CN115795523A - Loan information encryption management platform based on financial big data - Google Patents
Loan information encryption management platform based on financial big data Download PDFInfo
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Abstract
The invention relates to the technical field of data encryption, in particular to a loan information encryption management platform based on financial big data, which comprises: the obtaining module is used for obtaining the similarity between any user loan data string in the plurality of user loan data strings and other user loan data strings; the splicing module is used for splicing the loan data string of any user with the loan data string of the similar user according to the similarity to obtain a first data string; the data conversion module is used for acquiring the frequency count of each data in the first data string, matching the data in the first data string according to the frequency count to obtain a data pair, and converting the first data in the data pair into second data to obtain a second data string, wherein the frequency count of the first data is greater than that of the second data; and the encryption module is used for scrambling and encrypting the second data string to obtain a third data string as a ciphertext. The invention can improve the encryption degree of the user loan information, thereby improving the safety of the user loan information.
Description
Technical Field
The invention relates to the technical field of data encryption, in particular to a loan information encryption management platform based on financial big data.
Background
At present, information science and technology are rapidly developing, cloud computing and big data technology are widely applied to various fields, and for future financial industry, mining valuable information from big data is core competitiveness. Therefore, the storage confidentiality of the financial big data is important, wherein the data of the loan information not only comprises the core data of a bank, but also comprises the privacy data of a client, and the confidentiality of the data is extremely high.
In the prior art, a frequency encryption method based on data is adopted to encrypt the user loan information, and the encrypted data has obvious statistical characteristics, so that the encryption degree of the user loan information is low and the user loan information is easy to crack, and the safety of the user loan information is low.
Disclosure of Invention
In order to solve the problem of low encryption degree of user loan information, the invention provides a loan information encryption management platform based on financial big data, and the adopted technical scheme is as follows:
the invention provides a loan information encryption management platform based on financial big data, which comprises:
the system comprises an acquisition module, a processing module and a processing module, wherein the acquisition module is used for acquiring loan information of a user from financial big data, the loan information comprises a plurality of user loan data strings and acquiring the similarity between any user loan data string in the user loan data strings and other user loan data strings;
the splicing module is used for determining a similar user loan data string similar to the loan data string of any user from the loan data strings of other users according to the similarity, and splicing the loan data string of any user with the loan data string of the similar user to obtain a first data string;
the data conversion module is used for obtaining the frequency count of each data in the first data string, matching the data in the first data string according to the frequency count to obtain a data pair, and converting first data in the data pair into second data to obtain a second data string, wherein the frequency count of the first data is greater than the frequency count of the second data;
and the encryption module is used for scrambling and encrypting the second data string to obtain a third data string and determining that the third data string is the ciphertext of any user loan data string.
In some embodiments, the obtaining the similarity between any one of the user loan data strings and the other user loan data strings includes:
determining the same data and different data in the loan data string of any user and the loan data strings of other users, and acquiring a first amount of the same data and a second amount of the different data;
obtaining a first frequency count of the same data in any user loan data string and a second frequency count of the same data in other user loan data strings;
extracting all data in the loan data string of any user and the loan data strings of other users to obtain a target data set, and acquiring the data average frequency of the target data set;
and acquiring the similarity according to the first number, the second number, the first frequency, the second frequency, the data average frequency and a set weight coefficient.
In some embodiments, the obtaining the similarity according to the first number, the second number, the first frequency, the second frequency, the data average frequency, and a set weight coefficient includes:
wherein the content of the first and second substances,
for any similarity between the user's loan data string and the other user's loan data string,
for a first amount of the same data in any one user's loan data string and in other user's loan data strings,
for any user loan data string and a second amount of different data in other user loan data strings,
is a first
The first frequency of the same data in any user loan data string,
is as follows
A second frequency of the same data in the other user loan data strings,
the average frequency of the data for the target data set,
and
are all the weight coefficients of the weight coefficient,
are indices of the same data.
In some embodiments, the determining, from the other user loan data strings according to the similarity, a similar user loan data string similar to the any user loan data string includes:
and determining the maximum similarity from the similarities, and determining the user loan data string corresponding to the maximum similarity as the similar user loan data string.
In some embodiments, the matching the data in the first data string according to the frequency count to obtain a data pair includes:
sorting the data in the first data string according to the size sequence of the frequency counts to obtain a data sequence;
and sequentially matching data at two ends of the data sequence to be used as the data pair.
