CN110580625A - circulating data supervision method and device, storage medium and terminal - Google Patents
circulating data supervision method and device, storage medium and terminal Download PDFInfo
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- CN110580625A CN110580625A CN201910693801.3A CN201910693801A CN110580625A CN 110580625 A CN110580625 A CN 110580625A CN 201910693801 A CN201910693801 A CN 201910693801A CN 110580625 A CN110580625 A CN 110580625A
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
- G06Q20/00—Payment architectures, schemes or protocols
- G06Q20/38—Payment protocols; Details thereof
- G06Q20/40—Authorisation, e.g. identification of payer or payee, verification of customer or shop credentials; Review and approval of payers, e.g. check credit lines or negative lists
- G06Q20/401—Transaction verification
- G06Q20/4016—Transaction verification involving fraud or risk level assessment in transaction processing
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
- G06Q40/00—Finance; Insurance; Tax strategies; Processing of corporate or income taxes
- G06Q40/04—Trading; Exchange, e.g. stocks, commodities, derivatives or currency exchange
Abstract
A method and a device for supervising circulating data, a storage medium and a terminal are provided, wherein the method for supervising the circulating data comprises the following steps: for each trading order, acquiring behavior state information of a data supplier in the trading order in a trading platform, attribute information of a data product in the trading order and trading information in the trading order according to a supervision period; analyzing the behavior state information to determine the risk level of the data supplier; analyzing the attribute information to determine the risk level of the data product; analyzing the transaction information, and determining a transaction risk level, wherein the transaction risk level can represent the abnormal degree of the transaction amount and/or the charging mode in the transaction information; and determining whether to check the content of the transaction data in the transaction order according to the risk level of the data supplier, the risk level of the data product and the transaction risk level. The technical scheme of the invention can realize the supervision of the flow data.
Description
Technical Field
the invention relates to the technical field of data processing, in particular to a method and a device for supervising circulating data, a storage medium and a terminal.
background
in the data transaction platform system, the transaction system determines the transaction products which are allowed to circulate by combing the circulation requirements, and clearly defines and describes the data range, content and use constraint conditions according to a data standard description method of 'six elements of metadata'. The data supplier carries out listing within the range of the transaction products, and the data demand party completes the order contract after the data demand party selects the required data products and confirms with the supplier in the transaction hall. In the validity period of the whole order, the demand side can initiate a data query request to the data supplier, and the supplier returns a query result.
however, the data transaction platform only retains queried log information at present, and the log information only comprises information such as transaction amount, transaction time, transaction state and the like; the data transaction platform does not store the query content and the result data, and cannot judge whether the current or the traced historical circulation content is legal or not.
disclosure of Invention
The technical problem solved by the invention is how to realize the supervision of the flow data.
in order to solve the above technical problem, an embodiment of the present invention provides a method for supervising circulation data, where the method for supervising circulation data includes: for each trading order, acquiring behavior state information of a data supplier in the trading order in a trading platform, attribute information of a data product in the trading order and trading information in the trading order according to a supervision period; analyzing the behavior state information to determine the risk level of the data supplier, wherein the risk level of the data supplier can represent the abnormal degree of the state of the data supplier; analyzing the attribute information to determine the risk level of the data product, wherein the risk level of the data product can represent the abnormal degree of the state of the data product; analyzing the transaction information, and determining a transaction risk level, wherein the transaction risk level can represent the abnormal degree of the transaction amount and/or the charging mode in the transaction information; and determining whether to check the content of the transaction data in the transaction order according to the risk level of the data supplier, the risk level of the data product and the transaction risk level.
optionally, the behavioral state information includes income flow, withdrawal amount and listing data product distribution, and the analyzing the behavioral state information includes: comparing the income running water in the current supervision period with the historical income running water in the same period or the income running water of a data supplier with the same type of listing data products to obtain an income running water abnormal score; comparing the withdrawal amount with a preset threshold value to obtain an abnormal score of the withdrawal amount; analyzing the product quantity in the listing data product distribution and the field to which the product belongs to determine the abnormal value of the product distribution; and calculating the risk level of the data supplier according to the income running water abnormal score, the withdrawal sum abnormal score, the product distribution abnormal score and the corresponding weight.
