 Verification results In summary, by adopting the query method of blockchain privacy data of the present invention to implement the query operation of privacy data, the final data result is more accurate and takes less time, and can effectively intercept the request operation of abnormal users. Therefore, the query method of blockchain privacy data of the present invention can be better used in practical applications.

[0036] Meanwhile, the contents not described in detail in this specification belong to the prior art known to those skilled in the art.

[0037] Although embodiments of the present invention have been shown and described, it will be appreciated by those skilled in the art that various changes, modifications, substitutions and variations may be made to the embodiments without departing from the principles and spirit of the present invention, and that the scope of the present invention is defined by the appended claims and their equivalents.

Claims

1. A method for querying blockchain privacy data, characterized by: The specific steps include: A1. Collect financial transaction data of individuals and store the collected data in a database using wireless communication transmission technology; A2. Process the collected data and then extract and analyze it according to the query requirements. The specific operations are as follows: a21. After the collected data is classified, multi-level encryption operations are implemented on the data to enable decryption and verification operations to be performed during subsequent inquiries; a22. Based on the query request initiated by the inquirer, the identification matching algorithm is used to extract the required query data, and after confirming the identification data, the decryption verification operation is performed, and after the decryption requirements are met, the encrypted data is transmitted to the inquirer; A3. According to the matching data results, the decrypted query data is transmitted to the display terminal of the inquirer for display.

2. A method for querying blockchain privacy data according to claim 1, characterized in that: The multi-level encryption operation of data in a21 is: B1. Set a classification template, match the collected data with the category content in the classification template, and implement data classification. At this time, the unmatched data does not need to be encrypted; B2. Divide the data according to the classified content, determine the encryption level of the data according to the importance of the data, and implement multi-level encryption operations on the data based on the encryption level to form encrypted data with identification; B3. Store the encrypted data in different storage locations of the blockchain according to the level to facilitate traceability operations.

3. A method for querying blockchain privacy data according to claim 2, characterized in that: The operation of matching the collected data in B1 with the category content in the classification template is: b11. The categories in the classification template specifically include personal identity information categories, transaction content information categories and amount content information categories corresponding to financial data; b12. Match the category content corresponding to the collected data with the category content in the classification template, and store the data with the same category content in the corresponding category of the classification template; b13. Unmatched data will be removed without encryption, otherwise the retained data will need to be encrypted.

4. A method for querying blockchain privacy data according to claim 2, characterized in that: The multi-level encryption operation in B2 is: b21. Classify the data according to its importance, and form a three-level encryption method to encrypt the three types of data after the data is divided; b22, and the three-level encryption method is specifically: Level 1 encryption method: used for SMS verification of the inquirer; Secondary encryption method: used to identify and verify the face of the inquirer; Level 3 encryption method: used to identify and verify the signature of the inquirer; b23. The encryption applied to the three types of data is encrypted in a combined manner. For example, the important type of data is encrypted in sequence through the first, second and third level encryption methods, and the decryption also needs to be processed from the first to the third level. The less important type of data is encrypted in sequence through the first and second level encryption methods, and the last type of data is encrypted through the first level encryption method; b24. The encrypted data is identified by data category, data source and data generation time.

5. A method for querying blockchain privacy data according to claim 1, characterized in that: The specific operation of the identification matching algorithm in a22 is: C1. Establish a protocol between the queryer and the stored data and implement the entry and confirmation of the queryer's information. After it is correct, enter the query content of the queryer based on the search bar, and classify the encrypted data identifiers to form an identification data set marked as P; C2. Segment the query content, perform search operations in the identified data set P based on the segmented query content, and then increase the query requirements based on the searched and displayed content to determine the final required data content; C3. Decrypt the final required data content.

6. A method for querying blockchain privacy data according to claim 5, characterized in that: The operation of segmenting the query requirement content in C2 is: c21. Set the window function to extract content based on the query requirement content and match it with the content in the identification data set P; c22. If there is the same required data content, there is no need to split it. Otherwise, the extraction length of the window function is shortened, and it is gradually reduced from the end of the query required content until the extracted content matches the content in the identification data set P. c23. Then, a new round of window function extraction operation starts after the content extracted from the query requirement content, until all the query requirement content is traversed, and then sorted by the number of occurrences of the searched identification data for personnel confirmation.