In some embodiments, the scrambling and encrypting the second data string to obtain a third data string includes:
determining a two-dimensional data table according to the data quantity of the second data string;
determining a set starting mapping position and a set mapping sequence of the two-dimensional data table, and mapping the data in the second data string into the two-dimensional data table from the set starting mapping position according to the set mapping sequence;
and determining a set initial traversal position and a set traversal order of the two-dimensional data table, and traversing the two-dimensional data table from the set initial traversal position according to the set traversal order to obtain the third data string.
The invention has the following beneficial effects: because the statistical characteristics of the single user loan data string are usually obvious and the encryption effect is poor during encryption, the loan data string of the user is spliced in order to improve the encryption effect, so that the statistical characteristics of the data string are reduced subsequently, and the encryption effect of the loan information can also be improved by converting the encryption of the single data string into the encryption of the spliced data string. The two similar user loan data strings are spliced, the frequency of each data in the original user loan data string can be changed as much as possible, and therefore the statistical characteristic of the original user loan data string is changed, and the encryption effect is improved. By converting the high-frequency data in the spliced user loan data string into the corresponding low-frequency data, the frequency of different data in the user loan data string can be more balanced, thereby reducing the statistical characteristics of the user loan data string and further enhancing the encryption degree of loan information. By scrambling and encrypting the second data string, the data encryption degree of the loan information can be further improved, so that the safety of the loan information is ensured.
Drawings
In order to more clearly illustrate the embodiments of the present invention or the technical solutions and advantages of the prior art, the drawings used in the embodiments or the description of the prior art will be briefly described below, it is obvious that the drawings in the following description are only some embodiments of the present invention, and other drawings can be obtained by those skilled in the art without creative efforts.
Fig. 1 is a schematic structural diagram of a loan information encryption management platform based on financial big data according to an embodiment of the present invention;
FIG. 2 is a schematic diagram of a zigzag scanning method according to an embodiment of the present invention;
FIG. 3 is a schematic diagram of another zigzag scanning method according to an embodiment of the present invention.
Detailed Description
To further illustrate the technical means and effects of the present invention for achieving the predetermined objects, the following detailed description, structures, features and effects of a loan information encryption management platform based on financial big data according to the present invention will be provided with reference to the accompanying drawings and preferred embodiments. In the following description, different "one embodiment" or "another embodiment" refers to not necessarily the same embodiment. Furthermore, the particular features, structures, or characteristics may be combined in any suitable manner in one or more embodiments.
Unless defined otherwise, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this invention belongs.
In the technical scheme of the invention, the data acquisition, storage, use, processing and the like all conform to relevant regulations of national laws and regulations.
The following describes a specific scheme of a loan information encryption management platform based on financial big data in detail with reference to the accompanying drawings.
Referring to fig. 1, a schematic structural diagram of a financial big data-based loan information encryption management platform according to an embodiment of the present invention is shown, where the loan information encryption management platform 10 includes an obtaining module 101, a splicing module 102, a data transformation module 103, and an encryption module 104.
The obtaining module 101 is configured to obtain loan information of the user from the financial big data, where the loan information includes a plurality of user loan data strings, and obtain a similarity between any one of the user loan data strings in the plurality of user loan data strings and a loan data string of another user.
The loan information of the user can comprise information such as name, telephone, address, amount and the like, the information data of each user can be arranged according to a certain sequence, and then each arranged data is converted into a decimal code by referring to an ASCII code table to obtain a decimal code sequence as a user loan data string.
In the embodiment of the invention, the method for acquiring the similarity between any user loan data string in a plurality of user loan data strings and other user loan data strings comprises the following steps:
s101, the same data and different data in any user loan data string and other user loan data strings are determined, and a first quantity of the same data and a second quantity of the different data are obtained.
The first amount is the amount of the same data between the loan data string of any user and the loan data strings of other users, and the second amount is the amount of different data between the loan data string of any user and the loan data strings of other users.
S102, obtaining a first frequency count of the same data in any user loan data string and a second frequency count of the same data in other user loan data strings.
The first frequency is the frequency of the same data between any user loan data string and other user loan data strings appearing in any user loan data string, and the second frequency is the frequency of different data between any user loan data string and other user loan data strings appearing in other user loan data strings.
S103, extracting all data in any user loan data string and other user loan data strings to obtain a target data set, and obtaining the data average frequency of the target data set.