Optionally, the attribute information includes a product description, a listing unit price, and a transaction object, and analyzing the attribute information includes: performing semantic correlation analysis on the product description and words in a preset word bank to obtain a product abnormal score, wherein the words in the preset word bank are selected from sensitive words and illegal words; comparing the listing unit price with unit prices of the same type of listing data products to determine a price anomaly score; determining a transaction abnormal score according to the number of the transaction objects; and calculating the risk level of the data product according to the product abnormal score, the price abnormal score, the transaction abnormal score and the corresponding weight.
Optionally, the analyzing the transaction information includes: comparing the transaction amount in the current supervision period with the transaction amount in the historical supervision period to obtain an abnormal transaction amount score; performing text analysis on the charging mode to determine a charging abnormal score; and calculating the transaction risk level according to the transaction quantity abnormal score, the charging abnormal score and the corresponding weight.
optionally, the determining whether to check the content of the transaction data in the transaction order according to the risk level of the data supplier, the risk level of the data product, and the transaction risk level includes: calculating a risk level of the trade order according to the risk level of the data supplier, the risk level of the data product and the trade risk level; if the risk level of the trade order is smaller than a first preset level, adding the trade order to a white list, wherein the trade order in the white list cannot be checked in a preset number of supervision periods after the current supervision period; or if the risk level of the trade order is greater than the first preset level and less than a second preset level, continuing to calculate the risk level of the trade order in the next supervision period; or if the risk level of the trade order is greater than the second preset level, determining to check the content of the trade data in the trade order.
optionally, the method for supervising circulation data further includes: if the content of the transaction data in the transaction order is confirmed to be checked, extracting part of transaction data in the transaction order; acquiring a key from a data demand party indicated by the transaction order; and decrypting the part of transaction data by using the key, and performing content verification on the decrypted part of transaction data.
optionally, the method for supervising circulation data further includes: if the content of the transaction data in the transaction order is confirmed to be checked and the checking result is illegal, modifying the data product in the transaction order or sending warning information to the data supplier in the transaction order; or if the content of the transaction data in the transaction order is determined to be checked and the checking result is compliance, adding the transaction order to a white list, or continuing to calculate the risk level of the transaction order in the next supervision period, wherein the transaction order in the white list cannot be checked in the supervision periods of the preset number after the current supervision period.
in order to solve the above technical problem, an embodiment of the present invention further discloses a device for monitoring circulation data, where the device for monitoring circulation data includes: the trading order acquisition module is used for acquiring behavior state information of a data supplier in a trading order, attribute information of a data product in the trading order and trading information in the trading order according to a supervision period for each trading order; the behavior state analysis module is used for analyzing the behavior state information and determining the risk level of the data supplier, and the risk level of the data supplier can represent the abnormal degree of the state of the data supplier; the attribute analysis module is used for analyzing the attribute information and determining the risk level of the data product, wherein the risk level of the data product can represent the abnormal degree of the state of the data product; the transaction analysis module is used for analyzing the transaction information and determining a transaction risk level, wherein the transaction risk level can represent the abnormal degree of the transaction amount and/or the charging mode in the transaction information; and the checking determination module is used for determining whether to check the contents of the transaction data in the transaction order according to the risk level of the data supplier, the risk level of the data product and the transaction risk level.
The embodiment of the invention also discloses a storage medium, wherein a computer instruction is stored on the storage medium, and the steps of the circulation data supervision method are executed when the computer instruction runs.
