Financial data sharing safety monitoring method and system based on artificial intelligence

Abstract

The invention discloses a financial data sharing safety monitoring method and system based on artificial intelligence, and relates to the technical field of the next generation information network industry, and the system comprises a monitoring center which is in communication connection with a data collection module, an identification code obtaining module, an identification code detection module and an anomaly detection module. The financial data before sharing is acquired through the data acquisition module, the identification code of the acquired financial data before sharing is acquired through the identification code acquisition module, the identification code of the shared financial data is acquired through the identification code inspection module, and the identification code of the shared financial data is inspected. According to the financial data sharing method and device, whether the shared financial data is tampered or not is judged, the shared financial data which is not tampered is detected through the anomaly detection module, whether the shared financial data which is not tampered is abnormal or not is judged, dual detection is conducted on the shared financial data, and the safety of financial data sharing is further improved.

Description

Technical Field

[0001] The present invention relates to the technical field of next-generation information network industry, and specifically to a financial data sharing security monitoring method and system based on artificial intelligence. Background Art

[0002] With the rapid development of the financial services industry, the scale of enterprises has continued to expand, and their businesses have become more and more diversified. The types and quantities of financial data have continued to increase, and the complexity of data sharing has also increased. Financial data is an important basis for business decision-making, directly affecting the strategic planning, resource allocation and performance evaluation of enterprises. Enterprises need to comply with various financial regulations and audit requirements to ensure the authenticity, integrity and timeliness of financial data. Financial data contains a lot of sensitive information, and leakage or tampering will cause huge losses to enterprises. How to determine whether the shared financial data has been tampered with, and to detect the financial data that has not been tampered with after sharing, to determine whether the financial data that has not been tampered with after sharing is abnormal, and to further improve the security of financial data sharing are the problems we need to solve. To this end, a financial data sharing security monitoring method and system based on artificial intelligence are provided. Summary of the invention

[0003] In order to solve the above technical problems, the purpose of the present invention is to provide a financial data sharing security monitoring method and system based on artificial intelligence. The object of the present invention can be achieved by the following technical solutions: A financial data sharing security monitoring system based on artificial intelligence, comprising a monitoring center, wherein the monitoring center is communicatively connected with a data acquisition module, an identification code acquisition module, an identification code verification module and an abnormality detection module; The data collection module is used to collect the financial data before sharing; The identification code acquisition module is used to acquire the identification code of the collected financial data before sharing; The identification code verification module is used to obtain the identification code of the shared financial data, and verify the identification code of the shared financial data to determine whether the shared financial data has been tampered with; The anomaly detection module is used to detect the financial data that has not been tampered with after sharing, and determine whether the financial data that has not been tampered with after sharing is abnormal.

[0004] Furthermore, the process of the data collection module collecting the financial data before sharing includes: The data acquisition module is composed of a data acquisition terminal, and the data acquisition terminal is used to collect financial data; The data acquisition terminal is configured to generate a corresponding configuration channel. The corresponding server is linked through the generated configuration channel. The data acquisition terminal obtains the pre-sharing financial data in the corresponding server through the configuration channel and sends the obtained pre-sharing financial data to the identification code acquisition module.

[0005] Furthermore, the process of the identification code acquisition module acquiring the identification code of the collected financial data before sharing includes: Arrange characters in the financial data before sharing into a character string, convert each character in the character string into a corresponding ASCII code representation, convert the ASCII code of each character into a binary representation, combine the binary representations of all characters to obtain a binary financial data stream corresponding to the financial data before sharing, and segment the obtained binary financial data stream to obtain a number of binary financial data blocks corresponding to the financial data before sharing; Obtain a first check code and a second check code of a binary financial data block; An XOR operation is performed on the binary digits corresponding to the odd bits of the first check code of the binary financial data block and the binary digits corresponding to the odd bits of the second check code to obtain the binary digits corresponding to the odd bits in the identification code of the binary financial data block, and the binary digits corresponding to the even bits of the first check code of the binary financial data block are used as the binary digits corresponding to the even bits in the identification code of the binary financial data block to obtain the identification code of the binary financial data block corresponding to the financial data before sharing.