All data in any user loan data string and other user loan data strings are extracted into a target data set, the data category number of the target data set and the frequency count of each type of data are obtained, the sum of the frequency counts of all types of data is calculated, and the ratio of the sum to the number category number is used as the data average frequency count of the target data set.
It should be noted that, in the embodiment of the present invention, the same data in the target data set is regarded as one category.
And S104, acquiring the similarity according to the first number, the second number, the first frequency, the second frequency, the data average frequency and the set weight coefficient.
Alternatively, the similarity may be calculated by the following formula.
Wherein the content of the first and second substances,
for any user's similarity between the loan data string and the loan data strings of other users,
for any user loan data string and other user loan data strings for a first amount of the same data,
for any user loan data string and a second amount of different data in other user loan data strings,
is as follows
The first frequency of the same data in any user loan data string,
is as follows
Loan data of other users with the same dataThe second frequency count in the series is,
the average frequency of the data for the target data set,
and
all the weight coefficients are set as the weight coefficients,
are indices of the same data.
The weight coefficient is
And
can be set according to actual requirements, is not limited at all, and optionally,
，
。
in the embodiment of the invention, the more data which are the same between the loan data string of any user and the loan data string of other users, namely the first amount of data which are the same between the loan data string of any user and the loan data string of other users
The larger the similarity between the loan data string of any user and the loan data strings of other users, and therefore the similarity
And a first amount
In a positive correlation relationship. The less data that is different between any user loan data string and other user loan data strings, i.e. any user loan data string and othersSecond amount of data identical to user loan data string
The smaller the similarity between the loan data string of any user and the loan data string of the other user, and the greater the similarity, therefore
And a first number
In a negative correlation relationship.
The data distribution difference before and after the data string of any user loan and the data string of other users loan can be reflected, the larger the difference is, the lower the degree between the data string of any user loan and the data string of other users loan is, namely, the similarity is
The smaller and thus the data distribution difference
Similarity with
In a negative correlation relationship. Therefore, the accuracy of the similarity between any user loan data string and other user loan data strings is improved by considering the first quantity of the same data and the second quantity of different data in any user loan data string and other user loan data strings and the data distribution difference before and after the any user loan data string and other user loan data strings are spliced.
And the splicing module 102 is used for determining a similar user loan data string similar to the loan data string of any user from the loan data strings of other users according to the similarity, and splicing the loan data string of any user and the loan data string of the similar user to obtain a first data string.
In some embodiments, the maximum similarity is determined from the similarities, and the user loan data string corresponding to the maximum similarity is determined to be the similar user loan data string.
Specifically, after the similarity between any user loan data string and each other user loan data string is obtained, the magnitude of each similarity is compared to determine the maximum similarity, and the user loan data string corresponding to the maximum similarity is determined as the similar user loan data string.
The data conversion module 103 is configured to obtain a frequency count of each data in the first data string, match data in the first data string according to the frequency count to obtain a data pair, convert the first data in the data pair into second data, and obtain a second data string, where the frequency count of the first data is greater than the frequency count of the second data.
In some embodiments, the data in the first data string are sorted according to the size order of the frequency count to obtain a data sequence, and the data at the two ends of the data sequence are sequentially matched to serve as a data pair.
The data in the first data string may be sorted in the order of frequency count from large to small or from small to large to obtain a data sequence, and then the data at both ends of the data sequence are sequentially matched to serve as a data pair. If the data in the first data string are arranged in the order from small frequency count to large frequency count to obtain a data sequence, the left end data of the data sequence is the second data in the data pair, the right end data of the data sequence is the first data in the data pair, and the first data is converted into the second data; if the data in the first data string are arranged in the order of the frequency count from large to small to obtain the data sequence, the left data of the data sequence is the first data in the data pair, the right data of the data sequence is the second data in the data pair, and the first data is converted into the second data. After the first data in each data pair in the first data string is transformed into the second data, the second data string is obtained.
When the total number of data in the data sequence is an odd number, the data in the middle of the data sequence is not subjected to the conversion processing.
Optionally, the first data may be transformed into the second data by using a linear transformation, or the first data may also be transformed into the second data by using any other possible way, which is not limited herein.
Because data are encrypted based on data frequency, high-frequency data can appear, and the statistical characteristics of the high-frequency data are obvious and are easy to crack according to the statistical characteristics of the high-frequency data. In the embodiment of the invention, the data frequency of the spliced data string can be balanced by splicing the similar data strings and converting the high-frequency data in the spliced data string into the corresponding low-frequency data, so that the statistical characteristics of the user loan data string are reduced, the encryption degree of the data is further improved, and the safety of the data is ensured.
