Public theory anti-anonymous analysis method and device fusing public network data

Abstract

The invention relates to a public theory anti-anonymous analysis method and device fusing public network data, and the method comprises the steps: reading block information from a Zhash full node through an RPC request, carrying out the traversal of a transaction hash value, initiating the RPC request, obtaining transaction information, and determining an input / output address and a corresponding input / output amount according to the transaction information. And respectively storing the block information, the transaction information, the input / output address and the input / output amount in a block table, a transaction table and an input and output table to generate block chain data, and storing the block chain data in a database. And analyzing the block chain data to cluster transaction information of different dimensions in the block chain data to obtain different clustering results. And receiving a GET request from the display layer, and in response to the GET request, sending the corresponding block information, the transaction information and the clustering result in the database to the display layer through POST to generate display data, thereby facilitating analysis of a transfer relationship between different addresses in a transaction network.

Description

Technical Field

[0001] The present invention relates to the field of digital currency and privacy protection technology, and in particular to a public rational anti-anonymity analysis method and device integrating public network data. Background Art

[0002] With the rapid development of the digital currency market, the anonymity and privacy protection features of digital currency have brought unprecedented challenges to financial supervision.

[0003] Traditional financial regulatory methods mainly rely on tracking bank accounts, transaction records and other methods for monitoring and analysis. As for digital currencies with strong privacy, especially Zcash, Zcash is a cryptocurrency based on zero-knowledge proof (ZKP) technology. Its main feature is to achieve transaction privacy protection through zero-knowledge proof, making information such as transaction amount and transaction parties invisible on the chain. However, this privacy protection also makes it very challenging for regulators to monitor and analyze transaction activities, especially the tracking and supervision of illegal capital flows. In traditional financial regulatory methods, the encryption and concealment of transaction content make it difficult for regulators to directly obtain transaction details through on-chain data, resulting in certain regulatory loopholes and increasing the risk of criminal activities such as illegal capital flows. Summary of the invention

[0004] Based on this, it is necessary to provide a method and device for analyzing the transfer relationship between different addresses in the transaction network, and find possible fund flows and associations in anonymous transaction records, so as to provide regulators with effective tools to identify suspicious activities and prevent financial crimes, which integrates public network data for public anti-anonymity analysis.

[0005] The present invention provides a public rational anti-anonymity analysis method integrating public network data, the method comprising:

[0006] Read block information from the Zcash full node through an RPC request, and traverse the transaction hash value to initiate the RPC request to obtain transaction information, so as to determine the input and output addresses and their corresponding input and output amounts according to the transaction information;

[0007] The block information, transaction information, input and output addresses, and input and output amounts are stored in a block table, a transaction table, and an input and output table, respectively, to generate blockchain data and store it in a database;

[0008] Parsing the blockchain data to cluster transaction information of different dimensions in the blockchain data to obtain different clustering results;

[0009] Receiving a GET request from the display layer, and sending the corresponding block information, transaction information, and clustering results in the database to the display layer via POST in response to the GET request to generate display data;

[0010] The Zcash full node is used to provide the data source of the whole network blocks and transactions. The clustering results include the clustering results of Zcash founders, user clustering results, specific amount clustering results and the same input clustering results. The display data is data that meets the display requirements of the display layer. The display layer includes data overview, block browsing, block details, transaction details, address details, address query and clustering results.

[0011] In one embodiment, the process of reading block information from a Zcash full node through an RPC request, and traversing the transaction hash value to initiate the RPC request to obtain transaction information, so as to determine the input and output addresses and their corresponding input and output amounts according to the transaction information, includes:

[0012] Sending the RPC request to the Zcash full node, obtaining the block information through the Zcash full node in response to the RPA request, and traversing the transaction hash values ​​to initiate the RPA request one by one to obtain transaction information corresponding to each transaction hash value;

[0013] The input and output addresses are obtained according to the transaction information, and the input and output amounts corresponding to each of the input and output addresses are extracted to trace the currency source transaction of the input address.

[0014] In one embodiment, storing the block information, transaction information, input and output addresses, and input and output amounts in a block table, a transaction table, and an input and output table, respectively, to generate blockchain data and store it in a database, includes:

[0015] Calling the data storage layer to store the block information in the block table, the transaction information in the transaction table, and the input and output addresses and the corresponding input and output amounts in the input and output tables;

[0016] The block table, transaction table, and input and output tables are uniformly stored in the database, and the blockchain data is generated at the same time.

[0017] In one embodiment, the parsing of the blockchain data to cluster transaction information of different dimensions in the blockchain data to obtain different clustering results includes:

[0018] Obtaining a founder address from the blockchain data, and parsing the founder address to obtain the founder address with the same transaction behavior, wherein the transaction amount in the transaction behavior and the amount received by the founder address have an integer multiple relationship;

[0019] Based on the founder address and transaction behavior, the transaction table in the database is queried and analyzed to match the address information controlled by the founder in the database, and the address information is stored in the founder transaction table to obtain the founder clustering result.

[0020] In one embodiment, the parsing of the blockchain data to cluster transaction information of different dimensions in the blockchain data to obtain different clustering results further includes:

[0021] Obtain the addresses of mainstream Zcash mining pools as seed data marked by the user, and respectively use the T mining pool profit distribution model and the Z mining pool profit distribution model to mark the address information stored in the database to obtain the transaction addresses belonging to each mining pool;

[0022] The transaction address is stored in a user transaction table, and the user transaction table is stored in the database to obtain a user clustering result.