[0006] Furthermore, the process of segmenting the obtained binary financial data stream includes: Obtain the length of the binary financial data stream and set a segmentation interval, where the segmentation interval is recorded as Q, where Q is an even number, and the binary financial data stream is segmented once every Q bits to obtain a number of binary financial data blocks; Determine whether the lengths of each binary financial data block are the same, divide the length of the binary financial data stream by the segmentation interval, and obtain the quotient and remainder. If the remainder obtained is zero, the lengths of each binary financial data block are the same. If the remainder obtained is not zero, there is a binary financial data block whose length is different from the lengths of the other binary financial data blocks, and the binary financial data block whose length is different from the lengths of the other binary financial data blocks is recorded as a binary financial data block to be supplemented; The binary financial data block to be supplemented is supplemented to obtain the supplementary digit, the remainder is subtracted from the segmentation interval to obtain the supplementary digit, the supplementary digit is recorded as B, and B zeros are added to the end of the binary financial data block to be supplemented.

[0007] Furthermore, the process of obtaining the first check code and the second check code of the binary financial data block includes: Obtaining binary digits corresponding to odd-numbered bits and binary digits corresponding to even-numbered bits of a binary financial data block, performing an XOR operation on the binary digits corresponding to odd-numbered bits of the obtained binary financial data block and the binary digits corresponding to even-numbered bits, performing an XOR operation on the binary digits corresponding to odd-numbered bits of the obtained binary financial data block and the binary digits corresponding to even-numbered bits, adding the XOR operation result to the end of the XOR operation result, and obtaining a first check code of the binary financial data block; An XOR operation is performed on the first check code of the binary financial data block and the binary financial data block, and an inversion operation is performed on the XOR operation result to obtain a second check code of the binary financial data block.

[0008] Furthermore, the identification code verification module obtains the identification code of the shared financial data, and the process of verifying the identification code of the shared financial data includes: Obtain a binary financial data stream corresponding to the shared financial data, segment the binary financial data stream corresponding to the shared financial data, obtain a binary financial data block corresponding to the shared financial data, obtain an identification code of the binary financial data block corresponding to the shared financial data, and compare the identification code of the binary financial data block corresponding to the shared financial data with the identification code of the binary financial data block corresponding to the financial data before sharing. If the comparison results are the same, the shared financial data has not been tampered with. If the comparison results are different, the shared financial data has been tampered with, and relevant personnel are reminded to handle it in a timely manner.

[0009] Furthermore, the process of the anomaly detection module detecting the financial data that has not been tampered with after sharing includes: An anomaly detection model is constructed by artificial intelligence technology, wherein a two-dimensional coordinate system is constructed in the anomaly detection model, and the financial data that has not been tampered with after sharing is input into the anomaly detection model. The anomaly detection model quantifies the input financial data that has not been tampered with after sharing, and maps the quantified result into the two-dimensional coordinate system to obtain a number of financial data points; Get the neighborhood of each financial data point. The circle with the financial data point as the center and r as the radius is the neighborhood of the financial data point, where r is a positive number. Obtain the number of other financial data points in the neighborhood of each financial data point and set a quantity threshold. If the number of other financial data points in the neighborhood of the financial data point is greater than or equal to the set quantity threshold, the financial data point is recorded as a core financial data point. If the number of other financial data points in the neighborhood of the financial data point is less than the set quantity threshold and the financial data point is located in the neighborhood of the remaining financial data points, the financial data point is recorded as a boundary financial data point. If there are financial data points that are not recorded as core financial data points or boundary financial data points, the financial data that has not been tampered with after sharing is abnormal, and the anomaly detection model outputs the financial data that has not been tampered with after sharing is abnormal, reminding relevant personnel to handle it in a timely manner; If there are no financial data points that are not recorded as core financial data points or boundary financial data points, the financial data that has not been tampered with after sharing is normal, the anomaly detection model outputs the financial data that has not been tampered with after sharing is normal, and the financial data sharing is safe.