And the encryption module 104 is configured to scramble and encrypt the second data string to obtain a third data string, and determine that the third data string is a ciphertext of any user loan data string.
Optionally, the two-dimensional data table is determined according to the data quantity of the second data string, a set starting mapping position and a set mapping order of the two-dimensional data table are determined, data in the two-dimensional data table are mapped into the two-dimensional data table from the set starting mapping position according to the set mapping order, a set starting traversal position and a set traversal order of the two-dimensional data table are determined, and the two-dimensional data table is traversed from the set starting traversal position according to the set traversal order to obtain a third data string.
In the embodiment of the invention, the two-dimensional data table is a data table with the same height and width, and the size of the two-dimensional data table can be obtained through the following formula:
wherein the content of the first and second substances,
is the height or width of the two-dimensional data table,
is the amount of data of the second data string,
means to take the bestA large integer.
In the embodiment of the present invention, after the two-dimensional data table is determined, a zigzag scanning method may be used to map data in the second data string into the two-dimensional data table, where the scanning start points include an upper left scanning start point, a lower left scanning start point, an upper right scanning start point, and a lower right scanning start point, where each scanning start point corresponds to one scanning order, the upper left scanning start point corresponds to the first scanning order, the lower left scanning start point corresponds to the second scanning order, the upper right scanning start point corresponds to the third scanning order, and the lower right scanning start point corresponds to the third scanning order. Wherein the first scanning order is opposite to the fourth scanning order, and the second scanning order is opposite to the third scanning order.
Fig. 2 is a schematic diagram of a zigzag scanning method according to an embodiment of the present invention, as shown in fig. 2, a two-dimensional data table is scanned in a first scanning order with an upper left scanning start point as a start point. When scanning the two-dimensional data table with the lower right scanning point as the starting point, scanning is performed in the reverse order of the first scanning order shown in fig. 2, that is, in the fourth scanning order.
Fig. 3 is a schematic diagram of another zigzag scanning method according to an embodiment of the present invention, as shown in fig. 3, the two-dimensional data table is scanned in a second scanning order with a lower left scanning point as a starting point. When scanning the two-dimensional data table with the upper right scanning point as the starting point, scanning is performed in the reverse order of the second scanning order shown in fig. 3, that is, in the third scanning order.
In the embodiment of the invention, the initial mapping position is set as the position of any scanning starting point, and the mapping sequence is set as the scanning sequence corresponding to any scanning starting point.
For example, assuming that the starting mapping position is set as the position where the upper-left scanning starting point is located, and the mapping order is the scanning order corresponding to the upper-left scanning starting point, the data in the second data string may be extracted according to the left-to-right order, and the extracted data may be sequentially stored in the two-dimensional data table according to the scanning order corresponding to the upper-left scanning starting point shown in fig. 2.
In the embodiment of the invention, the initial traversal position is set as the position of any scanning starting point, and the traversal sequence is set as the scanning sequence corresponding to any scanning starting point.
It should be noted that, the set initial mapping position and the set initial traversal position are positions of different scanning starting points, and accordingly, the scanning order corresponding to the set mapping order and the set traversal order is different.
For example, if the initial traversal position is set as the position of the lower right scanning start point, and the traversal order is set as the scanning order corresponding to the lower right scanning start point, the two-dimensional data table may be traversed from the lower right scanning start point according to the scanning order corresponding to the lower right scanning start point, so as to obtain the third data string. And the scanning sequence corresponding to the upper left scanning starting point is opposite to the scanning sequence corresponding to the lower right scanning starting point.
The third data string may be used as a ciphertext of a loan data string of any user, and all data in the loan information may be encrypted in the above manner to obtain a plurality of ciphertexts.
In the embodiment of the present invention, since the set mapping order is different from the set traversal order, and the set initial mapping position is different from the set initial traversal position, after the second data string is mapped into the two-dimensional data table and the third data string is obtained by traversing the two-dimensional data table, the data order in the second data string is disturbed, that is, the data order of the second data string is different from that of the third data string. By disordering the data sequence in the second data string, the confidentiality of the data can be further improved, and the encryption degree of the data can be improved.
Further, after all the data in the loan information are encrypted, a corresponding key can be obtained, so that the corresponding ciphertext can be decrypted according to the key.