[0023] In one embodiment, the parsing of the blockchain data to cluster transaction information of different dimensions in the blockchain data to obtain different clustering results further includes:

[0024] Acquire first transaction information from a first address to a second address and second transaction information from a second address to a first address respectively, and associate the first address with the second address when the transaction amounts corresponding to the first transaction information and the second transaction information match a set amount fingerprint and the first transaction information and the second transaction information occur in a chronological order;

[0025] The transaction table in the database is queried and analyzed, the numbers after the decimal point of the transaction amount are converted into strings for decimal comparison, and the transaction time is verified. After the verification is passed, the associated address is stored in the specific amount transaction table to obtain the specific amount clustering result.

[0026] In one embodiment, the parsing of the blockchain data to cluster transaction information of different dimensions in the blockchain data to obtain different clustering results further includes:

[0027] Acquire an address cluster list and initialize the address cluster list, wherein the initialized address cluster list is used to store clustered addresses;

[0028] Query and obtain all identical input transaction information containing transparent input addresses from the database, deduplicate all input addresses of the identical input transaction information, and store the deduplicated input addresses in a temporary set;

[0029] The address cluster list is traversed, and when there is an intersection between the temporary set and the address cluster in the address cluster list, the address cluster is updated to be a union with the temporary list, and when there is no intersection between the temporary set and any address cluster in the address cluster list, the temporary set is added to the address cluster list.

[0030] The present invention also provides a public rationale anti-anonymity analysis device for integrating public network data, which is used to implement any of the public rationale anti-anonymity analysis methods for integrating public network data as described above, and the device comprises:

[0031] A data acquisition module is used to read block information from a Zcash full node through an RPC request, and to traverse the transaction hash value to initiate the RPC request to obtain transaction information, so as to determine the input and output addresses and their corresponding input and output amounts according to the transaction information;

[0032] A data storage module, used to store the block information, transaction information, input and output addresses, and input and output amounts in a block table, a transaction table, and an input and output table, respectively, to generate blockchain data and store it in a database;

[0033] A data clustering processing module, used to parse the blockchain data to cluster transaction information of different dimensions in the blockchain data to obtain different clustering results;

[0034] A data display module, configured to receive a GET request from the display layer, and in response to the GET request, send the corresponding block information, transaction information, and clustering results in the database to the display layer via POST to generate display data;

[0035] The Zcash full node is used to provide the data source of the whole network blocks and transactions. The clustering results include the clustering results of Zcash founders, user clustering results, specific amount clustering results and the same input clustering results. The display data is data that meets the display requirements of the display layer. The display layer includes data overview, block browsing, block details, transaction details, address details, address query and clustering results.

[0036] The present invention also provides an electronic device, including a memory and a processor, wherein the memory stores a computer program, and when the processor executes the computer program, it implements the public rational anti-anonymity analysis method for integrating public network data as described in any one of the above.

[0037] The present invention also provides a computer storage medium storing a computer program, which, when executed by a processor, implements any of the above-mentioned public rational anti-anonymity analysis methods for integrating public network data.

[0038] The above-mentioned public rational anti-anonymity analysis method and device integrating public network data reads block information from the Zcash full node through RPC request, and traverses the transaction hash value to initiate RPC request to obtain transaction information, so as to determine the input and output addresses and their corresponding input and output amounts according to the transaction information. Then the block information, transaction information, input and output addresses and input and output amounts are stored in the block table, transaction table, and input and output table respectively to generate blockchain data and store it in the database. In the cluster analysis process, the blockchain data is parsed to cluster the transaction information of different dimensions in the blockchain data, and the clustering results including the Zcash founder clustering results, user clustering results, specific amount clustering results and the same input clustering results are obtained. Finally, a GET request is received from the display layer, and in response to the GET request, the corresponding block information, transaction information and clustering results in the database are sent to the display layer via POST to generate display data. The display data is data that meets the display requirements of the display layer. The display layer includes data overview, block browsing, block details, transaction details, address details, address query and clustering results, which facilitates the analysis of transfer relationships between different addresses in the transaction network, and finds possible fund flows and associations in anonymous transaction records, thereby providing regulators with effective tools to identify suspicious activities and prevent financial crimes. BRIEF DESCRIPTION OF THE DRAWINGS

[0039] In order to more clearly illustrate the technical solutions in the present invention or the prior art, the following briefly introduces the drawings required for use in the embodiments or the description of the prior art. Obviously, the drawings described below are some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative work.

[0040] Figure 1 One of the flow charts of the public rational anti-anonymity analysis method for integrating public network data provided by the present invention;

[0041] Figure 2 A schematic diagram of the blockchain supervision platform architecture of the public rational anti-anonymity analysis method integrating public network data in the specific embodiment provided by the present invention;

[0042] Figure 3 The second flowchart of the public rational anti-anonymity analysis method for integrating public network data provided by the present invention;

[0043] Figure 4 The third flowchart of the public rational anti-anonymity analysis method for integrating public network data provided by the present invention;

[0044] Figure 5 The fourth flowchart of the public rational anti-anonymity analysis method for integrating public network data provided by the present invention;

[0045] Figure 6 The fifth flowchart of the public rational anti-anonymity analysis method for integrating public network data provided by the present invention;

[0046] Figure 7 Flow chart of the public anti-anonymity analysis method for integrating public network data provided by the present invention No. 6;

[0047] Figure 8 Flow chart of the public rational anti-anonymity analysis method for integrating public network data provided by the present invention No. 7;

[0048] Fig. 9 A schematic diagram of the structure of a public rational anti-anonymity analysis device for integrating public network data provided by the present invention;

[0049] Fig.10 This is a diagram of the internal structure of the electronic device provided by the present invention. DETAILED DESCRIPTION

[0050] In order to make the purpose, technical solution and advantages of the embodiments of the present invention clearer, the technical solution in the embodiments of the present invention will be clearly and completely described below in conjunction with the drawings in the embodiments of the present invention. Obviously, the described embodiments are 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.