The embodiment of the invention also discloses a terminal which comprises a memory and a processor, wherein the memory is stored with a computer instruction capable of running on the processor, and the processor executes the steps of the circulation data supervision method when running the computer instruction.
compared with the prior art, the technical scheme of the embodiment of the invention has the following beneficial effects:
In the embodiment of the invention, the risk level of the data supplier, the data product or the transaction information can be obtained by obtaining the behavior state information of the data supplier in the transaction order, the attribute information of the data product in the transaction order and the transaction information in the transaction order and analyzing the behavior abnormal condition of the data supplier, the data product or the transaction information, and the transaction data in the transaction order can be checked by determining the risk level, so that the technical problem that the transaction data cannot be supervised by using the transaction log information in the prior art is solved, the transaction data can be evaluated and supervised in all aspects from the aspects of the data supplier, the data product, the transaction information and the like, and the accuracy of supervision on the flow data is ensured.
Drawings
FIG. 1 is a flow chart of a method for monitoring circulation data according to an embodiment of the present invention;
FIG. 2 is a flowchart of one embodiment of step S102 shown in FIG. 1;
FIG. 3 is a flowchart of one embodiment of step S103 shown in FIG. 1;
FIG. 4 is a flowchart of one embodiment of step S104 shown in FIG. 1;
FIG. 5 is a flowchart of one embodiment of step S105 shown in FIG. 1;
Fig. 6 is a schematic structural diagram of a circulation data monitoring apparatus according to an embodiment of the present invention.
Detailed Description
As described in the background art, the data transaction platform only retains queried log information at present, and the log information only includes information such as transaction amount, transaction time, transaction state and the like; the data transaction platform does not store the query content and the result data, and cannot judge whether the current or the traced historical circulation content is legal or not.
In the embodiment of the invention, the risk level of the data supplier, the data product or the transaction information can be obtained by obtaining the behavior state information of the data supplier in the transaction order, the attribute information of the data product in the transaction order and the transaction information in the transaction order and analyzing the behavior abnormal condition of the data supplier, the data product or the transaction information, and the transaction data in the transaction order can be checked by determining the risk level, so that the technical problem that the transaction data cannot be supervised by using the transaction log information in the prior art is solved, the transaction data can be evaluated and supervised in all aspects from the aspects of the data supplier, the data product, the transaction information and the like, and the accuracy of supervision on the flow data is ensured.
In order to make the aforementioned objects, features and advantages of the present invention comprehensible, embodiments accompanied with figures are described in detail below.
Fig. 1 is a flowchart of a method for monitoring circulation data according to an embodiment of the present invention.
the circulation data supervision method may be executed on a data transaction platform, and specifically, each step of the method shown in fig. 1 may be executed by the data transaction platform.
the circulation data supervision method specifically comprises the following steps:
Step S101: for each trading order, acquiring behavior state information of a data supplier in the trading order in a trading platform, attribute information of a data product in the trading order and trading information in the trading order according to a supervision period;
step S102: analyzing the behavior state information to determine the risk level of the data supplier, wherein the risk level of the data supplier can represent the abnormal degree of the state of the data supplier;
Step S103: analyzing the attribute information to determine the risk level of the data product, wherein the risk level of the data product can represent the abnormal degree of the state of the data product;
Step S104: analyzing the transaction information, and determining a transaction risk level, wherein the transaction risk level can represent the abnormal degree of the transaction amount and/or the charging mode in the transaction information;
Step S105: and determining whether to check the content of the transaction data in the transaction order according to the risk level of the data supplier, the risk level of the data product and the transaction risk level.
It should be noted that the sequence numbers of the steps in this embodiment do not represent a limitation on the execution sequence of the steps.
In specific implementation, each transaction order can be supervised and monitored according to a supervision period so as to ensure the accuracy of supervision. The supervision period may be any practicable time length such as 3 months, 6 months, etc., and the embodiment of the present invention is not limited thereto.
In the specific implementation of step S101, since the trade order has the identifier of the data supplier, the identifier of the data product, and the trade information, such as the trade volume and the billing method, the data supplier and the data product can be determined, and further, the behavior state information of the data supplier in the trading platform and the attribute information of the data product in the trade order can be obtained.
Specifically, the transaction amount in the transaction information refers to the number of data products that completed the transaction.