In some embodiments, a first data quantity of any user loan data string, a second data quantity of a similar user loan data string of the loan information string of any user, a first position parameter of the loan data string of any user in the second data string, a second position parameter of the loan data string of similar users in the second data string, a transformation parameter for transforming the first data into the second data, a third position parameter for setting a starting mapping position and a fourth position parameter for setting a starting traversal position are obtained, and a corresponding key is generated according to the first data quantity, the second data quantity, the first position parameter, the second position parameter, the transformation parameter, the third position parameter and the fourth position parameter.
If the first position parameter is 0 and the second position parameter is 1, it indicates that any user loan information string in the second data string is located on the left side of the similar user loan data string, and if the first position parameter is 1 and the second position parameter is 0, it indicates that any user loan information string in the second data string is located on the right side of the similar user loan data string.
In some embodiments, when transforming the first data of the data pair in the first data string into the second data by linear transformation, the second data is assumed to be
The first data is
The transformation parameters can be calculated by the following formula, respectively
And transformation parameters
。
Wherein, the first and the second end of the pipe are connected with each other,
is the slope parameter of the linear transformation,
is the intercept parameter of the linear transformation,
is the second data to be transmitted to the first data,
as the first data, it is the first data,
indicating taking the largest integer.
Accordingly, the function for transforming the first data into the second data is:
=
。
in determining the transformation parameters
And transformation parameters
Then, the conversion parameter can be used for decryption
And transformation parameters
The second data is transformed into the first data.
Further, the conversion parameter includes a conversion number and a conversion position parameter, where the conversion data amount is the number of the data pairs, and the conversion position parameter is a position parameter of the first data, and the position parameter of the first data, for example, a position index of the first data in the first data string, may be recorded as the conversion position parameter when the first data is converted into the second data.
In the embodiment of the present invention, when scrambling and encrypting the second data string, as shown in fig. 2, the scanning start points include an upper left scanning start point, a lower left scanning start point, an upper right scanning start point, and a lower right scanning start point, and the position of the upper left scanning start point may be represented by a parameter 0, the position of the lower left scanning start point may be represented by a parameter 1, the position of the upper right scanning start point may be represented by a parameter 2, and the position of the lower right scanning start point may be represented by a parameter 3. That is, the third position parameter may be 0, 1, 2, or 3, and the fourth position parameter may also be 0, 1, 2, or 3. Wherein the third position parameter is different from the fourth position parameter.
Specifically, after the first data quantity, the second data quantity, the first position parameter, the second position parameter, the transformation parameter, the third position parameter and the fourth position parameter are obtained, the first data quantity, the second data quantity, the first position parameter, the second position parameter, the transformation parameter, the third position parameter and the fourth position parameter may be spliced according to a set sequence to obtain a group of arrays as a key, and the key is stored for decryption of the ciphertext.
The decryption process of the ciphertext by using the key is as follows:
(1) And extracting a fourth position parameter in the secret key, determining a set initial traversal position and a set traversal sequence according to the fourth position parameter, setting the set initial traversal position as an initial mapping position, setting the set traversal sequence as a mapping sequence, and sequentially mapping the data in the secret key into the two-dimensional data table from the initial mapping position according to the mapping sequence. And extracting a third position parameter in the key, determining a set initial mapping position and a set mapping sequence according to the third position parameter, taking the set initial mapping position as an initial traversal position, taking the set mapping sequence as a traversal sequence, and traversing the two-dimensional data table from the initial traversal position according to the traversal sequence to obtain a second data string.
(2) And extracting transformation parameters in the key, and performing inverse transformation processing when encrypting the data in the second data string according to the transformation parameters to obtain the first data string.
(3) And extracting the first data quantity, the second data quantity, the first position parameter and the second position parameter in the key, and determining two user loan data strings in the first data string according to the first data quantity, the second data quantity, the first position parameter and the second position parameter.
(4) And respectively converting the two user loan data strings in the first data string into original data by contrasting the ASCII code table, and finishing decryption, wherein the original data is a plaintext before encryption.