[0051] Combine the following Figures 1 to 10 The present invention describes a method and device for analyzing public network data in a public rationale manner and in an anonymous manner.

[0052] like Figure 1 As shown, in one embodiment, a public rational anti-anonymization analysis method integrating public network data includes the following steps:

[0053] Step S110, read the block information from the Zcash full node through an RPC request, and traverse the transaction hash value to initiate an RPC request to obtain the transaction information, so as to determine the input and output addresses and their corresponding input and output amounts according to the transaction information.

[0054] Among them, the Zcash full node is used to provide block and transaction data sources for the entire network.

[0055] Specifically, the blockchain supervision platform sends an RPC request to the Zcash full node, reads block information from the Zcash full node through the RPC request, traverses the transaction hash value to initiate an RPC request to obtain transaction information, and determines the input and output addresses and the input and output amounts corresponding to each input and output address based on the obtained transaction information.

[0056] Combination Figure 2 As shown, in a specific embodiment, the public rational anti-anonymity analysis method for integrating public network data provided by the present invention is implemented through a blockchain supervision platform and is divided into multiple functional modules:

[0057] The data acquisition layer consists of original block files, Zcash full nodes, RPC request data, and block data parsing programs. Among them, the Zcash full node is used to provide the data source of the entire network block and transaction data, the original block file is used to store the original data of the blockchain, and the RPC request data is used to interact with the Zcash node through remote procedure calls to obtain real-time data. The block data parsing program is used to parse and convert the acquired data for subsequent storage and processing.

[0058] In this embodiment, the blockchain supervision platform sends an RPC request to the Zcash full node to obtain the corresponding block information, then traverses the transaction hash values ​​to initiate RPC requests one by one to obtain detailed information of the transaction, and then extracts the corresponding input and output amounts based on the input and output addresses obtained from the transaction information, and can simultaneously trace the currency source transaction of the input address. This process completes the acquisition of the block and transaction information data of the Zcash currency.

[0059] Step S120, storing the block information, transaction information, input and output addresses, and input and output amounts in the block table, transaction table, and input and output table, respectively, to generate blockchain data and store it in the database.

[0060] Specifically, the blockchain supervision platform stores the block information obtained in step S110 in the block table, stores the transaction information in the transaction table, and stores the input and output addresses and their corresponding input and output amounts in the input and output tables, and then stores the block table, transaction table, and input and output table in the database to generate corresponding blockchain data.

[0061] Combination Figure 2 As shown, in a specific embodiment, the public rational anti-anonymity analysis method for integrating public network data provided by the present invention, the blockchain supervision platform also includes a data storage layer. The data storage layer includes a database and Qidong City clustering result data. Among them, the database is used to store the parsed block information, transaction information, input and output addresses and their corresponding input and output amounts.

[0062] In this embodiment, the block information obtained by the platform is stored in the block table, the transaction details obtained are stored in the transactions table, the input and output amounts corresponding to the input and output addresses are stored in the inputs and outputs tables, and the data tables are uniformly stored in the same database to form blockchain data, which is convenient for subsequent data query, analysis and processing.

[0063] Step S130, parsing the blockchain data to cluster transaction information of different dimensions in the blockchain data to obtain different clustering results.

[0064] Among them, the clustering results include Zcash founder clustering results, user clustering results, specific amount clustering results and same input clustering results.

[0065] Specifically, the blockchain supervision platform parses the blockchain data in the database and clusters the transaction information of different dimensions in the blockchain data to obtain different clustering results.

[0066] Combination Figure 2 As shown, in a specific embodiment, the public rational anti-anonymity analysis method for integrating public network data provided by the present invention, the blockchain supervision platform also includes a data processing layer, the data processing layer, including founder clustering, user clustering, unique amount clustering and same input clustering. Among them, founder clustering is used to identify and aggregate the transaction behavior of the founder of Zcash. User clustering is used to identify user addresses and their related transaction activities. Unique amount clustering is used to identify and cluster transactions of specific amounts. Same input clustering is used to analyze transactions with the same input address and make correlation judgments.

[0067] In this embodiment, the data processing layer completes the in-depth analysis of the blockchain data through a multi-dimensional heuristic method:

[0068] Founder clustering: Get the founder address and analyze the data. It can be concluded that the founder addresses have the same transaction behavior, and the transaction amount is an integer multiple of the block reward they receive. Query and analyze the transactions table in the database, match the address information controlled by the founder in the database, and store it in the Founders table (founder transaction table) in the database.

[0069] User clustering: Collect the addresses of mainstream Zcash mining pools as seed data for user labeling, and use the T mining pool profit distribution model and the Z mining pool profit distribution model to label the address information stored in the database, so as to obtain the transaction addresses belonging to each mining pool and store them in the Miners table (user transaction table) in the database.