[0010] The present invention also discloses a financial data sharing security monitoring method based on artificial intelligence, comprising the following steps: Step 1: Obtain the financial data before sharing and obtain the identification code of the financial data before sharing; Step 2: Obtain the identification code of the shared financial data, and verify the identification code of the shared financial data to determine whether the shared financial data has been tampered with; Step 3: Detect the financial data that has not been tampered with after sharing to determine whether the financial data that has not been tampered with after sharing is abnormal.

[0011] Compared with the prior art, the beneficial effects of the present invention are: collecting financial data before sharing, obtaining identification codes of the collected financial data before sharing, obtaining identification codes of the financial data after sharing, and verifying the identification codes of the financial data after sharing, judging whether the shared financial data has been tampered with, detecting the financial data that has not been tampered with after sharing, judging whether the financial data that has not been tampered with after sharing is abnormal, and performing double detection on the financial data after sharing, thereby ensuring that the shared financial data has no security threats and further improving the security of financial data sharing. BRIEF DESCRIPTION OF THE DRAWINGS

[0012] Figure 1 It is a schematic diagram of the present invention. DETAILED DESCRIPTION

[0013] like Figure 1 As shown, a financial data sharing security monitoring system based on artificial intelligence includes a monitoring center, and the monitoring center is communicatively connected with a data acquisition module, an identification code acquisition module, an identification code verification module and an anomaly detection module; The data collection module is used to collect the financial data before sharing; It should be further explained that, in the specific implementation process, the process of the data collection module collecting the financial data before sharing includes: The data acquisition module is composed of a data acquisition terminal, and the data acquisition terminal is used to collect financial data; The data acquisition terminal is configured to generate a corresponding configuration channel. The corresponding server is linked through the generated configuration channel. The data acquisition terminal obtains the pre-sharing financial data in the corresponding server through the configuration channel and sends the obtained pre-sharing financial data to the identification code acquisition module.

[0014] The identification code acquisition module is used to acquire the identification code of the collected financial data before sharing; It should be further explained that, in a specific implementation process, the process of the identification code acquisition module acquiring the identification code of the collected financial data before sharing includes: Arrange the characters in the financial data before sharing into a character string, convert each character in the character string into a corresponding ASCII code representation, convert the ASCII code of each character into an 8-bit binary representation, combine the binary representations of all characters to obtain a binary financial data stream corresponding to the financial data before sharing, and segment the obtained binary financial data stream to obtain a number of binary financial data blocks corresponding to the financial data before sharing; It should be further explained that, in the specific implementation process, the process of segmenting the obtained binary financial data stream includes: Get the length of the binary financial data stream, and record the length of the binary financial data stream as L d , set a segmentation interval, record the set segmentation interval as Q, Q is an even number, segment the binary financial data stream once every Q bits to obtain a number of binary financial data blocks; Determine whether the lengths of each binary financial data block are the same, divide the length of the binary financial data stream by the segmentation interval, and obtain the quotient and remainder. If the remainder obtained is zero, the lengths of each binary financial data block are the same. If the remainder obtained is not zero, there is a binary financial data block whose length is different from the lengths of the other binary financial data blocks, and the binary financial data block whose length is different from the lengths of the other binary financial data blocks is recorded as a binary financial data block to be supplemented; The binary financial data block to be supplemented is supplemented to obtain the supplementary digit, the remainder is subtracted from the segmentation interval to obtain the supplementary digit, the supplementary digit is recorded as B, and B zeros are added to the end of the binary financial data block to be supplemented; For example: the binary financial data stream is 00100100101, the length of the binary financial data stream is 11, and the segmentation interval is set to 4, then the obtained binary financial data blocks are 0010, 0100 and 101, the remainder of the length of the binary financial data stream divided by the segmentation interval is 3, then the number of supplementary bits is 1, and the supplemented binary financial data block is supplemented, and the supplemented data block is 1010; Obtain the binary digits corresponding to the odd bits and the binary digits corresponding to the even bits of the first binary financial data block, perform an XOR operation on the binary digits corresponding to the odd bits and the binary digits corresponding to the even bits of the first binary financial data block, perform an XOR operation on the binary digits corresponding to the odd bits and the binary digits corresponding to the even bits of the first binary financial data block, add the XOR operation result to the end of the XOR operation result, and obtain a first check code of the first binary financial data block; Obtain the binary digits corresponding to the odd bits and the binary digits corresponding to the even bits of the second binary financial data block, perform an XOR operation on the binary digits corresponding to the odd bits and the binary digits corresponding to the even bits of the obtained second binary financial data block, perform an XOR operation on the binary digits corresponding to the odd bits and the binary digits corresponding to the even bits of the obtained second binary financial data block, add the XOR operation result to the end of the XOR operation result, and obtain a first check code of the second binary financial data block; And so on, the first checksums of the remaining binary financial data blocks are obtained; Performing an XOR operation on the first check code of the first binary financial data block and the first binary financial data block, and performing an inversion operation on the XOR operation result to obtain a second check code of the first binary financial data block; Performing an XOR operation on the first check code of the second binary financial data block and the second binary financial data block, and performing an inversion operation on the XOR operation result to obtain a second check code of the second binary financial data block; And so on, the second check codes of the remaining binary financial data blocks are obtained; Perform an XOR operation on the binary digits corresponding to the odd bits of the first check code of the first binary financial data block and the binary digits corresponding to the odd bits of the second check code to obtain the binary digits corresponding to the odd bits in the identification code of the first binary financial data block, and use the binary digits corresponding to the even bits of the first check code of the first binary financial data block as the binary digits corresponding to the even bits in the identification code of the first binary financial data block to obtain the identification code of the first binary financial data block corresponding to the financial data before sharing; Perform an XOR operation on the binary digits corresponding to the odd bits of the first check code of the second binary financial data block and the binary digits corresponding to the odd bits of the second check code to obtain the binary digits corresponding to the odd bits in the identification code of the second binary financial data block, and use the binary digits corresponding to the even bits of the first check code of the second binary financial data block as the binary digits corresponding to the even bits in the identification code of the second binary financial data block to obtain the identification code of the second binary financial data block corresponding to the financial data before sharing; And so on, the identification codes of the binary financial data blocks corresponding to the remaining financial data before sharing are obtained.