The behavior state information of the data supplier can reflect the behavior and the state of the data supplier in the trading platform; the attribute information of the data product may be used to describe the data product.
further, in the specific implementation of step S102, the behavioral state information may be analyzed, and by analyzing the behavioral state information, the risk level of the data supplier may be determined, and further, whether and how much the state of the data supplier is abnormal may be determined, for example, a sudden increase in income or a sudden increase in cash of the data supplier during the supervision period indicates that the state of the data supplier is abnormal. The risk level may be represented using a risk score.
Furthermore, in the specific implementation of step S103, by analyzing the attribute information of the data product, the risk level of the data product can be determined, and further, whether the state of the data product is abnormal and the abnormal degree are determined, for example, if there is a sensitive word or an illegal word in the description of the data product, it indicates that the data product may be illegal data, that is, the data product is abnormal.
furthermore, in the specific implementation of step S104, by analyzing the transaction information, specifically, by analyzing the transaction amount and/or the charging manner in the transaction information, the transaction risk level may be determined to indicate whether the transaction amount or the charging manner of the transaction order is abnormal or abnormal, for example, if the transaction amount in the transaction order is significantly different from the transaction amount of the same type of product, it indicates that the transaction order may be abnormal.
In the specific implementation of step S105, the risk level of the trade order may be determined by combining the risk level of the data supplier, the risk level of the data product, and the trade risk level, and when the risk level of the trade order indicates that the abnormality degree of the order reaches a preset abnormality degree, the content of the trade data related to the trade order may be checked.
the verification of the transaction data in the embodiment of the present invention refers to determining whether the transaction data is illegal data, where the illegal data may refer to data that forbids transactions explicitly specified by a country or a regulatory body, such as data that endangers national security and social stability, data that relates to a specific personal equity, data that relates to a specific equity of an enterprise, and the like, specifically, data such as rumors, publicized sales of drugs, and privacy data of users who are not authorized by users.
In the embodiment of the invention, the risk level of the data supplier, the data product or the transaction information can be obtained by obtaining the behavior state information of the data supplier in the transaction order, the attribute information of the data product in the transaction order and the transaction information in the transaction order and analyzing the behavior abnormal condition of the data supplier, the data product or the transaction information, and the transaction data in the transaction order can be checked by determining the risk level, so that the technical problem that the transaction data cannot be supervised by using the transaction log information in the prior art is solved, the transaction data can be evaluated and supervised in all aspects from the aspects of the data supplier, the data product, the transaction information and the like, and the accuracy of supervision on the flow data is ensured.
In one embodiment of the invention, the behavioral state information includes revenue stream, withdrawal amount, and listing data product distribution. Referring to fig. 2, step S102 shown in fig. 1 may include the following steps:
Step S201: comparing the income running water in the current supervision period with the historical income running water in the same period or the income running water of a data supplier with the same type of listing data products to obtain an income running water abnormal score;
Step S202: comparing the withdrawal amount with a preset threshold value to obtain an abnormal score of the withdrawal amount;
Step S203: analyzing the product quantity in the listing data product distribution and the field to which the product belongs to determine the abnormal value of the product distribution;
Step S204: and calculating the risk level of the data supplier according to the income running water abnormal score, the withdrawal sum abnormal score, the product distribution abnormal score and the corresponding weight.
In this embodiment, the income flow may represent the income status of the data supplier, that is, the income distribution of the data supplier at each time in the supervision period. The withdrawal amount may represent the distribution of funds the data supplier draws from the transaction platform at various times during the regulatory period. The listing data product distribution may represent the distribution of data products listed by the data supplier on the transaction platform, for example, the distribution status of the field to which the listing data products belong, the distribution status of the number of the listing data products in the supervision period, and the like.
in a specific implementation, the income in the current supervision period may be kept running with the historical income in the same period, where the same period may refer to the same historical supervision period as the current supervision period is in, for example, the current supervision period is 1 month to 6 months of 2019, and then the same period may be 1 month to 6 months of 2018.
the revenue stream for the current regulatory period may also be compared to the revenue stream for data providers having the same type of listing data product. For example, if the type of data product being listed by the data supplier is credit data, then the comparison can be made with the income flow of the data supplier listing the credit data.
and determining the abnormal value of the income running water according to the comparison result of the income running water, namely the difference between the income running water in the current supervision period and the historical income running water in the same period or the income running water of the data supplier with the same type of listing data products.