[0070] Unique amount clustering: For a t-to-z (t address to z address) transaction and a z-to-t (z address to t address) transaction, if the amount fingerprints of the two transactions match, and the t-to-z transaction occurs before the z-to-t transaction, the addresses of the two transactions can be associated, and it is considered that these addresses are controlled by the same entity. The transactions table in the database is queried and analyzed, and the decimal comparison is performed by converting the numbers after the decimal point into strings. At the same time, the transaction time is verified to exclude the situation where the z-to-t transaction occurs before the corresponding t-to-z transaction, thereby improving accuracy. The associated addresses are stored in the UniqueClusters table (specific amount transaction table) in the database.

[0071] Clustering of same inputs: Initialize an address cluster list to store clustered addresses. Query all transactions containing transparent input addresses (t-to-t transactions and t-to-z transactions). After each transaction is queried, deduplicate all input addresses of the transaction and store them in a temporary collection. Traverse the address cluster list. If the temporary collection intersects with an address cluster in the list, update the address cluster to the union of the two; if the temporary collection does not intersect with any address cluster, add the temporary collection to the address cluster list as a new item. Repeat this cycle until the input addresses of all related transactions are finally clustered, and the clustered addresses are stored in the HeuristicClusters table (same input transaction table) in the database.

[0072] By adopting the above-mentioned multi-dimensional heuristic method, data with specific characteristics can be identified and clustered to form clustering results of different dimensions, providing data support for the blockchain supervision platform.

[0073] Step S140, receiving a GET request from the display layer, and sending the corresponding block information, transaction information and clustering results in the database to the display layer via POST in response to the GET request to generate display data.

[0074] Among them, the display data is data that meets the display requirements of the user display layer. The display layer includes data overview, block browsing, block details, transaction details, address details, address query and clustering results.

[0075] Specifically, the blockchain supervision platform receives a GET request from the display layer, and in response to the GET request, sends the corresponding block information, transaction information and clustering results in the database to the display layer via POST to generate display data, and displays data overview, block browsing, block details, transaction details, address details, address query and clustering results on the display layer to facilitate the analysis of transaction information by regulatory agencies.

[0076] Combination Figure 2 As shown, in a specific embodiment, the public rational anti-anonymity analysis method for integrating public network data provided by the present invention, the blockchain supervision platform also includes a business layer. The business layer includes data query, data processing and data encapsulation. Among them, data query is used to query the stored data through the interface, data processing is used to perform business logic processing on the query results, and data encapsulation is used to encapsulate the processed data into a format that can be displayed by the front end.

[0077] In this embodiment, the business layer interacts with the data storage layer through POST / GET requests. The corresponding function of the display layer sends a GET request to the business layer, and the business layer sends the corresponding block information, transaction information, and address clustering result information in the database to the display layer through POST, providing the display layer system with a response function and generating data that meets the display requirements.

[0078] The blockchain supervision platform also includes a display layer, which includes functional units such as overview, block browsing, block details, transaction details, address details, address query, and clustering result analysis. Among them, the overview is used to provide a statistical overview of data such as blocks, transactions, users, and founders. Block browsing is used to query the content of the block table to build a brief information of the block, encapsulate it and display it, and support accurate search through block height and block hash. Block details are used to query the corresponding block in the block table through the block hash value information, and build detailed information of the block according to the needs, and can view the block hash, height, block time, and information of all transactions included. Transaction details can view the detailed information of each transaction, including hash value, transaction time, transaction type, and input and output parties of the transaction. Address details can view all activities of the input or output party address in any year, including all income and expenditure, as well as the transaction record information of the address. Address query is used to query the clustering result tables Founders, Miners, UniqueClusters and HeuristicClusters respectively, and then synthesize the results. Clustering result analysis is used to provide analysis results based on clustering algorithms, such as clustering statistics of founders, users, unique amounts, and identical inputs. The display layer presents analyzed and processed data through a visual interface to help users monitor and supervise data.

[0079] In this embodiment, the efficient acquisition and standardized processing of blockchain data are achieved through the Zcash full node and data analysis program, and the transaction behavior and data characteristics are effectively identified through cluster analysis of founders, users, unique amounts and identical inputs. In addition, the visualization platform provides data overview and in-depth analysis functions, so that users can quickly grasp the operation status and transaction characteristics of the blockchain, and the hierarchical structure design also improves the maintainability and scalability of the system.

[0080] The above-mentioned public rational anti-anonymity analysis method integrating public network data reads block information from the Zcash full node through RPC requests, and traverses the transaction hash value to initiate RPC requests to obtain transaction information, so as to determine the input and output addresses and their corresponding input and output amounts according to the transaction information. The block information, transaction information, input and output addresses and input and output amounts are then stored in the block table, transaction table, and input and output table respectively to generate blockchain data and store it in the database. In the cluster analysis process, the blockchain data is parsed to cluster the transaction information of different dimensions in the blockchain data, and clustering results including Zcash founder clustering results, user clustering results, specific amount clustering results, and the same input clustering results are obtained. Finally, a GET request is received from the display layer, and in response to the GET request, the corresponding block information, transaction information and clustering results in the database are sent to the display layer via POST to generate display data. The display data is data that meets the display requirements of the display layer. The display layer includes data overview, block browsing, block details, transaction details, address details, address query and clustering results, which facilitates the analysis of transfer relationships between different addresses in the transaction network, and finds possible fund flows and associations in anonymous transaction records, thereby providing regulators with effective tools to identify suspicious activities and prevent financial crimes.