7. A method for querying blockchain privacy data according to claim 4, characterized in that: The operation of decryption verification after confirming the identification data in a22 is: D1. Click to confirm according to the finalized identification data, check the importance level of the identification data, and determine the encryption method level according to the importance level to perform corresponding step-by-step decryption operations; D2. The specific decryption operation results are: Result 1: If the data is the last category identifier, the inquirer enters his / her own number and requests the terminal to send a PIN code to achieve input matching. After the match is achieved, the decryption operation is verified; Result 2 is the less important category identification data. After completing the verification operation of result 1, the terminal realizes the recognition operation of the inquirer's face and matches it with the input information when the protocol is initially established. After the match is achieved, the decryption operation is verified; Result 3 is important category identification data. After completing the verification operation of result 2, the inquirer implements the signature verification operation at the terminal and matches it with the input information when the agreement was initially established. After the match is achieved, the decryption operation is verified; D3. After the decryption verification operation is completed, the queried data is displayed through the terminal, and the request that has not completed the decryption operation is intercepted and marked.

8. A method for querying blockchain privacy data according to claim 7, characterized in that: In the second result, the terminal implements the following operations to recognize the face of the queryer: d201. Using the terminal to realize three-dimensional scanning of the inquirer's face, and realizing video data obtained by detecting the inquirer's movements according to the instruction requirements, and the video data is scaled in proportion to the actual face size; d202, dividing the video data into image data according to the set number of frames, and then extracting the image data entered when the protocol is established, by converting the collected image data and the extracted image data into images with the same pixels, and performing coverage comparison according to the image corner point position alignment based on the image data at the corresponding position; d203, setting a plurality of comparison points based on the centers of the characteristic parts of the two image data, and visualizing the upper image data, and observing whether the spacing of the same comparison points of the corresponding characteristic parts on the plane is within the deviation threshold; By obtaining the same comparison point spacing of the corresponding feature part as L1, and setting the deviation threshold as L2, and the number of comparison points on a single image data as M, the judgment formula for whether the facial recognition is passed is obtained: F = (m / M) ≥ f; m is the number of comparison points that meet the requirements after comparing the same comparison point spacing with the set deviation threshold, that is, L1≤L2, m / M represents the ratio of the number of comparison points that meet the requirements to the total number of comparison points, and f is the set minimum threshold for passing facial recognition, that is, if the judgment formula is met, the facial recognition verification passes, otherwise it fails and the query request needs to be intercepted.

9. A method for querying blockchain privacy data according to claim 7, characterized in that: In the third result, the operation of the queryer at the terminal to implement signature verification is: d211. Use the terminal to provide a signature interface and facilitate the inquirer to perform the signature operation. After confirmation, collect the signature data, extract the various signature data entered when the agreement was established, and match the collected signature data with the extracted signature data; d212. Analyze and operate the input signature data to extract the common outline features and connected stroke features in the process of multiple signatures, intercept and mark the partial image, and then extract the corresponding partial position image of the collected signature data and compare it with the intercepted partial image; d213. If the corresponding local position image of the collected signature data is consistent with the intercepted local image, the signature verification operation passes; otherwise, it fails and the query request needs to be intercepted.

10. A blockchain privacy data query system, according to a blockchain privacy data query method according to any one of claims 1-9, characterized in that: include: The data processing module is used to collect personal financial transaction data, classify it, and perform multi-level encryption operations on private data; The index query module establishes a connection protocol between the queryer and the data. By inputting the queryer's exploration requirements, the verification and decryption operations are performed based on the queryer's information. After the verification and decryption are completed, the verified data is transmitted to the queryer. The display terminal is convenient for the inquirer to operate and collect the verification data of the inquirer, and is also convenient for reference.

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