Similarly, the withdrawal amount abnormal score can be determined by comparing the withdrawal amount with the difference of the preset threshold value.
in a specific implementation, the analyzing of the product quantity in the listing data product distribution may be analyzing a change condition of the product quantity in a supervision period, for example, whether a sudden increase or a sudden decrease of the quantity occurs. The analysis of the product domain may refer to analyzing a change condition of the product domain within a supervision period, for example, whether a condition of crossing the domain occurs multiple times.
Furthermore, each score has a corresponding weight, and the abnormal score of the data supplier can be calculated by utilizing the abnormal score of the income flow, the abnormal score of the withdrawal sum, the abnormal score of the product distribution and the corresponding weight thereof to serve as the risk level of the data supplier.
it should be noted that the size of the weight may be preset and may be adjusted according to an actual application requirement, which is not limited in this embodiment of the present invention.
In another embodiment of the present invention, the attribute information includes a product description, a listing unit price, and a transaction object, referring to fig. 3, step S103 shown in fig. 1 may include the following steps:
Step S301: performing semantic correlation analysis on the product description and words in a preset word bank to obtain a product abnormal score, wherein the words in the preset word bank are selected from sensitive words and illegal words;
Step S302: comparing the listing unit price with unit prices of the same type of listing data products to determine a price anomaly score;
Step S303: determining a transaction abnormal score according to the number of the transaction objects;
Step S304: and calculating the risk level of the data product according to the product abnormal score, the price abnormal score, the transaction abnormal score and the corresponding weight.
specifically, the transaction object may refer to a subject who performs a transaction with a data supplier, and may be, for example, a data demander. The number of the transaction objects refers to the number of data demanders transacting with the data supplier.
In this embodiment, the preset lexicon may be established in advance. The method can be specifically constructed by using pre-acquired sensitive words and/or violation words.
When semantic relevance analysis is performed on the product description and words in a preset word bank, word segmentation can be performed on the product description, and the words after word segmentation are input into a relevance model for semantic relevance analysis. Wherein the correlation model may be pre-trained. The higher the semantic relevance, the higher the product anomaly score, indicating a higher likelihood of an anomaly in the data product.
In specific implementation, the listing unit price and the unit prices of the listing data products of the same type can be compared, the listing data products of the same type refer to the data products of the same type, the comparison result can be the difference between the listing unit price and the unit prices of the listing data products of the same type, the larger the difference is, the more abnormal the listing unit price of the data product is, the higher the price abnormality score is, the higher the possibility that the data product is abnormal is.
Furthermore, each abnormal score has a corresponding weight, and the total abnormal score of the data product can be calculated by using each abnormal score and the corresponding weight thereof to serve as the risk level of the data product.
in another embodiment of the present invention, referring to fig. 4, step S104 shown in fig. 1 may include the following steps:
Step S401: comparing the transaction amount in the current supervision period with the transaction amount in the historical supervision period to obtain an abnormal transaction amount score;
step S402: performing text analysis on the charging mode to determine a charging abnormal score;
step S403: and calculating the transaction risk level according to the transaction quantity abnormal score, the charging abnormal score and the corresponding weight.
in a specific implementation, when analyzing the transaction amount, the transaction amount in the current supervision period may be compared with the transaction amount in the historical supervision period, for example, to determine whether the transaction amount in the current supervision period is increased or decreased compared with the transaction amount in the historical supervision period. The higher the traffic anomaly score, the higher the probability of indicating traffic anomaly.
When the charging mode is analyzed, because the charging mode can be text description, semantic analysis can be performed on the description text of the charging mode. For example, the abnormal discount of the charging mode is determined through semantic analysis. The higher the billing anomaly score, the higher the probability that the billing method is anomalous.