[0081] like Figure 3 As shown, in one embodiment, the public rational anti-anonymity analysis method for integrating public network data provided by the present invention reads block information from the Zcash full node through an RPC request, and traverses the transaction hash value to initiate an RPC request to obtain transaction information, so as to determine the input and output addresses and their corresponding input and output amounts according to the transaction information, specifically including the following steps:

[0082] Step S111, sending an RPC request to the Zcash full node, obtaining block information through the Zcash full node in response to the RPA request, and traversing the transaction hash values ​​to initiate RPA requests one by one to obtain the transaction information corresponding to each transaction hash value.

[0083] Step S112, obtaining the input and output addresses according to the transaction information, and extracting the input and output amounts corresponding to each input and output address to trace the currency source transaction of the input address.

[0084] like Figure 4 As shown, in one embodiment, the public rational anti-anonymity analysis method for integrating public network data provided by the present invention stores block information, transaction information, input and output addresses, and input and output amounts in a block table, a transaction table, and an input and output table, respectively, to generate blockchain data and store it in a database, specifically comprising the following steps:

[0085] Step S121, calling the data storage layer to store the block information in the block table, the transaction information in the transaction table, and the input and output addresses and the corresponding input and output amounts in the input and output tables.

[0086] Step S122, the block table, transaction table, and input and output tables are uniformly stored in the database, and blockchain data is generated at the same time.

[0087] like Figure 5 As shown, in one embodiment, the public rational anti-anonymity analysis method for integrating public network data provided by the present invention parses blockchain data to cluster transaction information of different dimensions in the blockchain data to obtain different clustering results, specifically including the following steps:

[0088] Step S131, obtain the founder address from the blockchain data, and parse the founder address to obtain the founder address with the same transaction behavior, and the transaction amount in the transaction behavior and the received amount of the founder address have an integer multiple relationship.

[0089] Step S132, query and analyze the transaction table in the database based on the founder address and transaction behavior to match the address information controlled by the founder in the database, and store the address information in the founder transaction table to obtain the founder clustering result.

[0090] like Figure 6 As shown, in one embodiment, the public rational anti-anonymity analysis method for integrating public network data provided by the present invention parses the blockchain data to cluster the transaction information of different dimensions in the blockchain data to obtain different clustering results, and specifically includes the following steps:

[0091] Step S133, obtaining the addresses of mainstream Zcash mining pools as seed data marked by the user, and using the T mining pool profit distribution mode and the Z mining pool profit distribution mode to mark the address information stored in the database, and obtaining the transaction addresses belonging to each mining pool.

[0092] Step S134, storing the transaction address in the user transaction table, and storing the user transaction table in the database to obtain the user clustering result.

[0093] like Figure 7 As shown, in one embodiment, the public rational anti-anonymity analysis method for integrating public network data provided by the present invention parses the blockchain data to cluster the transaction information of different dimensions in the blockchain data to obtain different clustering results, and specifically includes the following steps:

[0094] Step S135, respectively obtain the first transaction information from the first address to the second address and the second transaction information from the second address to the first address, and associate the first address with the second address when the transaction amounts corresponding to the first transaction information and the second transaction information match the set amount fingerprint and the time when the first transaction information and the second transaction information occur in sequence.

[0095] Step S136, query and analyze the transaction table in the database, convert the digits after the decimal point of the transaction amount into a string for decimal comparison, and verify the transaction time. After the verification is passed, the associated address is stored in the specific amount transaction table to obtain a specific amount clustering result.

[0096] like Figure 8 As shown, in one embodiment, the public rational anti-anonymity analysis method for integrating public network data provided by the present invention parses the blockchain data to cluster the transaction information of different dimensions in the blockchain data to obtain different clustering results, and specifically includes the following steps:

[0097] Step S137, obtaining an address cluster list and initializing the address cluster list, wherein the initialized address cluster list is used to store clustered addresses.

[0098] Step S138, query and obtain all identical input transaction information containing transparent input addresses from the database, and deduplicate all input addresses of the identical input transaction information, and store the deduplicated input addresses in a temporary set.

[0099] Step S139, traverse the address cluster list, and when there is an intersection between the temporary set and the address cluster in the address cluster list, update the address cluster to the union with the temporary list; and when there is no intersection between the temporary set and any address cluster in the address cluster list, add the temporary set to the address cluster list.

[0100] The following is a description of the public rational anti-anonymity analysis device for integrating public network data provided by the present invention. The public rational anti-anonymity analysis device for integrating public network data described below and the public rational anti-anonymity analysis method for integrating public network data described above can be referenced to each other.

[0101] like Fig. 9 As shown, in one embodiment, a public rational anti-anonymization analysis device integrating public network data includes a data acquisition module 910, a data storage module 920, a data clustering processing module 930 and a data display module 940.

[0102] The data acquisition module 910 is used to read block information from the Zcash full node through an RPC request, and traverse the transaction hash value to initiate an RPC request to obtain transaction information, so as to determine the input and output addresses and their corresponding input and output amounts according to the transaction information.

[0103] The data storage module 920 is used to store block information, transaction information, input and output addresses, and input and output amounts in the block table, transaction table, and input and output table, respectively, to generate blockchain data and store it in the database.

[0104] The data clustering processing module 930 is used to parse the blockchain data to cluster transaction information of different dimensions in the blockchain data to obtain different clustering results.

[0105] The data display module 940 is used to receive a GET request from the display layer, and in response to the GET request, send the corresponding block information, transaction information and clustering results in the database to the display layer via POST to generate display data.