In summary, in the embodiment of the present invention, since the statistical characteristics of the single user loan data string are usually obvious and the encryption effect is poor when encryption is performed, in order to improve the encryption effect, the present invention performs splicing processing on the user loan data string, so as to reduce the statistical characteristics of the data string subsequently, and can also improve the encryption effect of the loan information by transforming the encryption of the single data string into the encryption of the spliced data string. The two similar user loan data strings are spliced, the frequency of each data in the original user loan data string can be changed as much as possible, and therefore the statistical characteristic of the original user loan data string is changed, and the encryption effect is improved. By converting the high-frequency data in the spliced user loan data string into the corresponding low-frequency data, the frequency of different data in the user loan data string can be more balanced, thereby reducing the statistical characteristics of the user loan data string and further enhancing the encryption degree of loan information. By scrambling and encrypting the second data string, the data encryption degree of the loan information can be further improved, so that the safety of the loan information is ensured.
It should be noted that: the precedence order of the above embodiments of the present invention is only for description, and does not represent the merits of the embodiments. The processes depicted in the accompanying figures do not necessarily require the particular order shown, or sequential order, to achieve desirable results. In some embodiments, multitasking and parallel processing may also be possible or may be advantageous.
The embodiments in the present specification are described in a progressive manner, and the same and similar parts among the embodiments are referred to each other, and each embodiment focuses on the differences from the other embodiments.
Claims (6)
1. A loan information encryption management platform based on financial big data is characterized by comprising:
the system comprises an acquisition module, a processing module and a processing module, wherein the acquisition module is used for acquiring loan information of a user from financial big data, the loan information comprises a plurality of user loan data strings and acquiring the similarity between any user loan data string in the user loan data strings and other user loan data strings;
the splicing module is used for determining a similar user loan data string similar to the loan data string of any user from the loan data strings of other users according to the similarity, and splicing the loan data string of any user with the loan data string of the similar user to obtain a first data string;
the data conversion module is used for obtaining the frequency count of each data in the first data string, matching the data in the first data string according to the frequency count to obtain a data pair, and converting first data in the data pair into second data to obtain a second data string, wherein the frequency count of the first data is greater than the frequency count of the second data;
and the encryption module is used for scrambling and encrypting the second data string to obtain a third data string and determining that the third data string is the ciphertext of any user loan data string.
2. The financial big data-based loan information encryption management platform according to claim 1, wherein the obtaining of the similarity between any one of the user loan data strings and the other user loan data strings comprises:
determining the same data and different data in the loan data string of any user and the loan data strings of other users, and acquiring a first quantity of the same data and a second quantity of the different data;
obtaining a first frequency count of the same data in any user loan data string and a second frequency count of the same data in other user loan data strings;
extracting all data in the loan data string of any user and the loan data strings of other users to obtain a target data set, and acquiring the data average frequency of the target data set;
and acquiring the similarity according to the first number, the second number, the first frequency, the second frequency, the data average frequency and a set weight coefficient.
3. The financial big data-based loan information encryption management platform according to claim 2, wherein the similarity is obtained according to the first amount, the second amount, the first frequency, the second frequency, the data average frequency and a set weight coefficient, and the calculation formula includes:
wherein, the first and the second end of the pipe are connected with each other,
for any user's similarity between the loan data string and the loan data strings of other users,
for a first amount of the same data in any one user's loan data string and in other user's loan data strings,
for any user loan data string and a second amount of different data in the other user loan data strings,
is as follows
The first frequency of the same data in any of the user's loan data strings,
is a first
A second frequency count of the same data in the other user loan data strings,
the average frequency of the data for the target data set,
and
are all the weight coefficients of the weight coefficient,
are indices of the same data.
4. The financial big data-based loan information encryption management platform according to claim 1, wherein the determining, from the other user loan data strings, a similar user loan data string similar to the loan data string of any user according to the similarity comprises:
and determining the maximum similarity from the similarities, and determining the user loan data string corresponding to the maximum similarity as the similar user loan data string.
5. The financial big data-based loan information encryption management platform according to claim 1, wherein the matching of the data in the first data string according to the frequency number to obtain a data pair comprises:
sorting the data in the first data string according to the size sequence of the frequency counts to obtain a data sequence;
and sequentially matching data at two ends of the data sequence to be used as the data pair.
6. The financial big data-based loan information encryption management platform according to claim 1, wherein the scrambling and encryption processing of the second data string to obtain a third data string comprises:
determining a two-dimensional data table according to the data quantity of the second data string;
determining a set starting mapping position and a set mapping sequence of the two-dimensional data table, and mapping data in the second data string to the two-dimensional data table from the set starting mapping position according to the set mapping sequence;
and determining a set initial traversal position and a set traversal order of the two-dimensional data table, and traversing the two-dimensional data table from the set initial traversal position according to the set traversal order to obtain the third data string.
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