[0015] The identification code verification module is used to obtain the identification code of the shared financial data, and verify the identification code of the shared financial data to determine whether the shared financial data has been tampered with; It should be further explained that, in a specific implementation process, the identification code verification module obtains the identification code of the shared financial data, and the process of verifying the identification code of the shared financial data includes: Obtain a binary financial data stream corresponding to the shared financial data, segment the binary financial data stream corresponding to the shared financial data, obtain a binary financial data block corresponding to the shared financial data, obtain an identification code of the binary financial data block corresponding to the shared financial data, and compare the identification code of the binary financial data block corresponding to the shared financial data with the identification code of the binary financial data block corresponding to the financial data before sharing. If the comparison results are the same, the shared financial data has not been tampered with. If the comparison results are different, the shared financial data has been tampered with, and relevant personnel are reminded to handle it in a timely manner.

[0016] The anomaly detection module is used to detect the financial data that has not been tampered with after sharing, and determine whether the financial data that has not been tampered with after sharing is abnormal; It should be further explained that, in the specific implementation process, the process of the anomaly detection module detecting the financial data that has not been tampered with after sharing includes: An anomaly detection model is constructed by artificial intelligence technology, wherein a two-dimensional coordinate system is constructed in the anomaly detection model, and the financial data that has not been tampered with after sharing is input into the anomaly detection model. The anomaly detection model quantifies the input financial data that has not been tampered with after sharing, and maps the quantified result into the two-dimensional coordinate system to obtain a number of financial data points; Get the neighborhood of each financial data point. The circle with the financial data point as the center and r as the radius is the neighborhood of the financial data point, where r is a positive number. Obtain the number of other financial data points in the neighborhood of each financial data point and set a quantity threshold. If the number of other financial data points in the neighborhood of the financial data point is greater than or equal to the set quantity threshold, the financial data point is recorded as a core financial data point. If the number of other financial data points in the neighborhood of the financial data point is less than the set quantity threshold and the financial data point is located in the neighborhood of the remaining financial data points, the financial data point is recorded as a boundary financial data point. If there are financial data points that are not recorded as core financial data points or boundary financial data points, the financial data that has not been tampered with after sharing is abnormal, and the anomaly detection model outputs the financial data that has not been tampered with after sharing is abnormal, reminding relevant personnel to handle it in a timely manner; If there are no financial data points that are not recorded as core financial data points or boundary financial data points, the financial data that has not been tampered with after sharing is normal, the anomaly detection model outputs the financial data that has not been tampered with after sharing is normal, and the financial data sharing is safe.