[0106] Among them, the Zcash full node is used to provide the data source of blocks and transactions for the entire network. The clustering results include the clustering results of Zcash founders, user clustering results, specific amount clustering results and the same input clustering results. The displayed data is the data that meets the display requirements of the display layer. The display layer includes data overview, block browsing, block details, transaction details, address details, address query and clustering results.

[0107] In this embodiment, the public rational anti-anonymity analysis device for integrating public network data provided by the present invention, the data acquisition module 910 is specifically used for:

[0108] Send an RPC request to the Zcash full node, which responds to the RPA request to obtain block information, and traverses the transaction hash values ​​to initiate RPA requests one by one to obtain the transaction information corresponding to each transaction hash value.

[0109] Get the input and output addresses based on the transaction information, and extract the input and output amounts corresponding to each input and output address to trace the currency source transaction of the input address.

[0110] In this embodiment, the public rational anti-anonymity analysis device for integrating public network data provided by the present invention, the data storage module 920 is specifically used for:

[0111] The data storage layer is called to store block information in the block table, transaction information in the transaction table, and input and output addresses and corresponding input and output amounts in the input and output tables.

[0112] The block table, transaction table, and input and output tables are stored in the database and blockchain data is generated at the same time.

[0113] In this embodiment, the public rational anti-anonymity analysis device for integrating public network data provided by the present invention, the data clustering processing module 930 is specifically used for:

[0114] The founder address is obtained from the blockchain data, and the founder address is parsed to obtain the founder address with the same transaction behavior. The transaction amount in the transaction behavior and the amount received by the founder address have an integer multiple relationship.

[0115] Based on the founder's address and transaction behavior, the transaction table in the database is queried and analyzed to match the address information controlled by the founder in the database, and the address information is stored in the founder's transaction table to obtain the founder clustering result.

[0116] In this embodiment, the public rational anti-anonymity analysis device for integrating public network data provided by the present invention, the data clustering processing module 930 is specifically used for:

[0117] The addresses of mainstream Zcash mining pools are obtained as the seed data for user marking, and the address information stored in the database is marked using the T mining pool profit distribution model and the Z mining pool profit distribution model respectively to obtain the transaction addresses belonging to each mining pool.

[0118] The transaction address is stored in the user transaction table, and the user transaction table is stored in the database to obtain the user clustering result.

[0119] In this embodiment, the public rational anti-anonymity analysis device for integrating public network data provided by the present invention, the data clustering processing module 930 is specifically used for:

[0120] First transaction information from the first address to the second address and second transaction information from the second address to the first address are obtained respectively, and when the transaction amounts corresponding to the first transaction information and the second transaction information match the set amount fingerprint and there is a chronological order in time between the first transaction information and the second transaction information, the first address and the second address are associated.

[0121] The transaction table in the database is queried and analyzed, the numbers after the decimal point of the transaction amount are converted into strings for decimal comparison, and the transaction time is verified. After the verification is passed, the associated address is stored in the specific amount transaction table to obtain the specific amount clustering result.

[0122] In this embodiment, the public rational anti-anonymity analysis device for integrating public network data provided by the present invention, the data clustering processing module 930 is specifically used for:

[0123] The address cluster list is obtained and initialized. The initialized address cluster list is used to store clustered addresses.

[0124] Query and obtain all identical input transaction information containing transparent input addresses from the database, and deduplicate all input addresses of the identical input transaction information. The deduplicated input addresses are stored in a temporary collection.

[0125] The address cluster list is traversed, and when there is an intersection between the temporary set and the address clusters in the address cluster list, the address cluster is updated to be the union of the temporary set and the temporary list; and when there is no intersection between the temporary set and any address cluster in the address cluster list, the temporary set is added to the address cluster list.

[0126] Fig.10 An example of a physical structure diagram of an electronic device is shown. The electronic device may be a smart terminal, and its internal structure diagram may be as follows: Fig.10 As shown. The electronic device includes a processor, an internal memory and a network interface connected via a system bus. The processor of the electronic device is used to provide computing and control capabilities. The memory of the electronic device includes a non-volatile storage medium and an internal memory. The non-volatile storage medium stores an operating system and a computer program. The internal memory provides an environment for the operation of the operating system and the computer program in the non-volatile storage medium. The network interface of the electronic device is used to communicate with an external terminal via a network connection. When the computer program is executed by the processor, a public rational anti-anonymization analysis method for integrating public network data is implemented, and the method includes:

[0127] Read block information from the Zcash full node through RPC requests, and traverse the transaction hash value to initiate RPC requests to obtain transaction information, so as to determine the input and output addresses and their corresponding input and output amounts based on the transaction information;

[0128] The block information, transaction information, input and output addresses and input and output amounts are stored in the block table, transaction table and input and output table respectively to generate blockchain data and store it in the database;

[0129] Analyze blockchain data to cluster transaction information of different dimensions in blockchain data and obtain different clustering results;

[0130] Receive a GET request from the display layer, and in response to the GET request, send the corresponding block information, transaction information, and clustering results in the database to the display layer via POST to generate display data;

[0131] Among them, the Zcash full node is used to provide the data source of blocks and transactions for the entire network. The clustering results include the clustering results of Zcash founders, user clustering results, specific amount clustering results and the same input clustering results. The displayed data is the data that meets the display requirements of the display layer. The display layer includes data overview, block browsing, block details, transaction details, address details, address query and clustering results.