In a non-limiting embodiment of the present invention, referring to fig. 5, step S105 shown in fig. 1 may include the following steps:
step S501: calculating a risk level of the trade order according to the risk level of the data supplier, the risk level of the data product and the trade risk level;
step S502: if the risk level of the trade order is smaller than a first preset level, adding the trade order to a white list, wherein the trade order in the white list cannot be checked in a preset number of supervision periods after the current supervision period;
Step S503: if the risk level of the trade order is larger than the first preset level and smaller than a second preset level, continuously calculating the risk level of the trade order in the next supervision period;
Step S504: and if the risk level of the trade order is greater than the second preset level, determining to check the content of the trade data in the trade order.
in a specific implementation, one of the steps S502 to S504 may be selectively performed.
In this embodiment, the risk level of the trade order can be calculated by combining the risk level of the data supplier, the risk level of the data product, and the trade risk level. The higher the level of risk rating of a trade order, the higher the probability that an anomaly exists for the trade order.
In particular implementations, different weights may be assigned to the three types of risk levels. The three types of risk levels described above may be represented by risk scores, so the sum of the products of the three types of risk scores and their corresponding weights may be calculated as the risk level of the trade order.
the trade orders with different risk levels may enter different processing flows, for example, when the risk level of the trade order is less than a first preset level, the trade order may be added to a white list. And when the risk level of the trade order is higher than the second preset level, indicating that the data content of the trade order needs to be checked, otherwise, continuously calculating the risk level of the trade order in the next supervision period.
in one non-limiting embodiment of the present invention, the method shown in FIG. 1 may further comprise the steps of: if the content of the transaction data in the transaction order is confirmed to be checked, extracting part of transaction data in the transaction order; acquiring a key from a data demand party indicated by the transaction order; and decrypting the part of transaction data by using the key, and performing content verification on the decrypted part of transaction data.
in this embodiment, when it is determined to check the content of the transaction data in the transaction order, the transaction data can be checked through the processes of sampling and retaining and decrypting the data.
In specific implementation, when part of transaction data is extracted from a transaction order, a random sampling mode can be adopted; in the transmission files transmitted in batch for a plurality of times, a preset amount of transaction data can be extracted from each transmission file. And part of extracted transaction data can be stored in a transaction platform or a data demander so as to be called when verification is required in the subsequent steps.
specifically, since the transaction data is encrypted during the data circulation process, and the clear text of the transaction data needs to be obtained when the transaction data is checked, the transaction data can be decrypted by obtaining the key from the data demander.
more specifically, the process of content checking the decrypted partial transaction data may be: performing text analysis on the text of the decrypted partial transaction data to determine whether the text contains illegal contents; or, the decrypted partial transaction data may be compared with example data to determine whether the transaction data contains the illegal content, where the example content may be a data sample containing the illegal content; the decrypted portion of transaction data may also be submitted to a human for review.
in one non-limiting embodiment of the present invention, the method shown in FIG. 1 may further comprise the steps of: if the content of the transaction data in the transaction order is confirmed to be checked and the checking result is illegal, modifying the data product in the transaction order or sending warning information to the data supplier in the transaction order;
Or if the content of the transaction data in the transaction order is determined to be checked and the checking result is compliance, adding the transaction order to a white list, or continuing to calculate the risk level of the transaction order in the next supervision period, wherein the transaction order in the white list cannot be checked in the supervision periods of the preset number after the current supervision period.
Embodiments of the present invention may manage data suppliers, data products, and/or trade orders based on the results of the audit.
In specific implementation, when the checking result is violation, the data product in the transaction order may be modified, for example, the data product is placed off shelf; or sending warning information to the data supplier in the trading order.
when the checking result is compliance, the trade order can be added to a white list, namely the trade order does not need to be monitored in a short time; alternatively, the risk level of the trade order continues to be calculated in the next supervision cycle, i.e. the trade order is continuously monitored.