[0017] The present invention also discloses a monitoring method of a financial data sharing security monitoring system based on artificial intelligence, comprising the following steps: Step 1: Obtain the financial data before sharing and obtain the identification code of the financial data before sharing; Step 2: Obtain the identification code of the shared financial data, and verify the identification code of the shared financial data to determine whether the shared financial data has been tampered with; Step 3: Detect the financial data that has not been tampered with after sharing to determine whether the financial data that has not been tampered with after sharing is abnormal.

[0018] The above embodiments are only used to illustrate the technical method of the present invention rather than to limit it. Although the present invention has been described in detail with reference to the preferred embodiments, those skilled in the art should understand that the technical method of the present invention may be modified or replaced by equivalents without departing from the spirit and scope of the technical method of the present invention.

Claims

1. A financial data sharing security monitoring system based on artificial intelligence, including a monitoring center, characterized in that: The monitoring center is communicatively connected to a data acquisition module, an identification code acquisition module, an identification code verification module and an anomaly detection module; The data collection module is used to collect the financial data before sharing; The identification code acquisition module is used to acquire the identification code of the collected financial data before sharing; The identification code verification module is used to obtain the identification code of the shared financial data, and verify the identification code of the shared financial data to determine whether the shared financial data has been tampered with; The anomaly detection module is used to detect the financial data that has not been tampered with after sharing, and determine whether the financial data that has not been tampered with after sharing is abnormal.

2. According to claim 1, a financial data sharing security monitoring system based on artificial intelligence is characterized in that: The process of the data collection module collecting the financial data before sharing includes: The data acquisition module is composed of a data acquisition terminal, and the data acquisition terminal is used to collect financial data; The data acquisition terminal is configured to generate a corresponding configuration channel. The corresponding server is linked through the generated configuration channel. The data acquisition terminal obtains the pre-sharing financial data in the corresponding server through the configuration channel and sends the obtained pre-sharing financial data to the identification code acquisition module.

3. According to claim 2, a financial data sharing security monitoring system based on artificial intelligence is characterized in that: The process of the identification code acquisition module acquiring the identification code of the collected financial data before sharing includes: Arrange characters in the financial data before sharing into a character string, convert each character in the character string into a corresponding ASCII code representation, convert the ASCII code of each character into a binary representation, combine the binary representations of all characters to obtain a binary financial data stream corresponding to the financial data before sharing, and segment the obtained binary financial data stream to obtain a number of binary financial data blocks corresponding to the financial data before sharing; Obtain a first check code and a second check code of a binary financial data block; An XOR operation is performed on the binary digits corresponding to the odd bits of the first check code of the binary financial data block and the binary digits corresponding to the odd bits of the second check code to obtain the binary digits corresponding to the odd bits in the identification code of the binary financial data block, and the binary digits corresponding to the even bits of the first check code of the binary financial data block are used as the binary digits corresponding to the even bits in the identification code of the binary financial data block to obtain the identification code of the binary financial data block corresponding to the financial data before sharing.

4. The financial data sharing security monitoring system based on artificial intelligence according to claim 3 is characterized in that: The process of segmenting the obtained binary financial data stream includes: Obtain the length of the binary financial data stream and set a segmentation interval, where the segmentation interval is recorded as Q, where Q is an even number, and the binary financial data stream is segmented once every Q bits to obtain a number of binary financial data blocks; Determine whether the lengths of each binary financial data block are the same, divide the length of the binary financial data stream by the segmentation interval, and obtain the quotient and remainder. If the remainder obtained is zero, the lengths of each binary financial data block are the same. If the remainder obtained is not zero, there is a binary financial data block whose length is different from the lengths of the other binary financial data blocks, and the binary financial data block whose length is different from the lengths of the other binary financial data blocks is recorded as a binary financial data block to be supplemented; The binary financial data block to be supplemented is supplemented to obtain the supplementary digit, the remainder is subtracted from the segmentation interval to obtain the supplementary digit, the supplementary digit is recorded as B, and B zeros are added to the end of the binary financial data block to be supplemented.