[0132] Those skilled in the art will understand that Fig.10 The structure shown in the figure is only a block diagram of a part of the structure related to the scheme of the present invention, and does not constitute a limitation on the electronic device to which the scheme of the present invention is applied. The specific electronic device may include more or fewer components than those shown in the figure, or combine certain components, or have a different arrangement of components.

[0133] On the other hand, the present invention also provides a computer storage medium storing a computer program, which, when executed by a processor, implements a public rational anti-anonymity analysis method for integrating public network data, the method comprising:

[0134] Read block information from the Zcash full node through RPC requests, and traverse the transaction hash value to initiate RPC requests to obtain transaction information, so as to determine the input and output addresses and their corresponding input and output amounts based on the transaction information;

[0135] The block information, transaction information, input and output addresses and input and output amounts are stored in the block table, transaction table and input and output table respectively to generate blockchain data and store it in the database;

[0136] Analyze blockchain data to cluster transaction information of different dimensions in blockchain data and obtain different clustering results;

[0137] Receive a GET request from the display layer, and in response to the GET request, send the corresponding block information, transaction information, and clustering results in the database to the display layer via POST to generate display data;

[0138] Among them, the Zcash full node is used to provide the data source of blocks and transactions for the entire network. The clustering results include the clustering results of Zcash founders, user clustering results, specific amount clustering results and the same input clustering results. The displayed data is the data that meets the display requirements of the display layer. The display layer includes data overview, block browsing, block details, transaction details, address details, address query and clustering results.

[0139] In another aspect, a computer program product or a computer program is provided, the computer program product or the computer program comprising computer instructions, the computer instructions being stored in a computer-readable storage medium. A processor of an electronic device reads the computer instructions from the computer-readable storage medium, and when the processor executes the computer instructions, a public rational anti-anonymization analysis method integrating public network data is implemented, the method comprising:

[0140] Read block information from the Zcash full node through RPC requests, and traverse the transaction hash value to initiate RPC requests to obtain transaction information, so as to determine the input and output addresses and their corresponding input and output amounts based on the transaction information;

[0141] The block information, transaction information, input and output addresses and input and output amounts are stored in the block table, transaction table and input and output table respectively to generate blockchain data and store it in the database;

[0142] Analyze blockchain data to cluster transaction information of different dimensions in blockchain data and obtain different clustering results;

[0143] Receive a GET request from the display layer, and in response to the GET request, send the corresponding block information, transaction information, and clustering results in the database to the display layer via POST to generate display data;

[0144] Among them, the Zcash full node is used to provide the data source of blocks and transactions for the entire network. The clustering results include the clustering results of Zcash founders, user clustering results, specific amount clustering results and the same input clustering results. The displayed data is the data that meets the display requirements of the display layer. The display layer includes data overview, block browsing, block details, transaction details, address details, address query and clustering results.

[0145] Those of ordinary skill in the art can understand that all or part of the processes in the above-mentioned embodiment methods can be implemented by instructing related hardware through a computer program, and the computer program can be stored in a non-volatile computer-readable storage medium. When the computer program is executed, it can include the processes of the embodiments of the above-mentioned methods. Among them, any reference to memory, storage, database or other media used in the embodiments provided by the present invention may include non-volatile and / or volatile memory. Non-volatile memory may include read-only memory (ROM), programmable ROM (PROM), electrically programmable ROM (EPROM), electrically erasable programmable ROM (EEPROM) or flash memory. Volatile memory may include random access memory (RAM) or external cache memory.

[0146] By way of illustration and not limitation, RAM is available in many forms, such as static RAM (SRAM), dynamic RAM (DRAM), synchronous DRAM (SDRAM), double data rate SDRAM (DDRSDRAM), enhanced SDRAM (ESDRAM), synchronous link (Synchlink) DRAM (SLDRAM), memory bus (Rambus) direct RAM (RDRAM), direct memory bus dynamic RAM (DRDRAM), and memory bus dynamic RAM (RDRAM), etc.

[0147] The technical features of the above embodiments may be combined arbitrarily. To make the description concise, not all possible combinations of the technical features in the above embodiments are described. However, as long as there is no contradiction in the combination of these technical features, they should be considered to be within the scope of this specification.

[0148] The above-mentioned embodiments only express several implementation methods of the present invention, and the description thereof is relatively specific and detailed, but it cannot be understood as limiting the scope of the patent of the present invention. It should be pointed out that, for ordinary technicians in this field, several variations and improvements can be made without departing from the concept of the present invention, which all belong to the protection scope of the present invention. Therefore, the protection scope of the patent of the present invention shall be subject to the attached claims.

Claims

1. A public rational anti-anonymization analysis method integrating public network data, characterized in that: The method comprises: Read block information from the Zcash full node through an RPC request, and traverse the transaction hash value to initiate the RPC request to obtain transaction information, so as to determine the input and output addresses and their corresponding input and output amounts according to the transaction information; The block information, transaction information, input and output addresses, and input and output amounts are stored in a block table, a transaction table, and an input and output table, respectively, to generate blockchain data and store it in a database; Parsing the blockchain data to cluster transaction information of different dimensions in the blockchain data to obtain different clustering results; Receiving a GET request from the display layer, and sending the corresponding block information, transaction information, and clustering results in the database to the display layer via POST in response to the GET request to generate display data; The Zcash full node is used to provide the data source of the whole network blocks and transactions. The clustering results include the clustering results of Zcash founders, user clustering results, specific amount clustering results and the same input clustering results. The display data is data that meets the display requirements of the display layer. The display layer includes data overview, block browsing, block details, transaction details, address details, address query and clustering results.