Referring to fig. 6, the embodiment of the present invention further discloses a circulation data monitoring apparatus 60, and the circulation data monitoring apparatus 60 may include a transaction order obtaining module 601, a behavior state analyzing module 602, an attribute analyzing module 603, a transaction analyzing module 604, and a verification determining module 605.
The trade order obtaining module 601 is configured to obtain, for each trade order, behavior state information of a data supplier in the trade order in a trade platform, attribute information of a data product in the trade order, and trade information in the trade order according to a supervision period; the behavioral state analysis module 602 is configured to analyze the behavioral state information and determine a risk level of the data provider, where the risk level of the data provider can represent a degree of abnormality of a state of the data provider; the attribute analysis module 603 is configured to analyze the attribute information and determine a risk level of the data product, where the risk level of the data product can indicate a degree of abnormality of a state of the data product; the transaction analysis module 604 is configured to analyze the transaction information and determine a transaction risk level, where the transaction risk level can indicate an abnormal degree of a transaction amount and/or a charging manner in the transaction information; the verification determination module 605 is configured to determine whether to verify the content of the transaction data in the transaction order according to the risk level of the data supplier, the risk level of the data product, and the transaction risk level.
according to the embodiment of the invention, the risk level of the data supplier, the data product or the transaction information can be obtained by acquiring the behavior state information of the data supplier in the transaction order, the attribute information of the data product in the transaction order and the transaction information in the transaction order and analyzing the behavior abnormal condition of the data supplier, the data product or the transaction information, and the transaction data in the transaction order is determined and checked by combining the risk level, so that the technical problem that the transaction data cannot be supervised by using the transaction log information in the prior art is solved, the transaction data can be comprehensively evaluated and supervised from the aspects of the data supplier, the data product, the transaction information and the like, and the accuracy of supervision on the flow data is ensured.
More contents of the operation principle and the operation mode of the circulation data monitoring device 60 can refer to the related descriptions in fig. 1 to 5, and are not described again here.
the embodiment of the invention also discloses a storage medium, wherein computer instructions are stored on the storage medium, and when the computer instructions are operated, the steps of the method shown in the figures 1 to 5 can be executed. The storage medium may include ROM, RAM, magnetic or optical disks, etc. The storage medium may further include a non-volatile memory (non-volatile) or a non-transitory memory (non-transient), and the like.
The embodiment of the invention also discloses a terminal which can comprise a memory and a processor, wherein the memory is stored with computer instructions capable of running on the processor. The processor, when executing the computer instructions, may perform the steps of the methods shown in fig. 1-5. The terminal includes, but is not limited to, a mobile phone, a computer, a tablet computer and other terminal devices.
Although the present invention is disclosed above, the present invention is not limited thereto. Various changes and modifications may be effected therein by one skilled in the art without departing from the spirit and scope of the invention as defined in the appended claims.
Claims (10)
1. a method of currency data administration, comprising:
For each trading order, acquiring behavior state information of a data supplier in the trading order in a trading platform, attribute information of a data product in the trading order and trading information in the trading order according to a supervision period;
analyzing the behavior state information to determine the risk level of the data supplier, wherein the risk level of the data supplier can represent the abnormal degree of the state of the data supplier;
Analyzing the attribute information to determine the risk level of the data product, wherein the risk level of the data product can represent the abnormal degree of the state of the data product;
Analyzing the transaction information, and determining a transaction risk level, wherein the transaction risk level can represent the abnormal degree of the transaction amount and/or the charging mode in the transaction information;
And determining whether to check the content of the transaction data in the transaction order according to the risk level of the data supplier, the risk level of the data product and the transaction risk level.
2. the method of currency data supervision according to claim 1, wherein the behavioural status information comprises revenue stream, cash out amount and branding data product distribution, and wherein the analyzing the behavioural status information comprises:
Comparing the income running water in the current supervision period with the historical income running water in the same period or the income running water of a data supplier with the same type of listing data products to obtain an income running water abnormal score;
comparing the withdrawal amount with a preset threshold value to obtain an abnormal score of the withdrawal amount;
Analyzing the product quantity in the listing data product distribution and the field to which the product belongs to determine the abnormal value of the product distribution;
and calculating the risk level of the data supplier according to the income running water abnormal score, the withdrawal sum abnormal score, the product distribution abnormal score and the corresponding weight.