5. The financial data sharing security monitoring system based on artificial intelligence according to claim 4 is characterized in that: The process of obtaining the first check code and the second check code of the binary financial data block includes: Obtaining binary digits corresponding to odd-numbered bits and binary digits corresponding to even-numbered bits of a binary financial data block, performing an XOR operation on the binary digits corresponding to odd-numbered bits of the obtained binary financial data block and the binary digits corresponding to even-numbered bits, performing an XOR operation on the binary digits corresponding to odd-numbered bits of the obtained binary financial data block and the binary digits corresponding to even-numbered bits, adding the XOR operation result to the end of the XOR operation result, and obtaining a first check code of the binary financial data block; An XOR operation is performed on the first check code of the binary financial data block and the binary financial data block, and an inversion operation is performed on the XOR operation result to obtain a second check code of the binary financial data block.

6. The financial data sharing security monitoring system based on artificial intelligence according to claim 5 is characterized in that: The process in which the identification code verification module obtains the identification code of the shared financial data and verifies the identification code of the shared financial data includes: Obtain a binary financial data stream corresponding to the shared financial data, segment the binary financial data stream corresponding to the shared financial data, obtain a binary financial data block corresponding to the shared financial data, obtain an identification code of the binary financial data block corresponding to the shared financial data, and compare the identification code of the binary financial data block corresponding to the shared financial data with the identification code of the binary financial data block corresponding to the financial data before sharing. If the comparison results are the same, the shared financial data has not been tampered with. If the comparison results are different, the shared financial data has been tampered with, and relevant personnel are reminded to handle it in a timely manner.

7. The financial data sharing security monitoring system based on artificial intelligence according to claim 6 is characterized in that: The process of the anomaly detection module detecting the financial data that has not been tampered with after sharing includes: An anomaly detection model is constructed by artificial intelligence technology, wherein a two-dimensional coordinate system is constructed in the anomaly detection model, and the financial data that has not been tampered with after sharing is input into the anomaly detection model. The anomaly detection model quantifies the input financial data that has not been tampered with after sharing, and maps the quantified result into the two-dimensional coordinate system to obtain a number of financial data points; Get the neighborhood of each financial data point. The circle with the financial data point as the center and r as the radius is the neighborhood of the financial data point, where r is a positive number. Obtain the number of other financial data points in the neighborhood of each financial data point and set a quantity threshold. If the number of other financial data points in the neighborhood of the financial data point is greater than or equal to the set quantity threshold, the financial data point is recorded as a core financial data point. If the number of other financial data points in the neighborhood of the financial data point is less than the set quantity threshold and the financial data point is located in the neighborhood of the remaining financial data points, the financial data point is recorded as a boundary financial data point. If there are financial data points that are not recorded as core financial data points or boundary financial data points, the financial data that has not been tampered with after sharing is abnormal, and the anomaly detection model outputs the financial data that has not been tampered with after sharing is abnormal, reminding relevant personnel to handle it in a timely manner; If there are no financial data points that are not recorded as core financial data points or boundary financial data points, the financial data that has not been tampered with after sharing is normal, the anomaly detection model outputs the financial data that has not been tampered with after sharing is normal, and the financial data sharing is safe.

8. A financial data sharing security monitoring method based on artificial intelligence, specifically applied to a financial data sharing security monitoring system based on artificial intelligence as claimed in any one of claims 1 to 7, characterized in that: The following steps are involved: Step 1: Obtain the financial data before sharing and obtain the identification code of the financial data before sharing; Step 2: Obtain the identification code of the shared financial data, and verify the identification code of the shared financial data to determine whether the shared financial data has been tampered with; Step 3: Detect the financial data that has not been tampered with after sharing to determine whether the financial data that has not been tampered with after sharing is abnormal.

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