2. The public rational anti-anonymity analysis method for integrating public network data according to claim 1 is characterized in that: The process of reading block information from the Zcash full node through an RPC request and traversing the transaction hash value to initiate the RPC request to obtain transaction information, so as to determine the input and output addresses and their corresponding input and output amounts according to the transaction information, includes: Sending the RPC request to the Zcash full node, obtaining the block information through the Zcash full node in response to the RPA request, and traversing the transaction hash values ​​to initiate the RPA request one by one to obtain transaction information corresponding to each transaction hash value; The input and output addresses are obtained according to the transaction information, and the input and output amounts corresponding to each of the input and output addresses are extracted to trace the currency source transaction of the input address.

3. The public rational anti-anonymity analysis method for integrating public network data according to claim 1 is characterized in that: The storing of the block information, transaction information, input / output addresses, and input / output amounts in a block table, a transaction table, and an input / output table, respectively, to generate blockchain data and store it in a database, includes: Calling the data storage layer to store the block information in the block table, the transaction information in the transaction table, and the input and output addresses and the corresponding input and output amounts in the input and output tables; The block table, transaction table, and input and output tables are uniformly stored in the database, and the blockchain data is generated at the same time.

4. The public rational anti-anonymization analysis method for integrating public network data according to claim 1 is characterized in that: The parsing of the blockchain data to cluster transaction information of different dimensions in the blockchain data to obtain different clustering results includes: Obtaining a founder address from the blockchain data, and parsing the founder address to obtain the founder address with the same transaction behavior, wherein the transaction amount in the transaction behavior and the amount received by the founder address have an integer multiple relationship; Based on the founder address and transaction behavior, the transaction table in the database is queried and analyzed to match the address information controlled by the founder in the database, and the address information is stored in the founder transaction table to obtain the founder clustering result.

5. The public rational anti-anonymity analysis method for integrating public network data according to claim 4 is characterized in that: The parsing of the blockchain data to cluster transaction information of different dimensions in the blockchain data to obtain different clustering results also includes: Obtain the addresses of mainstream Zcash mining pools as seed data marked by the user, and respectively use the T mining pool profit distribution model and the Z mining pool profit distribution model to mark the address information stored in the database to obtain the transaction addresses belonging to each mining pool; The transaction address is stored in a user transaction table, and the user transaction table is stored in the database to obtain a user clustering result.

6. The public rational anti-anonymity analysis method for integrating public network data according to claim 5 is characterized in that: The parsing of the blockchain data to cluster transaction information of different dimensions in the blockchain data to obtain different clustering results also includes: Acquire first transaction information from a first address to a second address and second transaction information from a second address to a first address respectively, and associate the first address with the second address when the transaction amounts corresponding to the first transaction information and the second transaction information match a set amount fingerprint and the first transaction information and the second transaction information occur in a chronological order; The transaction table in the database is queried and analyzed, the numbers after the decimal point of the transaction amount are converted into strings for decimal comparison, and the transaction time is verified. After the verification is passed, the associated address is stored in the specific amount transaction table to obtain the specific amount clustering result.

7. The public rational anti-anonymity analysis method for integrating public network data according to claim 6 is characterized in that: The parsing of the blockchain data to cluster transaction information of different dimensions in the blockchain data to obtain different clustering results also includes: Acquire an address cluster list and initialize the address cluster list, wherein the initialized address cluster list is used to store clustered addresses; Query and obtain all identical input transaction information containing transparent input addresses from the database, deduplicate all input addresses of the identical input transaction information, and store the deduplicated input addresses in a temporary set; The address cluster list is traversed, and when there is an intersection between the temporary set and the address cluster in the address cluster list, the address cluster is updated to be a union with the temporary list, and when there is no intersection between the temporary set and any address cluster in the address cluster list, the temporary set is added to the address cluster list.

8. A public anti-anonymity analysis device integrating public network data, characterized in that: The apparatus is used to implement the public rational anti-anonymity analysis method for integrating public network data as described in any one of claims 1 to 7, comprising: A data acquisition module is used to read block information from a Zcash full node through an RPC request, and to traverse the transaction hash value to initiate the RPC request to obtain transaction information, so as to determine the input and output addresses and their corresponding input and output amounts according to the transaction information; A data storage module, used to store the block information, transaction information, input and output addresses, and input and output amounts in a block table, a transaction table, and an input and output table, respectively, to generate blockchain data and store it in a database; A data clustering processing module, used to parse the blockchain data to cluster transaction information of different dimensions in the blockchain data to obtain different clustering results; A data display module, configured to receive a GET request from the display layer, and in response to the GET request, send the corresponding block information, transaction information, and clustering results in the database to the display layer via POST to generate display data; The Zcash full node is used to provide the data source of the whole network blocks and transactions. The clustering results include the clustering results of Zcash founders, user clustering results, specific amount clustering results and the same input clustering results. The display data is data that meets the display requirements of the display layer. The display layer includes data overview, block browsing, block details, transaction details, address details, address query and clustering results.

9. An electronic device comprising a memory and a processor, wherein the memory stores a computer program, wherein: When the processor executes the computer program, the steps of the public rational anti-anonymization analysis method for integrating public network data as described in any one of claims 1 to 7 are implemented.

10. A computer storage medium storing a computer program, characterized in that: When the computer program is executed by a processor, the steps of the public rational anti-anonymization analysis method for integrating public network data described in any one of claims 1 to 7 are implemented.

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