3. The circulation data supervision method according to claim 1, wherein the attribute information includes product description, listing unit price and transaction object, and the analyzing the attribute information includes: performing semantic correlation analysis on the product description and words in a preset word bank to obtain a product abnormal score, wherein the words in the preset word bank are selected from sensitive words and illegal words;
Comparing the listing unit price with unit prices of the same type of listing data products to determine a price anomaly score;
Determining a transaction abnormal score according to the number of the transaction objects;
and calculating the risk level of the data product according to the product abnormal score, the price abnormal score, the transaction abnormal score and the corresponding weight.
4. The circulation data curation method according to claim 1, wherein the analysis of the transaction information comprises:
Comparing the transaction amount in the current supervision period with the transaction amount in the historical supervision period to obtain an abnormal transaction amount score;
Performing text analysis on the charging mode to determine a charging abnormal score;
And calculating the transaction risk level according to the transaction quantity abnormal score, the charging abnormal score and the corresponding weight.
5. the method of claim 1, wherein determining whether to audit the content of the trade data in the trade order based on the risk level of the data supplier, the risk level of the data product, and the trade risk level comprises:
calculating a risk level of the trade order according to the risk level of the data supplier, the risk level of the data product and the trade risk level;
If the risk level of the trade order is smaller than a first preset level, adding the trade order to a white list, wherein the trade order in the white list cannot be checked in a preset number of supervision periods after the current supervision period;
Or if the risk level of the trade order is greater than the first preset level and less than a second preset level, continuing to calculate the risk level of the trade order in the next supervision period;
Or if the risk level of the trade order is greater than the second preset level, determining to check the content of the trade data in the trade order.
6. The circulation data curation method according to claim 1, further comprising:
If the content of the transaction data in the transaction order is confirmed to be checked, extracting part of transaction data in the transaction order;
Acquiring a key from a data demand party indicated by the transaction order;
And decrypting the part of transaction data by using the key, and performing content verification on the decrypted part of transaction data.
7. The circulation data curation method according to claim 1, further comprising:
If the content of the transaction data in the transaction order is confirmed to be checked and the checking result is illegal, modifying the data product in the transaction order or sending warning information to the data supplier in the transaction order;
Or if the content of the transaction data in the transaction order is determined to be checked and the checking result is compliance, adding the transaction order to a white list, or continuing to calculate the risk level of the transaction order in the next supervision period, wherein the transaction order in the white list cannot be checked in the supervision periods of the preset number after the current supervision period.
8. A circulation data supervision apparatus, comprising:
The trading order acquisition module is used for acquiring behavior state information of a data supplier in a trading order, attribute information of a data product in the trading order and trading information in the trading order according to a supervision period for each trading order;
The behavior state analysis module is used for analyzing the behavior state information and determining the risk level of the data supplier, and the risk level of the data supplier can represent the abnormal degree of the state of the data supplier;
the attribute analysis module is used for analyzing the attribute information and determining the risk level of the data product, wherein the risk level of the data product can represent the abnormal degree of the state of the data product;
the transaction analysis module is used for analyzing the transaction information and determining a transaction risk level, wherein the transaction risk level can represent the abnormal degree of the transaction amount and/or the charging mode in the transaction information;
And the checking determination module is used for determining whether to check the contents of the transaction data in the transaction order according to the risk level of the data supplier, the risk level of the data product and the transaction risk level.
9. a storage medium having stored thereon computer instructions, wherein said computer instructions when executed perform the steps of the method of custody of circulation data according to any of claims 1 to 7.
10. a terminal comprising a memory and a processor, the memory having stored thereon computer instructions executable on the processor, wherein the processor, when executing the computer instructions, performs the steps of the method of custody of circulation data according to any of claims 1 to 7.
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